Machine Learning

Nutanix, a pioneer in hybrid multicloud computing, today published findings from the healthcare vertical edition of its eighth annual Enterprise Cloud Index (ECI) survey. The report, which examines infrastructure readiness, AI adoption, and containerisation trends across healthcare organisations globally, reveals a sector under mounting pressure. AI deployment is being driven from the top, shadow AI is proliferating across clinical and administrative functions, and the infrastructure required to support secure, compliant AI workloads at the point of care is not yet in place. As AI moves from the data centre to the bedside, where up to 75% of healthcare data is expected to be generated, the stakes around infrastructure readiness, data sovereignty, and clinical governance have never been higher. The findings show that while healthcare IT leaders recognise the transformative potential of AI, including through autonomous agents and real-time clinical decision support, the organisational and infrastructure gaps required to realise that potential remain significant. Patient safety issue "Clinicians are exhausted, and they're turning to AI because they genuinely believe it can help them, and they're right,” said Sammy Zoghlami, SVP EMEA at Nutanix. “But when 88% of healthcare organisations tell us their infrastructure isn't ready to support AI on-premises, and nearly four in five are already encountering AI tools being deployed outside of IT oversight, that tells us that innovation is coming second to risk. The industry needs to get the foundations right before the gap between AI ambition and readiness becomes a patient safety issue." Maintaining clinical continuity Key findings from the 2026 Nutanix Healthcare ECI report include: Shadow AI is widespread and largely unmanaged: Seventy-nine percent of healthcare organisations encounter AI applications or agents being implemented by employees in non-IT functions, and 83% believe that AI tools and agents operating outside official oversight create business risk. The same proportion, 83%, say silos between business units and IT make it difficult to effectively execute technology initiatives, deepening the governance challenge as AI adoption scales. Infrastructure is not ready for AI at the point of care: Eighty-eight percent of healthcare IT leaders view their current infrastructure as not fully ready to support deploying AI workloads on-premises. This is a significant gap given that AI inference at the point of care, rather than via cloud-only processing, is increasingly seen as essential to eliminating latency risks in clinical settings. Single patient rooms can generate up to 7TB of data annually, and high-density device environments such as ICU beds can include 15 to 20 connected devices, requiring local, low-latency AI processing to maintain clinical continuity. AI is accelerating container adoption as healthcare modernises its application strategy: Eighty-six percent of healthcare organisations say AI is meaningfully accelerating their adoption of containers, which enable AI models to be deployed locally at the bedside in secure, portable environments. Eighty-one percent expect the level of application containerisation to increase at their organisation, and 80% are already building new applications in containers. Containers allow hospitals to keep data where it is generated, within their own walls, while enabling real-time AI-driven insights without compromising network performance. AI agents are seen as transformative for healthcare operations: Fifty-eight percent of healthcare IT leaders expect AI agents to improve productivity and efficiency, 57% anticipate agents will transform business processes and operations, and more than half (55%) see potential for AI agents to create new products, services, or revenue streams. Looking three years ahead, 57% of organisations anticipate using agentic AI or autonomous agents, alongside generative AI (62%) and predictive analytics or machine learning models (55%). Data sovereignty is a must-have, not a nice-to-have: Seventy-two percent of healthcare organisations say data sovereignty is a high priority or a must-include when making infrastructure decisions. Fifty-four percent run containerised applications on-premises or on private clouds today, and 54% feel the need to run infrastructure within a single country due to customer or stakeholder expectations. This reflects the sensitivity of protected health information (PHI) and the compliance requirements governing where this data can be stored and processed. AI adoption is being driven from the top, with scale coming fast: Fifty-five percent of healthcare organisations anticipate having more than five AI-enabled applications within three years, including 12% who expect to be running more than 10. Sixty-three percent currently run AI applications on managed service providers, with hybrid deployment models expected to remain the norm as organisations look to support AI centrally and at the point of care. Together, these findings paint a clear picture: healthcare organisations are accelerating into AI without the infrastructure beneath them to support it safely. Closing the gap from the data centre to the bedside requires a fundamental rethink of how healthcare IT is architected, governed, and scaled. Maintaining regulatory compliance The findings point to a sector at critical stage in its innovation journey. AI is more than just a consideration for healthcare and is already running in containerised environments, across hybrid infrastructures, and increasingly at the point of care. But the picture underneath is messy as organisations are juggling workloads across on-premises systems, private clouds, and managed services simultaneously, often without the unified infrastructure strategy to support them consistently or safely. For healthcare IT leaders, this creates a clear mandate. AI workloads at the bedside demand infrastructure that can deliver performance, maintain regulatory compliance, and support clinical governance. Not just centrally, but locally, where latency and continuity directly affect patient outcomes. A cloud-only approach is no longer sufficient. Clinical continuity and patient outcomes depend on healthcare organisations fundamentally rethinking how they architect for AI by building secure data environments, scalable compute, and reliable application delivery across the entire business.

SharpEagle Technology, a pioneer in explosion-proof surveillance and industrial safety solutions, announces a series of major advancements in hazardous area monitoring technology — establishing new performance, compliance, and intelligence benchmarks for high-risk industrial environments worldwide. With a growing international footprint spanning the Middle East, Europe, and the United Kingdom, SharpEagle continues to push the boundaries of what industrial-grade safety surveillance can achieve. Adjacent industrial operations Industries operating in hazardous zones — including oil refineries, petrochemical plants, offshore platforms, and mining facilities — face unique and life-threatening safety challenges. Conventional surveillance systems fall short in extreme conditions defined by flammable gases, high-pressure environments, and explosive atmospheres. SharpEagle's latest generation of ATEX and IECEx-certified camera systems are engineered to meet and exceed these demands, while its AI-powered forklift safety and reverse sensor tools bring intelligent monitoring to adjacent industrial operations. Programmable safety zones SharpEagle's latest innovations include: Forklift Reverse Sensor System: Advanced programmable safety zones with instant alerts for industrial vehicles — operating reliably in dust, fog, and low-visibility conditions. AI Forklift CCTV Solutions: Real-time AI analytics that have demonstrated a 30% reduction in warehouse incidents, combining pedestrian detection, speed monitoring, and blind spot elimination. ATEX Digital Camera Systems: High-resolution explosion-proof cameras built for extreme industrial environments, now recognised by QYResearch as a globally leading product in the ATEX camera market. Forklift Reverse Camera and Sensor System: UK industrial facilities using this system have reported up to a significant reduction in blind-spot-related incidents, setting a new safety standard for heavy-vehicle operations. International research reports "The industrial world cannot afford to compromise on safety — and neither can we. These advancements reflect years of engineering excellence, customer collaboration, and an unwavering commitment to protecting people in the world's most dangerous workplaces. We are not just building cameras; we are setting the global standard for what hazardous area surveillance should be," said Moiz Saeed, Founder & CEO, SharpEagle Technology. SharpEagle's commitment to innovation has earned it a shortlisting in the prestigious "Machine Learning / AI Project of the Year" category at the 2025 Digital Technology Leaders Awards, organised by Computing — recognising its outstanding work in applying AI to forklift safety and industrial operations. The company has also been featured as a Key Player in the Global Forklift 360-Degree Camera Market by The Business Research Company, and has gained global recognition in the ATEX camera market across international research reports. Adopting smarter monitoring technology As global industrial safety regulations tighten — particularly across the EU, UK, and GCC regions — organisations operating in hazardous environments face increasing pressure to demonstrate compliance, reduce incident rates, and adopt smarter monitoring technology. SharpEagle addresses these mandates on two fronts: ATEX/IECEx-certified explosion-proof cameras for hazardous area compliance, and AI-powered forklift safety and radar detection systems that deliver real-time situational awareness and audit-ready reporting for industrial operations. SharpEagle's full range of explosion-proof cameras, AI forklift safety systems, and Forklift reverse camera and sensor system are available globally.

Global technology solutions provider Arrow Electronics has announced a global network of experience centres, fortified to help channel partners define high-growth technology use and augment the skills and resources needed to bridge the gap between opportunity and implementation. The centres, located in Alpharetta, Georgia, United States, and in Stockholm, Sweden, serve as strategic hubs for vendors, channel partners and end customers across Europe and North America and are part of Arrow’s commitment to remain at the forefront of AI, cloud and security advancements. Networking “Our goal is to help organisations better understand how to harness the power of AI and cloud so our customers can securely and confidently use it and put it to work to address real-world challenges,” said Ben Klay, president of Arrow’s enterprise computing solutions business in North America. “By networking our centres globally, we are able to create the same experiences and environments, regardless of location, so our channel partners can immerse themselves and their customers in a solution before investing.” Core areas of support Arrow’s experience centres are designed to enable both vendors and channel partners to better understand the role of high-growth technologies such as AI within IT environments, including machine learning, modeling, data science, and more. Support at the experience centres is focused in three core areas: Hybrid infrastructure — creating and demonstrating multi-vendor hardware and software solutions, infused with vendor-focused capabilities, to meet the demands of organisations seeking secure, on-premise cloud and AI deployments. Cybersecurity, risk and resilience — aiding in the creation of solutions that protect critical systems, data and operations from an increasingly complex threat landscape, reduce risk and drive organisational resilience. Services and consultancy — providing training enablement, guidance and knowledge exchange to help identify potential gaps and opportunities with solution implementation. Adaptable AI use Within the centers, Arrow channel partners can access over 100 pre-built and tested solutions or create custom solutions with support from Arrow engineers and technicians. This helps ensure proven and adaptable AI use cases are suited to each channel partner’s or customer’s business. Arrow channel partners who have used experience centers to demonstrate their solutions have averaged a 90 percent close rate on their proposals. Unlocking the potential of AI “With many organisations still in the early stages of defining their AI strategies, Arrow has made the investment in the environment, technical support and tools needed to help us unlock the potential of AI with a vendor-agnostic approach to maximise innovation and ease of solutions deployment,” said Luiz Cordeiro, chief executive officer for SYSTECH, a global solutions provider and Arrow channel partner. “Our comprehensive solution encompassed compute, storage, networking, data protection and security, and Arrow did an unbelievable job with helping us create a demonstrable solution to meet our customers’ needs.” Arrow’s experience centers support high-growth technology areas including AI, cloud, security and multivendor solutions.

