AI-Powered Analysis: The Future of Agentic Security

Agentic Security Rewrites the Rules of Modern Protection

The security landscape transformed dramatically in 2022. Ransomware gangs now wield AI to supercharge their attacks. Nation-state hackers probe our infrastructure at an unprecedented scale, with Check Point Research reporting a 70% surge in utility cyberattacks in 2024 compared to the same period the previous year. The National Retail Federation's 2024 Security Survey reveals crime rings that operate like businesses, complete with sophisticated theft strategies and resale networks.

Static, one-size-fits-all defenses fail to protect against these evolving threats.

When AI Joins the Security Team

Traditional security measures followed a predictable script: wait for alarms, review footage, file reports. Rinse and repeat. But just as streaming services revolutionized how we watch TV, intelligent security systems are transforming how people protect assets. And the technology requires smart people to harness its capabilities.

"The human is still part of this puzzle," LiveView Technologies CTO/CIO Steve Lindsey told Loss Prevention Magazine. "We're not being displaced by AI. We're trying to make humans more efficient."

Take the 2023 DanaBot takedown. This modular botnet had frustrated security teams by rapidly adapting its tactics and infrastructure, rendering traditional defenses useless. But according to VentureBeat's October 2023 analysis, agentic AI helped analysts dismantle the threat by autonomously detecting behavior patterns and correlating global telemetry. What once took months of manual forensic work was reduced to weeks. 

From Transit to Power Grid: AI Guards Critical Infrastructure

In June 2024, Las Vegas made headlines when its public transit system became the first in the U.S. to deploy AI gun detection across its bus fleet. The system monitors camera feeds for weapons, alerting operations centers instantly if a threat is detected.

Meanwhile, critical infrastructure sites use AI to guard against both cyber and physical attacks. After the 2022 Moore County, North Carolina, substation attack, many facilities deployed intelligent video analytics that can detect intruders even in total darkness using thermal imaging. These systems continuously learn from each alert, automatically adjusting their detection parameters based on confirmed threats versus harmless activity like wildlife movement. At Georgia Tech, researchers use AI to scan thousands of internet-facing energy devices for vulnerabilities, helping utilities proactively plug security holes before adversaries find them.

"We’re seeing a fundamental shift in how security operates," Leo Simonovich, head of industrial cyber at Siemens Energy, told Latitude Media. "AI can be a good defensive shield—we've been very focused on deploying tools and technologies that help give the defenders the advantage." 

Retail's AI Revolution

Retail security teams face a perfect storm: sophisticated theft rings, violent shoplifters, and limited staff to counter these threats. According to the National Retail Federation's 2024 report, retailers that can track organized retail crime incidents reported a 57% increase in such crimes from 2022 to 2023. Multi-person thefts have also increased, with 62% of retailers saying coordinated thefts by small groups is an increasing concern.

“Retail crime is a complex and sophisticated challenge, with trends that continue to metamorphose,” University of Florida Research Scientist and Loss Prevention Research Council Executive Director Dr. Read Hayes said. “The retail industry is working in lockstep with the research community and solutions providers to develop, test, and improve the next generation of asset protection tools and strategies in the ongoing battle against ORC.”    

Modern surveillance systems use computer vision models trained on extensive hours of footage, learning what normal shopping looks like versus red flags. These systems continuously improve their accuracy by analyzing each incident. For instance, if the same group hits multiple store locations, AI can identify similar behaviors and alert asset protection teams to potential organized retail crime patterns. When potential theft is detected, these AI platforms can immediately alert security staff, helping teams to respond before losses occur. 

Building Better Defenses

At construction sites, AI-enabled cameras act as tireless guards. The National Insurance Crime Bureau and the National Equipment Register estimate that the theft of heavy construction equipment costs between $300 million and $1 billion annually, making adaptive AI surveillance measures a game-changer for the industry. These construction surveillance systems calibrate to individual environments, learning normal patterns within days. For example, after observing routine operations, the AI automatically adjusts its alerts, distinguishing between scheduled crane movements and suspicious night activity. As construction progresses and site layouts change, the system continuously recalibrates what "normal" looks like, ensuring consistent security through each project phase. 

