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AI in security: predictions from AITX's Steve Reinharz

18 Jun 2025

AI in security: predictions from AITX's Steve Reinharz
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Artificial Intelligence Technology Solutions, Inc, a global pioneer in AI-driven security and productivity solutions for enterprise clients, released insights from Steve Reinharz, CEO/CTO and founder of AITX and Robotic Assistance Devices, Inc. (RAD), highlighting his top five predictions for how artificial intelligence will reshape the security industry in 2026 and beyond.

According to Reinharz, adoption of advanced AI security solutions is rapidly shifting from early adopters to mainstream acceptance. Direct client feedback, industry partnerships, and ongoing technology advancements all point to a period of major transformation in security.

Cloud computing

“As we approach the midpoint of 2025, the inflection point for AI in security is clear,” said Reinharz.

“Just as we saw rapid shifts when IP cameras, smartphones, and cloud computing redefined expectations, we are now seeing the same momentum with AI-powered security. When the practical benefits become clear, widespread adoption accelerates quickly.”

“Every conversation with clients, partners, and industry leaders signals the same thing: security is undergoing a major transformation.”

Five predictions

Reinharz outlined the following five predictions as the trends most likely to shape how organisations approach security in the coming years:

Autonomous security becomes the new standard

By 2026, AI-powered security solutions, including autonomous patrol and surveillance platforms and interactive AI agents, will move from a niche interest to widespread adoption. Reinharz expects organisations to shift away from traditional manned guard posts and embrace autonomous security for surveillance and patrols, featuring intelligent incident detection and immediate response.

AI-driven monitoring will surpass human monitoring

Human attention is limited, but AI operates without these constraints. Reinharz predicts that most monitored video feeds worldwide will soon be managed by AI, with only the most complex or urgent events requiring human review. Rising costs, operator fatigue, and the need for constant vigilance are making AI the preferred choice for around-the-clock monitoring.

Security becomes predictive, not just reactive

The days of reviewing video after an incident are coming to an end. Reinharz sees security platforms evolving to identify patterns and anomalies in real time, taking immediate and proactive action. Automated voice and visual alerts, combined with instant escalation, will help organisations prevent incidents rather than just responding after the fact.

Physical and cybersecurity merge

The distinction between physical and digital threats is quickly disappearing. Reinharz anticipates a rise in unified security strategies that integrate AI-driven physical security devices with advanced cybersecurity tools. Access control, surveillance, and threat detection will operate together on cloud-based platforms, providing organisations with a single, integrated view of risk.

RMR surpasses CapEx in security budgets

The security industry is moving away from capital expenditures on hardware and toward subscription-based models. Reinharz expects more organisations to adopt AI-powered solutions delivered as a service, which ensures systems remain current, connected, and continually improving. This shift allows for regular updates, analytics, and enhancements, all included in a recurring monthly revenue model.

“If 2025 is the year the AI conversation in security becomes real, 2026 will be the year action takes over,” Reinharz added.

“At AITX and our RAD subsidiaries, our team is focused on staying ahead of these shifts and helping our clients do the same. The future is already taking shape.”

Discover how AI, biometrics, and analytics are transforming casino security

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Discover AITX's insights on AI in security. Steve Reinharz predicts AI-driven autonomous security will transform the industry by 2026, merging physical and cybersecurity, enhancing predictive measures, and shifting to RMR-based models.

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