Honeywell announces the expansion of its Operational Technology (OT) Cybersecurity Suite, delivering advanced, proactive protection for industrial environments facing an accelerating wave of sophisticated cyber threats. The enhanced portfolio integrates powerful new capabilities designed to defend critical infrastructure, streamline security compliance, and assist organisations to stay ahead of increasingly complex attacks. Cyber-attacks against operational technology assets continue to grow in both frequency and sophistication, however, according to The World Economic Forum’s annual Global Cybersecurity Outlook, only 32% of organisations with industrial environments actively monitor OT systems and just 20% maintain dedicated OT security teams. Recognising these risks, Honeywell’s OT Cybersecurity Suite equips industrial companies to move beyond reactive security models and adopt a unified, forward-looking approach to cyber resilience. Targeting critical operations “The cybersecurity landscape for industrial organisations continues to evolve rapidly, with increasingly advanced threats targeting critical operations,” said Jim Masso, President and CEO of Honeywell Process Automation. “Organisations with a unified cybersecurity strategy across both digital and physical environments are setting a solid foundation for operational resilience while also avoiding potentially dangerous and costly attacks.” Honeywell’s expanded OT cybersecurity suite includes five new capabilities that build on the platform’s current offerings to protect critical infrastructure and minimise operational risk: Secure Media Exchange (SMX) Portable Scanner: SMX is a specialised cyber-physical solution designed to protect industrial facilities and critical infrastructure from threats carried in on USBs and other removable media devices. Powered by advanced anti-virus and industry-leading threat intelligence, the new SMX Portable Scanner enables deep inspection of storage devices, Windows-based machines and air-gapped systems, reducing the risk of malware entering critical environments and disrupting supply chains. Delivering actionable insights Cyber Proactive Defense (CPD): CPD is a next generation AI-powered monitoring solution purpose-built for Operational Technology (OT) environments facing increasingly more sophisticated cyber-attacks. Using advanced analytics and real-time monitoring, it correlates alerts across process and automation tools to deliver actionable insights, enabling organisations to proactively identify, prioritise, and mitigate threats before they escalate into full-scale attacks and impact critical operations. Cyber Governance Risk and Compliance (GRC): Streamlining compliance management, Cyber GRC automates evidence collection and audit reporting through AI and machine learning capabilities. The software reduces administrative burden by transforming weeks of manual effort into hours while providing greater visibility into security posture. High security standards Data Diode: Protecting sensitive data flows is paramount in industrial environments. Honeywell’s data diode allows for secure, unidirectional data transfer, helping isolate critical systems and maintain high security standards in OT domains. OT Security Operations Center (SOC): As a managed service for network and endpoint monitoring, the OT SOC equips organisations with the expertise and resources needed to respond swiftly to incidents. With 24/7 monitoring and a vendor-agnostic hub, it enhances incident response, minimises asset downtime, and helps ensure operational continuity. The comprehensive expansion of Honeywell’s OT Cybersecurity Suite is available now and is engineered for deployment across various sectors, including manufacturing, energy, and critical infrastructure.

The showcase combines AI compute platforms, industrial storage, connectivity, sensing, and software technologies to support scalable and secure AI deployment across enterprise and industrial applications. Innodisk, a global AI solution provider, will showcase its complete edge AI ecosystem at COMPUTEX 2026, demonstrating how enterprises and industrial customers can accelerate AI deployment for production-ready applications. Built across five essential layers—compute, memory, storage, sensing and communication, and software—the portfolio brings together AI platforms, industrial modules, and real-world application demos to support secure, scalable AI adoption. Secure enterprise AI deployment At the centre of this year’s showcase are Innodisk’s on-premises AI solutions for secure enterprise AI deployment. AccelBrain, powered by the APEX-X200, enables fully on-premises deployment of open-source LLMs with 100% data sovereignty. Complementing it, AccelTune provides a no-code LLM fine-tuning experience, demonstrated on the APEX-S100 featuring Intel® Xeon® 6700-series processors and supporting dual NVIDIA RTX PRO GPU. Together, these solutions help enterprises build secure, application-specific LLM workflows without relying on public cloud infrastructure. Enhance operator awareness Beyond enterprise AI, Innodisk will demonstrate how edge AI can be deployed in demanding industrial environments. A heavy machinery safety solution showcases eight ruggedised GMSL2 camera modules rated IP67 and IP69K, delivering AI-driven surround-view stitching, Driver Monitoring System (DMS), and Blind Spot Detection (BSD) to enhance operator awareness and safety in harsh field applications. Innodisk, an Intel Gold Partner, will also present the APEX-E400 edge AI system, powered by Intel® Core™ Ultra Series 3 processors. Built on a heterogeneous CPU-GPU-NPU architecture, the system supports up to 16 simultaneous streams with parallel AI model inference. A live Intel OpenVINO™ demo will highlight adaptive workload distribution across the tri-engine architecture for optimised edge AI performance. Automatic emergency braking In collaboration with Qualcomm Technologies, Inc., Innodisk continues to expand its AI on Qualcomm Dragonwing™ series for compact, power-efficient edge inference, showcasing the latest Dragonwing processors, across the IQ9, IQ10 and IQ-X Series, in the Innodisk booth. Powered by the Dragonwing IQ-9075 processor-based COM-HPC Mini platform, there will be live demos showcasing AI screw thread inspection and multi-stream vision processing, while an AMR demonstration further integrates GMSL and depth cameras for spatial awareness, ROI safety zone detection, and PWM-triggered automatic emergency braking. Automatic emergency braking Software enablement is another key layer of the ecosystem. Innodisk integrates Edge Impulse’s end-to-end edge AI machine learning operations (MLOps) platform with iCAP, Innodisk’s intelligent cloud management platform, to demonstrate Agentic AI capabilities for automated remote model updates and deployment. Supporting these AI systems is Innodisk’s industrial-grade memory, storage, connectivity, and sensing portfolio. The company will showcase next-generation DDR5 8000 RDIMM, CUDIMM, and CSODIMM, along with industry-pioneer 12800 MRDIMM and a new CXL Add-in Card (AIC). Storage highlights include Data center SSDs in EDSFF and U.2 form factors, as well as 218-layer 3D TLC SSDs. Ruggedised camera solutions In connectivity, Innodisk debuts the ELPL-82F1 SFP28 25GbE LAN card, alongside the award-winning EGPL-T2F1—honoured at Embedded World 2026 as the world’s first SFP+ LAN card in M.2 form factor. The booth will also feature ruggedised camera solutions across GMSL2, MIPI, and USB interfaces, complemented by an interactive OCR container identification demo running on an integrated edge system. Together, these demonstrations show how Innodisk brings together its complete five-layer AI ecosystem, helping customers deploy AI securely, reliably, and at scale across enterprise and industrial environments. Experience Innodisk’s advanced edge AI solutions at Booth No. K0106, Taipei Nangang Exhibition Center, Hall 1.

Building on the success of Global Security Exchange (GSX) 2025, which welcomed participants from 95 countries, GSX 2026 is set to deliver another exceptional lineup of thought leadership and innovation. Taking place 14-16 September at the Georgia World Congress Center in Atlanta, Georgia, the event will feature 200+ education sessions, 500+ exhibitors, and three transformational keynote speakers who will challenge security professionals to think differently about leadership, technology, and resilience in an evolving threat landscape. Evolving threat landscape "Our members face complex, high stakes challenges every day, and they deserve a stage that matches that reality,” stated Eddie Sorrells, CPP, PSP, PCI, 2026 President, ASIS International. “This year's keynote speakers, a pioneer in exponential technology, a leader in AI and decision science, and a true embodiment of resilience, were chosen to do exactly that. To challenge, inspire, and equip our global community for what lies ahead." Rapid technological change Monday, 14 September - Peter Diamandis, MD | Founder and Executive Chairman, XPRIZE Foundation and Executive Founder and Director, Singularity University. Peter Diamandis is a visionary entrepreneur and futurist who has spent his career pushing the boundaries of what's possible through exponential technologies and moonshot thinking. As founder of the XPRIZE Foundation and co-founder of Singularity University, Diamandis has inspired global innovation in fields ranging from space exploration to healthcare. A New York Times bestselling author of four books, Diamandis helps leaders understand how rapid technological change creates both disruption and opportunity. In his GSX keynote, Diamandis will explore how exponential thinking and emerging technologies are reshaping security challenges and creating new possibilities for protection, resilience, and organisational transformation. Sponsored by Allied Universal. Avoiding common pitfalls Tuesday, 15 September - Cassie Kozyrkov | CEO, Kozyr; Fmr. Chief Decision Scientist, Google. Cassie Kozyrkov is widely regarded as one of the most influential voices in making AI and data science accessible, practical, and strategically valuable. As Google's former Chief Decision Scientist, she has helped organisations around the world apply AI and machine learning to real-world challenges while avoiding common pitfalls. Known for her ability to demystify complex technical concepts, Kozyrkov bridges the gap between technical possibility and business reality. In her GSX keynote, she will provide security leaders with practical frameworks for leveraging AI and data-driven decision-making to enhance threat detection, risk assessment, and organisational resilience in an increasingly complex landscape. High-stakes decisions Wednesday, 16 September - Travis Mills | Retired U.S. Army Staff Sergeant and Quadruple Amputee. Retired U.S. Army Staff Sergeant Travis Mills is one of only five quadruple amputees to survive injuries sustained from the wars in Iraq and Afghanistan. After being wounded by an IED (improvised explosive device) in Afghanistan in 2012, Mills embarked on a journey of recovery that exemplifies extraordinary resilience, determination, and leadership. He founded the Travis Mills Foundation, which provides critical support to injured veterans and their families, and has become a sought-after speaker on overcoming adversity, mental toughness, and never giving up. In his GSX keynote, Mills will share powerful lessons on resilience, adaptability, and leading in the face of extreme adversity—insights that resonate deeply with security professionals who face high-stakes decisions and complex crises.