Evolving Security Through Continuous Learning

Organizations succeeding with agentic security share a common approach: they treat their AI systems as dynamic learners. This evolution happens through three key processes:

1. Systems learn from each incident. 

When retail AI spots a new theft tactic or a utility's defensive AI blocks a novel cyber threat, that data feeds back into the system. This continuous learning reduces false alarms while improving threat detection accuracy over time.

2. Organizations regularly assess their AI's performance against emerging threats. 

Real-Time Crime Centers, for example, continuously fine-tune their pattern-recognition algorithms based on changing criminal tactics. This adaptive approach, as noted by Police1, helps law enforcement advise security teams on how to stay ahead of evolving challenges.

3. Cross-industry collaboration strengthens these adaptive strategies. 

The U.S. Cybersecurity and Infrastructure Security Agency encourages critical infrastructure sectors to share AI-related incidents and lessons learned, creating a broader knowledge base for defensive systems.

The evidence is clear: static security measures have become as outdated as VHS tapes in a streaming world. From utilities preventing cyberattacks to retailers stopping organized theft rings, adaptive security systems prove their worth across industries. These solutions don't just react—they learn, adapt, and protect in real-time.

Bad actors constantly refine their techniques, which makes it difficult for existing static defenses to keep pace. But agentic security with AI creates something better: security that evolves and anticipates, keeping your business protected, even as emerging challenges arise.

Contact our team today to learn how to enhance your security strategy with LiveView Technologies’ agentic security, powered by machine learning, and outthink evolving threats. Contact our team today to schedule a demo.

FAQ

Q: What is Agentic Security?

A: Agentic Security is an adaptive security model that uses AI and machine learning to autonomously detect, assess, and respond to potential threats. Unlike traditional systems that passively record events, agentic security anticipates risks in real time and dynamically adjusts its response strategies.

Q: How does Agentic AI Security differ from traditional AI systems?

A: Traditional AI in security often operates on static rules—triggering alerts based on predefined conditions. Agentic AI Security behaves more like a seasoned human guard: it learns from behavior patterns, adapts its approach, and executes intelligent deterrents using AI-powered analysis.

Q: Why are current security strategies no longer sufficient?

A: Today’s threats—from organized retail crime to critical infrastructure sabotage—are more complex and fast-moving than ever. Human attention spans and reactive technologies can’t keep pace. Agentic Security solves this by augmenting teams with intelligent systems that never fatigue, overlook, or repeat errors.

Q: What makes Agentic Security “adaptive”?

A: Its machine learning foundation. These systems continuously analyze historical and live data, improving their ability to distinguish between routine and suspicious behavior. They evolve alongside the threat landscape, refining responses over time.

Q: Where is Agentic AI Security being used successfully?

A:

• Retail: Identifies coordinated theft strategies and reduces incidents by up to 40%
• Construction: Detects off-hour movement patterns and protects against equipment theft
• Critical Infrastructure: Monitors remote sites, filtering out false positives and responding instantly to actual threats

Q: What are the measurable results of using Agentic Security?

A:

• 40% reduction in parking lot crime
• False alarms significantly decreased
• Response times cut from minutes to seconds
• Expanded coverage across sites—without increasing security staff

Q: Is Agentic Security hard to implement?

A: Not at all. Agentic AI Security platforms typically integrate with existing infrastructure, require minimal training, and scale incrementally. They focus on behavioral patterns, not identities, making deployment both effective and compliant.

Q: How can organizations get started with Agentic Security?

A:

1. Identify gaps in your current security strategies
2. Set clear performance goals (e.g., reduce false alarms, speed response)
3. Deploy agentic AI in high-risk or high-traffic areas
4. Use real-world data to optimize and expand coverage