Across many sectors, AI is transitioning from an experimental process to a trusted tool, but how will construction - and architectural ironmongery specifically - balance this technological opportunity with traditional practice? Artificial intelligence was once considered the trend of tomorrow, but it’s now here, and already it’s impacting the design, specification and management of the built environment. Following a period of refined development, the technology is emerging as a valuable tool for architectural professionals, with its growing role signifying far more than a passing industry trend. Passing industry trend According to the Royal Institute of British Architects’ (RIBA) Artificial Intelligence Report 2025, 59% of architectural practices now use AI on at least some projects, an increase from 41% in 2024. Furthermore, a global survey led by the Royal Institution of Chartered Surveyors in 2025 found that 56% of investors planned to increase AI investment, suggesting that the rate of adoption will continue to accelerate over the coming years. However, whilst innovation typically creates opportunity, there are challenges to address These findings represent a cultural shift, one where AI is firmly embedding itself into workflows and influencing the decision making process. However, whilst innovation typically creates opportunity, there are challenges to address. As more professionals equip themselves with an arsenal of AI-driven tools, are we in danger of becoming overly reliant on technology? Or are those reluctant to adapt likely to be left behind? Daniel May, Director at Consort Architectural Hardware, shares insight: Repetitive administration tasks “The development of the built environment has always relied on technical precision. Specifications naturally contain large volumes of product information and technical data, with professionals managing document-heavy tasks in the form of specification writing, door scheduling and BIM coordination in order to meet project requirements and compliance obligations. All of this data must be analysed and processed accurately - often in line with demanding timescales - and it is here where AI can offer the greatest value.” “Where time was once consumed by repetitive administration tasks and information processing, professionals are now embracing AI as a means of working more efficiently. For architectural ironmongery specifically, where specification accuracy is critical, AI has the potential to support architects and specification professionals as they navigate the product selection process. As a tool, AI can streamline documentation by rapidly processing performance data and certification requirements, whilst also identifying inconsistencies and absent compliance information within schedules.” Complex project requirements “AI systems are helping professionals navigate increasingly complex project requirements quickly, accurately and consistently. As machine learning and autonomous models continue to advance, these tools may further reduce the administrative burden associated with architectural work models whilst improving accuracy and minimising the risk of human error in the process. With that said, the effectiveness of AI software is very much reliant on the quality of the information it receives.” “With the sector so deeply tied to fire safety, accessibility, security and regulatory standards, the caution around adopting AI as common practice is of course justified. Historically, much of the construction industry has been measured in its adoption of new technology, partly due to the critical nature of compliance and the significant consequences of error. Though, AI feels somewhat different because of its pace and potential, and as such, organisations must be measured in their approach to it, ensuring that professional knowledge remains central to delivering safe, efficient and compliant building projects.” The human element As industry standards and the legislation surrounding the built environment continues to evolve, so too will the methods used to achieve high level design and compliance. Seemingly, AI looks set to have an increasingly prominent role, but it should be viewed as a collaborative partner capable of enhancing professional expertise as opposed to a system that can, or should, do it all. Daniel continues: “At this stage, AI alone simply can’t understand the nuances of individual projects and that has implications for both design and compliance. This is particularly relevant in the post-Grenfell regulatory landscape, where accountability, traceability and evidence-based decision-making have become fundamental to product specification and delivery.” Building greater trust “Although AI can assist with information processing, the technology is not ultimately responsible for the decisions being made. Accountability has rightly become a major focus point in construction, and as AI continues to disrupt practices, the industry must ensure that responsibility remains clearly defined. AI-driven errors could lead to serious penalties in relation to compliance, safety and project delivery, proving human expertise remains critical.” “Moving forward, greater transparency within AI systems will be key. If professionals are able to understand how or why AI recommendations have been generated, they can assess them with confidence, building greater trust in the technology.” Architectural design solutions “When it comes to architectural design, the emotional intelligence, contextual understanding and creative balance offered by a team of professionals far outweighs the speed that AI can offer. Already, AI is being used to support visualisation and concept development for multi-layered projects in hospitality, healthcare and commercial environments to name a few, helping teams to explore ideas and communicate concepts at a quicker rate.” “However, can AI effectively develop architectural design solutions based on the bespoke requirements of a project, the operational needs of its users or even the general character of the building? Most would argue that it’s not conceivable, because AI lacks the lived experience and contextual understanding that comes from being present in the project itself.” Architectural ironmongery products “For architectural ironmongery products, professionals must regularly assess how products will function in real environments. Human intuition is impossible to replace and those informed design decisions, made by human professionals, will always be essential. Whilst some question whether AI could one day plan and deliver a project from concept to completion, perhaps the more important question should be whether future generations of professionals could lose the critical design and specification skills that are needed, should the industry become too dependent on AI.” “There is a growing sense of inevitability surrounding AI’s influence on architectural ironmongery and the wider built environment. As the industry continues to embrace this new wave of technological development, it is important to remember that innovation must complement the knowledge, judgement and accountability of the professionals who create safe and functional buildings, not replace it.”

In the ever-evolving struggle between cyber offence and defence, attackers have almost always moved first. In the emerging domain of artificial intelligence, this pattern appears to be repeating itself. Yet, global cybersecurity pioneers appear disconcertingly disengaged. Just over half even agree that AI-driven attacks are set to become dramatically more complex and widespread. Equally concerning is the widespread apathy regarding AI’s role in expanding an already sprawling corporate attack surface. This is no small oversight. A recent global Trend Micro study showed that 73 percent of organisations have already suffered cybersecurity incidents due to unknown or unmanaged assets. In an era where digital blind spots are both common and consequential, hesitation is a risk few can afford. Security has to shift from reactive protection to proactive risk exposure management. The opportunity and the risk of AI Threat actors are now using jailbroken versions of legitimate generative AI tools such as ChatGPT The potential for AI to transform enterprise operations is enormous, but so is the risk. The warnings have been loud and clear. As early as the first quarter of 2024, the UK’s National Cyber Security Centre (NCSC) stated that AI would “almost certainly increase the volume and heighten the impact of cyber-attacks over the next two years.” Their prediction is proving accurate. Threat actors are now using jailbroken versions of legitimate generative AI tools such as ChatGPT, freely traded as services on the dark web, as well as malicious models like FraudGPT, built on open-source large language models (LLMs). These tools are no longer just about automating tasks; they are turbocharging the entire attack lifecycle. From more convincing phishing emails and precise target selection, to sophisticated malware creation and lateral movement within breached systems, AI is driving a step-change in threat actor capability. Integrating open-source models However, this is only one side of the coin. The other, often overlooked, is AI’s impact on the corporate attack surface. Even well-meaning employees can unintentionally expand organisational risk. The widespread use of AI-as-a-service tools like ChatGPT introduces significant shadow IT concerns, especially when sensitive business information is input without proper oversight. Data processing and storage practices for many of these services remain opaque, raising additional compliance concerns under regulations like the UK GDPR and the EU’s AI Act. For those organisations that choose to build or customise their own LLMs, the risks multiply. Integrating open-source models may expose businesses to vulnerabilities, misconfigurations and flawed dependencies. Each new tool and environment adds to the complexity of an attack surface already strained by remote work setups, sprawling cloud deployments, IoT ecosystems, and accelerating digital transformation programmes. Managing the expanding risk landscape Many have already shared security incidents where a lack of asset visibility was the root cause Many security pioneers do understand what is at stake. Nine in ten agree that effective attack surface management is tied directly to business risk. They cite a long list of potential consequences, disruptions to operations, reputational damage, declining competitiveness, strained supplier relationships, financial losses and reduced staff productivity. Many have already experienced security incidents where a lack of asset visibility was the root cause. Despite this recognition, however, the response remains largely inadequate. Fewer than half of global organisations use dedicated tools to monitor their attack surface proactively. On average, only a quarter of cybersecurity budgets are allocated to managing cyber risk exposure. Third-party risk management is similarly neglected: fewer than half of firms actively monitor their vendors for vulnerabilities. This inertia creates an obvious contradiction. Security pioneers understand the business implications of unmanaged risk, but they are not equipping themselves with the tools or processes to respond. That needs to change—and fast. How AI can help defenders take the lead There is good news: AI is not only a weapon for cybercriminals. It can also be a powerful ally for defenders, particularly in the field of Cyber Risk Exposure Management (CREM). The best tools in this category use AI to continuously scan an organisation’s entire digital footprint. They can automatically detect vulnerabilities, spot misconfigurations, identify rogue or shadow assets, and provide prioritised remediation recommendations. CREM platforms apply contextual filtering to reduce false positives and elevate the most urgent threats Intelligent algorithms can also analyse network behaviour to identify anomalies that could signal a breach in progress. Unlike traditional tools, which often drown analysts in noise, CREM platforms apply contextual filtering to reduce false positives and elevate the most urgent threats. For overburdened security teams, this enables a far more focused and effective response. However, the keyword here is “continuous.” The nature of today’s IT environments, especially in the cloud, is dynamic and fast-moving. Assets appear and disappear within minutes. Static, point-in-time assessments are no longer sufficient. Yet more than half of organisations still lack continuous scanning processes. This leaves them exposed to risks that might persist undetected for weeks or months. Overcoming barriers to adoption So what is holding organisations back? In many cases, it’s not the technology itself but the internal politics of investment. Security pioneers interested in CREM tools often prioritise real-time alerting, clear dashboards, and seamless integration with their existing environments. All of this is now achievable. The challenge lies in securing board-level support. Many security teams still work in silos, disconnected from the broader business Boards are often cautious when it comes to cybersecurity investment, particularly when immediate ROI is not clear. To gain their trust, security pioneers must learn to speak the language of business risk, not technical threat. They must frame cyber exposure in terms of reputational impact, regulatory liability, operational continuity, and investor confidence. There is also a cultural component. Many security teams still work in silos, disconnected from the broader business. This limits their influence and makes it harder to embed security as a strategic enabler. In the AI era, this divide must be bridged. Cybersecurity must become a board-level concern, and risk exposure must be treated as a fundamental operational issue. Time to act We are at a critical inflection point. The AI revolution is not on the horizon, it is already here. Threat actors are moving rapidly to exploit it, leveraging tools and techniques that were unthinkable just a few years ago. Meanwhile, organisations remain slow to respond. Too few are investing in the tools, processes, and people needed to manage their risk exposure effectively. AI can be used not only to attack but to defend. CREM tools powered by AI offer a powerful way to regain visibility, restore control, and build lasting resilience. They enable proactive rather than reactive security. And they help organisations align their cybersecurity strategy with their broader business objectives. Security teams have to elevate the conversation. They must advocate not just for new tools, but for a new mindset, one that treats cyber risk as an enterprise risk, and one that prioritises continuous visibility as a prerequisite for resilience.

Artificial Intelligence isn’t just a buzzword anymore. It has become part of our lives, and its uses and applications are growing every other day. Even the public sector, which usually is a late adopter of new technologies, has come onboard this new train. Law enforcement, in particular, has seen the advantages different AI technologies can offer to their work and has started to integrate them into their workflow and daily routines. But there is much more to come. Task automation: AI as a workhorse Due to the increasing importance of media files in police investigations, current police cases have an increasing amount of digital files to be analysed. Videos from mobile phones, computer files, sound recordings, voice messages from chat applications…the list is almost endless. But, in contrast to other types of digital files, like documents or PDFs, it is not possible to search directly a certain information in a video. It has to be watched by someone. And that takes an inordinate amount of time for a human being, as there can be hundreds of videos in a case. This is one of the areas where artificial intelligence shines. Modern analytics systems are able to find almost any kind of information in media files due to the improvement of artificial vision, object recognition and face biometrics. It is simply a matter of feeding the hundreds or thousands of media files to a AI analyser, which will work through them and find specific sounds, words, faces, cars, etc. Case of law enforcement On top of that, an analyser does not tire after long work hours and does not make errors What is more, unlike human officers, these systems can work 24/7 which speeds up investigations considerably, as more evidence is found in less time. On top of that, an analyser does not tire after long work hours and does not make errors. This is why police work can be helped greatly by AI Analytics, as it frees police officers to do high value work, instead of endlessly watching videos on a computer of listening to audio recordings, in search of evidence. As soon as the system finds what the officer has specified (a face, name, number plate, object, etc.) it sends an alarm to the officers’ phone, so he or she can take a look and decide what to do with that information. Despite AI being touted as a danger to many workplaces, in the case of law enforcement, it is a valuable tool to help police do more, with more accuracy, and in less time, freeing officers from the repetitive and boring work of checking mountains of evidence in search of clues. The AI Analyser landscape The field of AI analytics is expanding constantly and new types of analysis are being discovered that may be helpful to police or intelligence. The most used analysers today are probably Automatic Licence Plate Recognition (ALPR), object and face recognition. But OCR is equally useful not just for reading documents, but also signs and logos that may appear in pictures or videos, to help identify a location. And for audio (as in interception or surveillance recordings) there is speech-to-text (S2T), translation, Speaker ID, audio fingerprinting (AFP) and natural language processing (NLP) which is able to extract sentiment from what is said. All of these have their application in daily police work and can save time in investigations or make them possible in the first place. But looming on the horizon are new possibilities, which we will discuss later and that are even more powerful. So the field of AI Analytics is, by no means, a closed one. Generative AI in law enforcement LLMs will be an important part in all those tasks related to investigate large sets of documents For the past year, the term “Generative AI” has become part of our general vocabulary, although most of the time we just say ChatGTP, Copilot o similar. The large language models (LLM) use Deep Learning and different AI strategies to, amongst other things, analyse and summarise vast amounts of information, in order to generate a short report with the highlights. This can be of use for Law Enforcement in all those cases that have great amounts of documents that may contain evidence. Again, this is a case like the above, where AI helps speed up operations by doing the grunt work much quicker than any person could.  The difference is in the Deep Learning part. The model can be tuned to specific needs (like financial crimes, for example) and will get better over time when dealing with specific sets of documents. Thus, LLMs will be an important part in all those tasks related to investigate large sets of documents during a case. What the future holds As with all technology, it is virtually impossible to predict what the future will hold. Because any breakthrough can upend complete sectors, as demonstrated by ChatGPT not that long ago. However, there are several promising AI technologies in the pipeline, some of which are already being tested and perfect around the world: Behaviour analysis: as facial recognition systems get better and better, they are not only able to recognise faces, but also facial expressions. This means that AI systems could be assisting during interrogations, to evaluate the truthfulness of what is being said. Combined with the analysis of small voice inflections, they can be a non-invasive “lie detector”. Robotics: already in use by many police forces around the world, robots are going to be ever so important. Particularly the autonomous kind, which is able to do missions on its own, without a human behind the controls. This, combined with swarm technology, could be an incredible help in disaster areas, where time is of the essence in locating victims. Predictive policing: thanks to pattern analysis, predictive policing, which has been to the test several times already, will be an important part of police work, to figure out where to send units or concentrate surveillance efforts. In short, AI has much more to offer, and we are going to see and incredible evolution of this technology applied to law enforcement, over the next years.

Anyone who has been in a proverbial cave for the last couple of years faced a language barrier at this year’s ISC West 2025 trade show. The industry’s latest wave of innovation has brought with it a new bounty of jargon and buzzwords, some of which I heard at ISC West for the first time. As a public service, we are happy to provide the following partial glossary to promote better understanding of the newer terms. (Some are new to the security industry but have been around in the IT world for years.) Obviously, if we can’t understand the meaning of the industry’s lexicon (and agree on the meaning of terms!), we will struggle to embrace the full benefits of the latest industry innovation. Not to mention, we will struggle to communicate. Generative AI Generative AI can identify an object in an image based on its understanding of previous objects This was perhaps the most common new(ish) term I heard bouncing around at ISC West. While the term artificial intelligence (AI) now rolls off everyone’s tongue, the generative “version” of the term is catching up. Generative AI uses what it has learned to create something new. The name comes from the core function of this type of artificial intelligence: it can generate (or create) new content. It doesn’t just copy and paste; it understands the underlying patterns and creates something original based on that understanding. In the case of video, for example, generative AI can identify an object in an image based on its understanding of previous objects it has seen. Video and security Generative AI can tell you something digitally about what is happening in an environment. There is no longer a need to write “rules;” the system can take in data, contextualise it, and understand it, even if it does not exactly match something it has seen before. In the case of video and security, generative AI offers more flexibility and better understanding. From 2014 to 2024, the emphasis was on detecting and classifying things; today AI is expanding to allow new ways to handle data, not so prescriptive and no more rules engines. Agentic AI Agentic AI refers to artificial intelligence systems that can operate autonomously to achieve specific goals Agentic AI refers to artificial intelligence systems that can operate autonomously to achieve specific goals, with minimal to no direct human intervention. In addition to the capabilities of generative AI, agentic AI can take action based on what it detects and understands. Use of agentic AI typically revolves around an if/then scenario. That is, if action A occurs, then the system should proceed with action B. For example, if an AI system “sees” a fire, then it will shut down that part of the building automatically without a human having to initiate the shutdown. There is a lot of discussion in the industry about the need to keep humans involved in the decision-making loop, so the use of truly autonomous systems will likely be limited in the foreseeable future. However, the ability of agentic AI to act on critical information in a timely manner, in effect to serve as an “agent” in place of a human decision-maker, will find its place in physical security as we move forward. Inference Inference is another common term related to AI. It refers to the process by which an AI model uses the knowledge it gained during its training phase to make predictions, classifications, or generate outputs on new, unseen data. The direct relationship of this term to physical security and video is obvious. In the simplest terms, an AI system is “trained” by learning patterns, relationships, and features from a large dataset. During inference, the trained model is presented with new questions (data it hasn't seen before), and it applies what it learned during training to provide answers or make decisions. Simply put, inference is what makes AI systems intelligent. Containerisation Dividing a massive security management system into several separate containers enables management of the various parts In IT, containerisation is a form of operating system-level virtualisation that allows you to package an application and all its dependencies (libraries, binaries, configuration files) into a single, portable image called a container. This container can then be run consistently across any infrastructure that supports containerisation, such as a developer's laptop, a testing environment, or a server in the cloud. In the physical security industry, you hear “containerisation” used in the context of separating out the various components of a larger system. Dividing a massive security management system into several independent containers enables the various parts to be managed, updated, and enhanced without impacting the larger whole. Genetec’s SecurityCentre cloud platform Think of it like shipping containers in the real world. Each container holds everything an application needs to run, isolated from other applications and from the underlying system. This ensures that the application will work the same way regardless of the environment it is deployed in.   “It took us five years to containerise Genetec’s SecurityCentre cloud platform, but containerisation now simplifies delivering updates to products whenever we want,” says Andrew Elvish, Genetec’s VP Marketing. Among other benefits, containerisation enables Genetec to provide more frequent updates--every 12 days. Headless appliance Headless appliance is a device that is managed and controlled remotely through a network or web interface A headless appliance is a device that is managed and controlled remotely through a network or web interface. The device is like a “body without a head” in the traditional sense of computer interaction: It performs its intended function, but without any visual output or input device for local interaction. In physical security, such devices are increasingly part of cloud-based systems in which the centralised software manages and operates all the disparate “headless” devices. A headless appliance does not have a Windows management system. “The whole thing is managed through the as-a-service cloud system,” says Elvish. With a headless device, you just plug it into the network, and it is managed by your system. You manage the Linux-based device remotely, so configuring and deploying it is easy. Democratising AI You hear the term democratising AI used by camera manufacturers who are looking to expand AI capabilities throughout their camera lines, including value-priced models. For example, even i-PRO’s value-priced cameras (U series) now have AI – fulfilling their promise to democratise AI. Another approach is to connect non-AI-equipped cameras to the network by way of an AI-equipped camera, a process known as “AI-relay.” For instance, i-PRO can incorporate non-AI cameras into a system by routing/connecting them through an X-series camera to provide AI functionality. Bosch is also embracing AI throughout its video camera line and enabling customers to choose application-specific analytics for each use case, in effect, tailoring each camera to the application, and providing AI to everyone. Context Cloud system also enables users to ask open-ended queries that involve context, in addition to detection Context refers to an AI system that can understand the “why” of a situation. For example, if someone stops in an area and triggers a video “loitering” analytic, the event might trigger an alarm involving an operator. However, if an AI system can provide “context” (e.g., he stopped to tie his shoe), then the event can be easily dismissed by the automated system without involving an operator. Bosch’s IVA-Pro Context product is a service-based model that adds context to edge detection. The cloud system also enables users to ask open-ended questions that involve context in addition to detection. For example, rather than asking "do you see a gas can?" you can ask "do you see any safety hazards in this scene?" The pre-trained model understands most common objects, and understands correlations, such as "a gas can could be a safety hazard.” A scaled-down on-premise version of the IVA Context product will be available in 2026. Bosch showed a prototype at ISC West. Most video data is never viewed by an operator. Context allows a system to look at all the video with "almost human eyes." Cameras are essentially watching themselves, and understanding why something happened and what we can do. All that previously unwatched video is now being watched by the system itself, boosted by the ability to add “context” to the system. Any meaningful information based on context can trigger a response by an operator. Data lake A data lake is a centralised repository that allows one to store vast amounts of structured, semi-structured, and unstructured data in its native format. In the case of the physical security marketplace, a data lake includes data generated by systems outside the physical security infrastructure, from inventory and logistics systems, for example. A data lake is where an enterprise can accumulate all their data, from the weather to Point-of-Sale information to logistics, to whatever they can gather. Putting the data in one place (a “data lake”) enables them to mine that data and parse it in different ways using AI to provide information and insights into their business. Notably, a data lake contains all a company’s data, not just security or video data, which opens up new opportunities to leverage the value of data beyond security and safety applications. Crunching the various information in a data lake, therefore, security technology can be used to maximise business operations.

With the year 2025 stretched out before us, there are many techniques one could use to predict what will happen in the new year. You might analyse historical data and analyse future trends. Or you could try statistical or economic modelling. Or you could develop multiple scenarios based on various assumptions to explore potential outcomes. Or you could just check your email. At this time of year, my email is full of industry folks looking to predict what the future holds in 2025. Ranging from artificial intelligence (AI) to privacy, the retail market to drones, here is a sampling of forecasts for 2025 provided by various players in the security market, courtesy of my email messages. What’s Ahead for AI? From Faisal Pandit, VP & GM, Global Security Products, Johnson Controls (JCI): “The future of security operations includes customisable, scalable solutions where users can control if, when, and how they use AI to improve efficiency depending on the size and function of their organisation.” Says Kevin Woodworth, Vice President, Global Product Management, Intrusion, JCI: “Next year will see a growing focus from product developers on designing systems that streamline setup and configuration through increased AI integration. This reflects a broader trend of leveraging AI to simplify use and enhance adaptability as solutions evolve, rather simply employing it because it’s popular.” From Peter Evans, CEO of Xtract One Technologies: “AI algorithms will significantly advance in distinguishing between harmless, everyday items and potential threats. With this, we will see false alerts become even more rare.” Says JP Castellanos, Director of Threat Intelligence, Binary Defense: “Machine learning (ML)-powered anomaly detection will move beyond proof-of-concept to become mission-critical, enabling teams to uncover unknown threats and behavioural anomalies in real time – well before they escalate.” Evans of Xtract: “As AI becomes more advanced in threat detection, it will lead to more sophisticated protection of individual privacy. We can expect to see more AI techniques utilised for threat identification that do not capture personal data and are privacy-first.” Predictions on interoperability and compliance Woodworth of JCI: “New products added to singular systems must be interoperable. In 2025, organisations will need to embrace interoperability. AI will progress past reactive measures to achieve predictive capabilities.” Pandit of JCI: “With organisations increasing their focus on the regulatory environment, there will be an uptick in specialised certification programs to meet these needs. New security roles will emerge that will be focused on tracking and applying relevant regulatory changes.” Expanding capabilities for video cameras Woodworth of JCI: “Beyond capturing images, cameras will be able to detect potential threats and also mitigate them instantly, issuing vocal warnings, controlling access, or escalating issues without human intervention.” Looking ahead to retail developments Hansel Oh, Director of Product Marketing at Brivo: “Centralized, cloud-based security platforms will enhance credential management and monitor logistical operations to enable retailers to battle cargo theft.” Stephen Burd, Vice President, Essence Security: “With an increase in police response times, sophisticated crime, and smash and grabs, 2025 will see a huge demand for security solutions that go beyond simply notifying the police and will look to actively intervene and prevent damage or loss from occurring.” The role of drones and training Mary-Lou Smulders, CMO, Dedrone by Axon: “Drones will transition from being viewed as supplementary tools to becoming essential components of public safety operations. As departments recognise their effectiveness in various scenarios, the perception of drones will shift, and they will be integrated into core operational frameworks alongside traditional assets like patrol cars while replacing helicopters as a cost-effective and versatile alternative.” Erik Hohengasser, Electrical Technical Lead at NFPA: “As the skilled trades evolve, there will be an increasing demand for specialised and technical training. Predictive analytics, virtual simulations and hands-on experiential learning will become especially valuable due to allowing employees to gain real-world expertise in safe and controlled environments.”

Security applications for drones have evolved to provide benefits such as bird's-eye views of large areas, easy access to remote locations, and rapid deployment. However, to date, most drone applications have been outdoors. Not for long. Today, indoor drones are also finding unique opportunities for enhanced surveillance, security, and operational efficiency in indoor environments such as offices, warehouses, self-storage facilities, and malls. Indoor drones can navigate complex indoor spaces, providing real-time data and monitoring without the limitations of fixed cameras. New era of autonomous robotics A significant advantage of using drones indoors, as opposed to outdoors, is their ability to operate fully autonomously, circumventing U.S. Federal Aviation Administration (FAA) regulations that restrict such autonomy in outdoor environments. A new era of autonomous robotics enables drones to work seamlessly for users without the need for specialised flight training. A single security manager can oversee multiple indoor drones simultaneously with simple map clicks or prompts. A new era of autonomous robotics enables drones to work seamlessly for users Indoor monitoring and inspection Indoor Robotics is a company seeking to revolutionise indoor monitoring and inspection through its Control Bridge platform guiding indoor drones. Since its founding in 2018, Indoor Robotics has evolved through years of market engagement and product development. After initially recognising a demand for autonomous indoor monitoring, the company found that existing hardware fell short. “However, we understood the challenges of full autonomy and knew we would solve it using drones,” says Bar Biton, Marketing Manager of Indoor Robotics. Indoor Robotics has evolved through years of market engagement and product development Hardware challenges  Seven years later, with the hardware challenges addressed, the company is shifting focus to continually increasing value for security managers, especially with generative AI (artificial intelligence). In 2018, the problem was charging methods, which has been solved with ceiling docking stations and five patents. “Today it’s about making indoor environments safer and even saving lives by identifying blocked emergency exits, missing safety gear, leaks, fire hazards and more,” says Biton. While indoor navigation presents challenges—such as the unreliability of GPS and the need for precision — Indoor Robotics has dedicated significant resources to achieve centimeter-level accuracy and ensure the utmost safety, maintaining a record of zero safety incidents to date, says Biton. Indoor navigation presents challenges—such as the unreliability of GPS and the need for precision Advanced AI-driven navigation systems Navigation challenges for indoor drones include manoeuvering through confined spaces, avoiding obstacles, and maintaining stable flight in varied lighting conditions. To address these, Indoor Robotics employs advanced AI-driven navigation systems, real-time 3D mapping, and robust obstacle avoidance technologies. These solutions enable drones to adapt to dynamic environments, ensuring precise and safe navigation. Additionally, the Control Bridge platform provides real-time data and monitoring, allowing drones to adjust their routes and respond to changing conditions effectively, thus enhancing their operational reliability. Highly versatile indoor drones find applications across numerous vertical markets such as retail, logistics, healthcare, and corporate settings. Key use cases encompass security surveillance, where drones monitor premises continuously; maintenance checks, especially in hard-to-reach areas; safety inspections to comply with regulations and company policies; and emergency response to provide real-time data during incidents. In warehouses, drones efficiently inspect high shelves. Healthcare facilities and data centres use them to oversee restricted zones. Additionally, corporate offices employ drones to automate after-hours security, safety and maintenance routines. Indoor Robotics employs advanced AI-driven navigation systems, real-time 3D mapping, and robust obstacle-avoidance technologies Alerts to the remote management team One Indoor Robotics client, a global tech company, deploys drones to enhance site surveillance and operational efficiency across six offices in three countries. The drones conduct regular security patrols after-hours, monitor facility activities, and ensure compliance with safety standards. This deployment has significantly improved the overall safety and security of their offices. The drones provide real-time alerts to the remote management team, enabling prompt responses to any anomalies, such as maintenance issues or unauthorised access. “The key advantage is the unified security standard provided by our Control Bridge operating system, allowing them to oversee all their sites from one centralised platform, ensuring consistent security management across all locations,” says Biton. When indoor drones co-exist with human workers, primary challenges include ensuring safety and preventing disruptions. Drones are equipped with advanced sensors and AI-driven obstacle avoidance systems to detect and navigate effectively around people. Strict operational protocols and designated flight paths are implemented to minimise interactions. Additionally, many drone operations are scheduled for after-hours to further reduce potential disruptions. “Safety is our top priority, and we invest significant resources to ensure it,” says Biton. “We are proud to report zero safety issues to date, reflecting our commitment to maintaining a secure environment for both drones and human workers.” Deploys drones to enhance site surveillance and operational efficiency across six offices in three countries Implementation of indoor drones Indoor drones are significantly more cost-effective and affordable when compared to traditional security methods like additional cameras, sensors, manpower, and even ground robots, says Biton. They cover larger areas and provide dynamic surveillance in less time, offering real-time data collection and enhanced flexibility. Unlike cameras or ground robots, drones eliminate blind spots and adapt to environmental changes autonomously. They also offer substantial indirect savings by optimising maintenance routines, according to Indoor Robotics. For instance, a drone can instantly identify issues in hard-to-reach areas, allowing for immediate, targeted responses, instead of requiring an inspector first and then a technician, thus streamlining maintenance processes. “The biggest obstacle to greater implementation of indoor drones is education and awareness,” says Biton. “Many people are not yet exposed to the concept of autonomous indoor drones and may find it hard to believe they really work.” To overcome this, Indoor Robotics focuses on creating awareness and educating customers about the reliability and benefits of the technology. Demonstrations, case studies, and clear communication about the capabilities and safety of drones are key. By showcasing successful implementations and providing hands-on experiences, Indoor Robotics seeks to build trust and drive wider adoption of indoor drone technology in security applications. Control Bridge operating system Drones are designed with strict privacy controls and advanced AI to ensure they respect privacy norms A common misconception is that indoor drones are intrusive and pose significant privacy risks. However, drones are designed with strict privacy controls and advanced AI to ensure they respect privacy norms. They operate primarily during off-hours and are programmed to avoid sensitive areas, focusing solely on enhancing security and operational efficiency. The solution also includes rigorous data protection measures to safeguard any collected information, ensuring compliance with privacy regulations and addressing concerns effectively. Soon, automation will become integral to tasks across all facility types, from manufacturing and logistics to retail and office spaces. Using Indoor Robotics’ Control Bridge operating system, facility managers will deploy fleets of robots to identify issues, collect data, and gain insights to enhance operations, maintenance, and safety. Facilities will benefit from 24/7 AI-driven monitoring, eliminating the need for occasional surveys. Managers will receive immediate alerts for any anomalies, with preventive maintenance tasks seamlessly integrated into building management platforms, ensuring optimal performance and safety. New standards in the industry  The Indoor Robotics platform-agnostic approach provides flexibility and scalability. “As we continue to evolve, we support more and more platforms, enabling our clients to tailor their indoor monitoring solutions to their specific needs,” says Biton. “We believe that the future of security lies in intelligent, automated systems that can adapt to dynamic environments and provide real-time insights,” says Biton. Indoor Robotics seeks to be at the forefront of this transformation, setting new standards in the industry and paving the way for a safer, more efficient future.

The client, a large telecommunications provider, had teams working across multiple time zones and operated a sprawling and complex IT system. The scale and density of this system made gaining visibility into IT services extremely difficult, leaving the security team blind to what was happening with its IT environment. With little-to-no operations monitoring tools in place to proactively monitor these systems, the team had no visibility on the availability of its IT services or KPIs, such as failure rates, send request times, and response times. This lack of oversight made it difficult for the team to prioritise issues — and nearly impossible for them to find the root cause of any problem. Proactive measures Without the ability to investigate the source of issues, the team was unable to take proactive measures to prevent them from reoccurring, severely impacting service performance. This was not only a problem for IT teams, but also for executives, who lacked the insight into IT business operations that would help them make decisions. The solution The company needed a solution that would map KPIs to critical service components, enabling the operations team to effectively drill down into issues in real time and conduct in-depth investigations to find resolutions. RiverSafe had previously implemented Splunk Enterprise Security for the customer and given the success of the implementation and the positive client feedback on the platform, RiverSafe was again engaged to deploy Splunk’s IT Service Intelligence (ITSI) tool to help it tackle its visibility problem. Data collection metrics Splunk ITSI uses machine learning to analyse existing data and predict future issues. As well as forecasting potential services bottlenecks, it can also troubleshoot problems and help users resolve issues fast. Delivering comprehensive monitoring across the entire IT environment, Splunk ITSI would also give the team full observability of their IT infrastructure. In particular, the engineering team wanted to gather metric data relating to the Kubernetes platform. RiverSafe reconfigured and implemented data collection metrics used elsewhere in the IT environment in Splunk to allow engineers to collate and access this information from different data sources in one place. The outcome: Actionable insights in days, not weeks In less than a week, the RiverSafe team implemented Splunk ITSI and began running monitoring services. With data from existing KPIs already indexed by the Splunk platform, the team are now able to access service insights even faster. These KPIs allow the operations team to identify trends, detect patterns, and proactively address any anomalies that occur before issues arise. Instant visibility with glass table visualisations To enable rapid and proactive issue resolution, RiverSafe implemented custom glass table visualisations in Splunk ITSI. This enables the team to navigate large volumes of data and reduce the time needed to identify and resolve problems. This simple and accessible dashboard gives the team an instant, digestible overview of its web portal performance metrics. These KPIs included the number of open tickets and failed login attempts, memory usage, API call success rates, average response times, and overall health of container services. Event analytics in Splunk ITSI As a result of RiverSafe’s work, the team has been able to centralise events from all its previously siloed solutions into a single interface with Splunk ITSI. The event analytics in Splunk ITSI help to prioritise responses and react more quickly to customers’ infrastructure events, empowering them to provide a better service. This is thanks in part to Splunk ITSI’s ability to identify and filter out false positives from the event management process. Excluding these invalid events reduced the total event volume by 40%, helping operators focus on the events that really matter. With fewer events to process, a single interface to work from, and a streamlined event analytics framework in Splunk ITSI, operators now process events eight minutes faster on average. This boost in efficiency has led to a major improvement in the company’s SLA performance. Best practices for using Splunk ITSI Overall, Splunk ITSI has delivered enhanced operational visibility, meaning the team can locate bottlenecks in workflows quickly and deliver fast recovery and troubleshooting solutions. Along the way, RiverSafe also provided best practices for using Splunk ITSI and recommended the most effective ways to collect data, including proposing an alternative metric type that would save on storage space when collecting logs.

With an extensive network of customers spanning the globe, cybersecurity is a primary concern for our client. Protecting extensive infrastructure and customer data requires a robust cybersecurity posture and effective tools, but the team found its SIEM solution lacking. Flooding its security team with an unmanageable number of false positives, the solution was diverting attention away from genuine threats and leaving them vulnerable. A substandard SIEM solution was not the only security issue. With no UEBA platform in place to help detect insider threats and data breaches, the company was faced with a number of gaps and weak spots in its security infrastructure that needed to be addressed. Three key issues The biggest concerns centred around three key issues: A lack of insider threat detection: Without a UEBA solution, the company had difficulty identifying insider threats and anomalous user behaviour within the network. Time spent on manual investigation: Security analysts spent significant amounts of time manually correlating events and investigating incidents, leading to delays in incident response and inefficient use of resources. Alert fatigue: The company’s existing SIEM solution generated a high volume of alerts, making it challenging for analysts to identify genuine threats among the many false positives. The solution The company engaged with RiverSafe to create a bespoke implementation plan that would address its primary issues and properly secure its digital infrastructure. Working in collaboration with the in-house security team, RiverSafe got to grips with existing infrastructure, gathered requirements and outlined the desired outcomes of the project. With all challenges and end goals collated, the RiverSafe team developed a solution that would meet all requirements and eliminate current security weaknesses. The team suggested Exabeam’s Fusion SIEM platform as it addressed the key concerns: Incident management: Delivering streamlined incident management processes by automating the correlation and enrichment of security events, Fusion SIEM equips analysts with actionable insights and real-time alerts. This improved visibility helps analysts hone in on genuine threats more quickly and reduce response times. Behaviour analytics: Tackling the company’s lack of UEBA issue, Exabeam’s advanced machine learning algorithms were configured to establish baseline behaviour for all users and systems. Any deviation from this baseline alerts analysts, enabling them to investigate anomalous activities and potential security issues, including insider threats. Data integration: The platform was integrated with various data sources, including logs from firewalls, servers, applications, and network devices to ensure comprehensive visibility across the organisation’s infrastructure. The outcome The implementation of Exabeam’s Fusion SIEM solution has yielded significant benefits, including: Enhanced threat detection: Exabeam’s behavioural analytics (AA) and machine learning (ML) capabilities have improved the accuracy of threat detection, enabling analysts to identify and respond to security incidents more effectively. Faster incident response: Exabeam’s automated incident enrichment and real-time alerts are helping the security team to respond to incidents promptly, minimising the impact of potential breaches. Reduced alert fatigue: The platform’s next-generation event analysis capabilities have reduced the number of false positives generated, reducing alert fatigue and giving analysts more time to focus on genuine threats. Improved insider threat detection: With its advanced behaviour analytics, Fusion SIEM is enabling the team to detect insider threats by identifying abnormal user activities and deviations from established behavioural patterns.

Honeywell has been selected as the building automation provider for LG Energy Solution’s cylindrical EV battery manufacturing facility being built in Queen Creek, near Phoenix, Arizona. Set for completion in 2026, this state-of-the-art project represents a critical milestone in LG Energy Solution’s strategy to lead EV battery innovation in North America, and it also supports Honeywell’s alignment of its portfolio to three compelling megatrends, including automation and the energy transition. New standard for operational efficiency Deployment of Honeywell’s building automation technologies at the Queen Creek facility Global battery demand is projected to quadruple by 2030 according to Bain, and the deployment of Honeywell’s building automation technologies at the Queen Creek facility will help set a new standard for operational efficiency in high-tech manufacturing environments. This 1.3-million-square-foot standalone facility will integrate a suite of Honeywell technologies to help optimise performance, enhance safety and support sustainability outcomes. Future of automation “By developing and delivering solutions that blend cutting-edge technology and energy management, we are driving the future of automation," said Billal Hammoud, president and CEO of Honeywell Building Automation. "Honeywell’s collaboration with LG Energy Solution demonstrates how advanced building automation can help empower companies to achieve operational excellence in their facilities while also accelerating the shift to a more secure energy future.” Honeywell’s innovative solutions Honeywell’s innovative solutions will provide the Queen Creek facility with the following: Unified Systems Integration: Honeywell’s Enterprise Buildings Integrator platform will help enable seamless control of building management and safety systems via integration into Honeywell Forge, which provides advanced monitoring and analytics. Honeywell Forge, an IoT platform, enables condition-based maintenance to improve the resiliency of critical systems around the clock, helping to reduce unplanned reactive work and help lower energy costs. Its machine learning capabilities will continuously study a building's energy consumption patterns, which will enable LG Energy Solution to automatically adjust the facility to optimal energy-saving settings. Comprehensive Fire and Safety Solutions: Honeywell’s VESDA smoke detection and advanced self-testing fire alarm system offers automated and continuous air sampling enabling early warning of an impending fire hazard, often even before heavy smoke or flames are detected. VESDA and the networked fire alarm solution will be integrated into the facility’s building management system to allow coordinated and near-instant responses from the HVAC system if smoke is detected. Mission Critical Control and Advanced Cybersecurity: The QronoX Programmable Logic Controller will enable LG Energy Solution to enhance operational performance and resilience by providing advanced cybersecurity for its facility. The Honeywell technology will also help ensure asset security and compliance while reducing downtime for critical systems. Honeywell’s scalable solutions are designed to support the future expansion of the project as well, reinforcing its role as a key collaborator in this transformative industrial sector.

Artificial Intelligence Technology Solutions, Inc., a pioneer in AI-driven security and productivity solutions for enterprise clients, along with its subsidiary Robotic Assistance Devices (RAD), announced recent successes in St. Louis, Missouri, where the Downtown St. Louis Community Improvement District (CID) has embraced RAD’s solutions as part of its public safety initiatives. The CID has deployed multiple ROSA™ security devices, showcased RAD’s ROAMEO™ and RADDOG™ LE2 during the NCAA Frozen Four Championship, and is actively developing a citywide program that would introduce hundreds of RADCam™ units across St. Louis. RAD’s added layer of security RAD’s ROAMEO and RADDOG LE2 were actively deployed in St. Louis as part of the city’s public safety From April 10 to 12, RAD’s ROAMEO and RADDOG LE2 were actively deployed in downtown St. Louis as part of the city’s public safety and engagement efforts during the NCAA Frozen Four Championship. These high-visibility units provided an added layer of security, engaged with residents and visitors, and generated strong public interest.  Steve Reinharz, CEO/CTO of AITX and RAD, was interviewed on-site by KSDK, the St. Louis NBC affiliate, where he discussed how RAD’s technologies enhance urban safety while fostering meaningful community interaction.  RAD security solutions During the event, representatives from several local organisations, including casino operators, professional sports teams, and major property management firms, visited with RAD and the Downtown St. Louis CID to see firsthand how ROAMEO, ROSA, RADDOG LE2, and other RAD security solutions could be used to support safety and operational efficiency in real-world environments. Of particular interest to many of these organisations was RAD’s multiple  SARA™ (Speaking Autonomous Responsive Agent) and ROSS™ (RAD Operations System Software) platforms. RAD’s analytics and automation capabilities Software solutions allow clients to reimagine the role of their existing security infrastructure These software solutions allow clients to reimagine the role of their existing security infrastructure by adding an intelligent, agentic AI layer to legacy hardware. By leveraging RAD’s analytics and automation capabilities, organisations can unlock powerful new functionality from their current systems, enhancing performance, accelerating incident response, and delivering significant cost savings without the need for full system replacement. RAD’s technology: public safety efforts “RAD’s technology has been an impactful addition to our public safety efforts,” said Kelli McCrary, Executive Director of the Downtown St. Louis CID. “The presence of ROSA, ROAMEO, and RADDOG has not only helped deter unwanted activity, but also brought positive attention and community engagement, especially during the excitement of the Frozen Four Championship. This kind of innovation supports our vision for a safer, more welcoming downtown experience.” RAD over traditional security solutions RAD secured deployments of ROSA and RIO units following a competitive review, with city leadership RAD’s momentum extends beyond St. Louis. In Cleveland, RAD partnered with Downtown Cleveland, Inc. to launch a smart security initiative in Public Square, featuring the RIO™ 360 tower with live video integration into the city’s crime centre. In Nashville, RAD secured deployments of ROSA and RIO units following a competitive review, with city leadership opting for RAD over traditional security solutions to enhance monitoring and deterrence in key public areas. How RAD’s solutions meet the evolving security needs As municipalities and CIDs search for scalable, cost-effective ways to secure public spaces, RAD has emerged as a trusted partner in redefining how cities approach safety. From high-traffic districts to major public events, RAD’s AI-powered devices provide 24/7 monitoring, advanced detection capabilities, and autonomous responses that relieve the burden on human personnel. The recent deployments in St. Louis, Cleveland, and Nashville illustrate how RAD’s solutions meet the evolving security needs of urban centres while reinforcing community confidence. RAD's effective security solutions “We’re seeing growing interest from CIDs and public sector organisations that are eager to rethink how they secure their communities,” said Reinharz. “RAD is executing a nationwide campaign to deliver meaningful, affordable, and effective security solutions to cities, towns, and districts across the country. Our technology gives these organisations the tools to protect public spaces, ease the strain on human resources, and deliver a stronger sense of safety for residents and visitors alike.” Outdated approaches and deployments  RAD welcomes inquiries from municipalities, CIDs, BIDs, DDAs, and other organisations “It’s incredibly rewarding to see our devices actively supporting the safety goals of communities like St. Louis, Cleveland, Nashville, and others,” said Troy McCanna, Chief Security Officer at RAD. “These deployments represent a shift away from outdated approaches and a move toward intelligent, responsive technology that delivers results. We’re proud to be working hand-in-hand with local pioneers who are committed to creating safer urban environments through innovation.” How its AI-powered security solutions can support safety goals RAD welcomes inquiries from municipalities, Community Improvement Districts (CIDs), Business Improvement Districts (BIDs), Downtown Development Authorities (DDAs), and other organisations focused on public safety and urban revitalisation.  The Company offers personalised consultations to explore how its AI-powered security solutions can support local safety goals, improve operational efficiency, and strengthen community trust. RAD's security guarding and monitoring model  RAD solutions are precisely designed to provide cost savings to businesses of between 35%-80% AITX, through its subsidiary, Robotic Assistance Devices, Inc. (RAD), is redefining the nearly $50 billion (US) security and guarding services industry through its broad lineup of innovative, AI-driven Solutions-as-a-Service business model. RAD solutions are specifically designed to provide cost savings to businesses of between 35%-80% when compared to the industry’s existing and costly manned security guarding and monitoring model. RAD AI-based analytics and software platforms RAD delivers these tremendous cost savings via a suite of stationary and mobile robotic solutions that complement, and at times, directly replace the need for human personnel in environments better suited for machines. All RAD technologies, AI-based analytics and software platforms are developed in-house.  RAD has a prospective sales pipeline of over 35 Fortune 500 companies and numerous other client opportunities. RAD expects to continue to attract new business as it converts its existing sales opportunities into deployed clients, generating a recurring revenue stream. Each Fortune 500 client has the potential of making numerous reorders over time.

CCOM Global Technologies, experts in managing video surveillance on cruise liners is leveraging Pimloc’s Secure Redact privacy platform, the world’s pioneering automated video redaction AI software solution, to ensure the privacy of uninvolved individuals when disclosing footage to third parties or in response to subpoenas.  The security challenges onboard cruise ships – effectively small towns with up to 5,000 ‘residents’ are huge, and Secure Redact has proven to be highly effective in maintaining passenger privacy during video surveillance. Automatic blurring  Secure Redact’ automatically blurs personal and sensitive data in captured and live security videos.  This enables organisations such as CCOM Global Technologies to quickly and responsibly handle footage from CCTV by protecting and redacting personal data, such as faces and automatically redacting and anonymising the information 200 times faster than traditional video editing services.  Secure Redact platform The technology can be deployed selectively, removing some or all faces or other identifying information Pimloc has developed world-pioneering AI solutions, trained to perform on real-world security footage, through its Secure Redact platform to protect personal data in images and video automatically. The technology can be deployed selectively, removing some or all faces or other identifying information. As a result, video clips that have been selectively anonymised with Secure Redact can be supplied externally, while staying compliant with data privacy laws and regulations.  Privacy, safety, and security “When we are looking at security challenges, we have thousands of people that we need to keep safe and secure, maintaining their well-being,” says Daniel Ginat, Director of Technology at CCOM Global Technologies. “It's a small town, or a Vegas scale of the hotel, with hundreds and hundreds of CCTV cameras. Privacy, as well as security, is key, and Secure Redact helps us to deal with security issues for our clients, while effectively keeping bystanders and other innocents out of the picture.”​ Advanced features After comparing other solutions, CCOM Global Technologies chose Pimloc’s Secure Redact privacy platform for its advanced features and fair pricing, making it the ideal choice. But it wasn't only the features and value that secured the contract with CCOM Global Technologies; communication was also key. “From the start, we felt like the team at Pimloc was very knowledgeable of the system,” Ginat adds. “They could show us exactly all of the features and how to use them. This level of expertise, combined with the platform's capabilities, made Secure Redact the clear choice for us to partner with.” Face detections  Secure Redact creates the final redacted video for download by blurring all the detected personal data Secure Redact automatically processes and ingests any uploaded video from CCOM GlobalTechnologies’ CCTV footage onboard ship, before reformatting it and running machine learning algorithms over each frame to detect all faces. These detections are then marked for redaction as orange boxes on the video and are only viewable by CCOM Global Technologies operatives, who review the results before Secure Redact creates the final redacted video for download by blurring all the detected personal data, ready for export and delivery to their cruise liner client.   Data privacy compliance requirements “We’re delighted to be helping CCOM Global Technologies to maintain privacy during cruise ship video surveillance,” says Pimloc CEO Simon Randall. “Secure Redact meets international data privacy compliance requirements when dealing with personal data in images and video files, and it is the fastest solution on the market. We’re enabling cruise liners to supply video clips externally to employees, customers, or even corporate insurance companies, law enforcement, and lawyers while staying compliant with data privacy laws and regulations.”

In a hyperconnected world, a lack of proactive communication can disrupt operations significantly, particularly in access control and time-attendance management. With over 2 billion global users, WhatsApp stands as a powerhouse in dynamic communication. This widely popular messaging platform provides a seamless way to streamline notifications and approvals, enabling real-time interactions and swift decision-making. Benefits of integration  Matrix not only boosts efficiency and productivity but also fortifies security and HR operations Matrix, renowned for its cutting-edge access control and time-attendance solutions, harnesses the power of WhatsApp to redefine proactiveness. By seamlessly connecting essential workplace systems with a globally trusted communication platform, organisations can achieve unparalleled convenience and reliability in managing workforce operations. Through WhatsApp integration, Matrix not only boosts efficiency and productivity but also fortifies security and HR operations. This ensures that critical access and attendance data are managed with exceptional precision and responsiveness. To maximise the benefits of this integration, it's crucial to understand the steps required to seamlessly connect WhatsApp with the Matrix COSEC system. Matrix COSEC notifications Integrating WhatsApp with COSEC ensures instant and seamless notifications for attendance approvals, access events, and other important updates. This integration simplifies the way employees and management interact by streamlining the process of receiving and responding to time-attendance notifications. Be it leave approvals, late arrivals, or early departures, the integration ensures timely updates to all relevant stakeholders, enabling quick and informed decision-making. WhatsApp integration with COSEC Input these details into the Alert Message Configuration within the Admin Module of COSEC To enable WhatsApp integration with COSEC for alerts and notifications, start by creating a WhatsApp Business account through the Meta Developer Portal. Gather the required details, including the Permanent Access Token, Phone Number ID, WhatsApp Business Account ID, App ID, and Security Token. Input these details into the Alert Message Configuration within the Admin Module of COSEC. Then, specify the types of alerts they wish to receive on WhatsApp and validate the setup by sending test alerts to ensure everything functions smoothly. Team's attendance and access events with WhatsApp integration Receiving real-time updates on a team's attendance and access control events via WhatsApp offers unmatched convenience. Managers and HR personnel can instantly access attendance records, detect access control violations, and review unusual entries directly on their devices. This streamlined approach eliminates the hassle of switching between systems, ensuring immediate access to essential information and enabling quicker responses. With attendance and security event notifications delivered straight to WhatsApp, managers achieve full visibility into attendance trends and security incidents. Proactive approach  Integration boosts active efficiency by centralising touch and streamlining access to critical data Daily summaries of these events enhance organisational transparency, enabling swift resolution of attendance discrepancies and rapid responses to potential security breaches. This integration boosts operational efficiency by centralising communication and streamlining access to critical data. Managers can make timely decisions, whether addressing attendance issues or responding to access violations, with alerts delivered directly to WhatsApp. By ensuring key information is readily available, this proactive approach enhances efficiency and responsiveness throughout the organisation. Integration in time-attendance and access control systems Advanced communication integration for notifications and alerts in time-attendance and access control systems will leverage cutting-edge technologies to enhance efficiency and security. Below are some of the key potential advancements: Anomaly Detection Capabilities: AI-driven algorithms will analyse regular attendance and access patterns to identify anomalies, such as unusual entry times or unauthorised access attempts. These irregularities can be instantly flagged and notified to security personnel or administrators in real-time for prompt action. Personalized Notifications: AI-powered customisation will enable role-based notifications tailored to individual preferences and responsibilities. For instance, management may receive strategic alerts related to security breaches or policy violations, while employees are notified of attendance updates or access approvals, ensuring relevant and focused communication. Predictive Maintenance Alerts: Leveraging predictive analytics, the system can anticipate maintenance needs for attendance and access control systems. Administrators will receive timely notifications about potential issues, allowing them to address concerns proactively before they impact operations. Implementing these advanced features will rely on robust API frameworks, secure data handling practices, and intuitive user interfaces to effectively manage notifications and alerts. With these foundations in place, these developments can significantly improve operational efficiency and security while delivering a superior user experience for time-attendance and access control systems. Revolutionising workplace control with WhatsApp integration The integration of WhatsApp with Matrix time-attendance and access control solutions is set to transform workplace management like never before. This cutting-edge integration delivers real-time notifications and streamlines approval processes, offering unparalleled ease in monitoring and managing workforce dynamics. The result? Enhanced productivity, operational efficiency, and a more connected organisation. Discover how Matrix’s innovative integration solutions can elevate the security and management systems.

Future-proofing your skillset is about embracing continuous learning and developing a versatile set of competencies that remain valuable regardless of technological shifts or industry changes. In the security marketplace, it is not about predicting the exact jobs of the future, but rather equipping yourself to adapt and thrive in the uncertain security landscape. But where to begin? The emerging technology shifts in the security industry provide clues, such as the growing importance of cybersecurity and artificial intelligence (AI). We asked our Expert Panel Roundtable: How can physical security professionals “future-proof” their skillsets to prepare for emerging technologies?

If recent physical security events are a guide, the topic of artificial intelligence (AI) will be everywhere at the upcoming ISC West 2025 exhibition in Las Vegas. Cybersecurity solutions are another core focus at today's physical security events, and ISC West will likely follow the trend. Attendees will also be looking for advancements in access control systems, including biometric technologies and integrated security platforms, among other hot topics. We asked our Expert Panel Roundtable: What will be the big topics of discussion at ISC West 2025?

Technology innovations and an evolving threat landscape will be core factors impacting the physical security market in 2025. Technology elements such as artificial intelligence (AI), multi-factor access control, and mobile devices will continue to drive growth in the greater industry. We asked our Expert Panel Roundtable: What is the outlook for the physical security industry in the year ahead?