By Mike French | December 6, 2024
A rtificial intelligence (AI) continues to reshape how we conduct physical and network security. 2025 is promising even greater advancements. Across organizations of all sizes, AI-driven solutions enable security capabilities that were once only accessible to enterprise organizations with large budgets.
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Business leaders have gotten savvy and are prioritizing AI investments strategically, focusing on areas where technology can drive the most impact. Upskilling the workforce and attracting AI-familiar talent are also top priorities, as research from Gartner reveals that 85 percent of CEOs anticipate the need for significant improvements in AI-related skills over the next three years.
In 2025, AI will deliver deeper insights into security operations, automate complex tasks, and empower newer and under-resourced security officers with tools that provide the expertise of seasoned veterans. This article explores the trends shaping AI in physical security for 2025 and beyond. To start, we’ll clarify some key AI terms.
Understanding AI in Security
Artificial Intelligence (AI) technology might sound complex, but it’s more approachable than you think. Here's a breakdown of essential concepts to help you understand AI and its applications in security.
What is Artificial
Intelligence (AI)?
“AI” refers to computer systems capable of performing tasks that typically require human intelligence. These tasks include learning from data, identifying patterns, making decisions, and taking on their own or recommending actions to human operators. AI powers many tools we use every day, such as voice assistants, facial recognition systems, and fraud detection algorithms.
Learn More: Everything You Need to Know About Artificial Intelligence and Physical Security
What is Machine
Learning (ML)?
Machine Learning is a subset of AI that focuses on teaching computers to learn and improve from data without explicit programming. Instead of following fixed instructions, ML algorithms analyze vast amounts of information to recognize patterns and make predictions or decisions. For instance, ML enables a system to detect unusual activity on security cameras or recommend the next steps in a workflow based on previous outcomes.
What is Generative
AI (GenAI)?
Generative AI creates new content, such as text, images, or music, by learning patterns from massive datasets. Tools like ChatGPT or AI art generators use this technology to produce human-like text or realistic-looking visuals. For example, showing an art GenAI program many images of cars can create new ones that look like real cars.
What are Large Language Models (LLMs)?
Large Language Models are AI systems trained on extensive text data from books, articles, and other sources to understand and generate human-like language. They power chatbots, translation tools, and content generation systems. LLMs predict the next word or sentence based on learned patterns, enabling natural and context-aware communication. This technology is vital in customer support systems, security briefings, and real-time language translation applications.
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2025 AI Trends in Physical Security
Let’s explore what’s over the horizon in 2025 for security.
Using AI to Maximize Security Efficiency
AI helps organizations to adopt proactive, data-driven approaches to threat management. By leveraging real-time data and predictive analytics, AI-powered tools can analyze vast datasets, detecting patterns and anomalies at speeds far beyond human capability.
Machine learning plays a pivotal role in this transformation. Machine learning algorithms can predict and preempt security incidents by studying historical data and evolving threats. For example, advanced deep learning models used in video surveillance can identify specific objects or behaviors captured by a video feed.
In 2025, more and more organizations will deploy AI systems that integrate seamlessly with existing security infrastructure, acting as an intelligence layer over surveillance cameras, access controls, and IoT sensors. This will improve situational awareness and allow security personnel to focus on high-priority tasks, automating routine monitoring and freeing up valuable resources for strategic decision-making.
Learn More: [Definition] What is Physical Asset Surveillance?
A Growing Need for Unified Security Ecosystems
Organizations are facing diverse and sophisticated threats. Centralizing various physical and network security technologies into a single, integrated platform enhances situational awareness, operational efficiency, and response times. These programs, sometimes called security convergence, combine surveillance, access controls, IoT devices, and incident management tools. They improve real-time monitoring capabilities and enable security teams to assess threats holistically.
We will see an increased push from business and security leaders in 2025 to unify security. This approach eliminates the need for extensive upgrades and replacements, allowing organizations to create a comprehensive "single pane of glass" interface. Such platforms streamline operations and empower security teams to deliver faster, more cohesive responses to potential threats.
AI for Outcome-Driven Security Enhancements
Outcome-driven activity is a business concept that has been around for a while. It involves working backward from the outcome you want to achieve rather than specifically focusing on profit. The idea is that the profits will follow by focusing on good, strategic outcomes. For example, they seek the outcome of fully satisfied customers who become brand advocates. Or seeking a more secure workplace that helps attract and retain the best talent.
What will be new in 2025 is more and greater use of AI in achieving outcome-driven security enhancements. AI applications in physical security include automating event detection through advanced video analytics, prioritizing emergency response, and filtering vast amounts of data into actionable insights. By leveraging AI to classify incidents and highlight process inefficiencies, security teams can move from data overload to targeted decision-making.
Cloud-Based Security Solutions Powered by AI
The security landscape will rapidly evolve in 2025 as more organizations transition to cloud-based systems. Key drivers behind this shift include the need for scalable solutions that can grow with organizational demands, remote management that enables flexibility across distributed teams, and seamless integration for unified security ecosystems.
These advantages allow organizations to adapt quickly to changing environments while managing infrastructure more effectively. It will also allow wider use of resource-intensive AI systems, including in security. Running LLMs and generative AI tools can take a lot of computing resources, typically more than any medium-sized business could hope to have on-premises. As more and more businesses move to the cloud for their security, we’ll see their ability to use AI increase many fold.
Learn More: Corporate Security: What an Integrated Access Control System Can Do?
The Rise of AI-Powered Autonomous Security Solutions
2025 will see more autonomous technologies integrate seamlessly into broader security ecosystems, enabling enterprises to automate patrols, conduct real-time surveillance, and respond to incidents instantly. Autonomous security solutions are reshaping how organizations protect their assets and operations, offering advanced capabilities for patrolling, monitoring, and responding to threats.
Technologies like drones, robots, and smart management systems provide 24/7 coverage, eliminating fatigue and extending security into hazardous or challenging areas for human personnel.
Equipped with AI-driven analytics, advanced sensors, and cameras, autonomous systems excel at detecting anomalies, tracking movements, and delivering real-time data to security teams. These solutions enhance situational awareness and significantly improve response times by reducing reliance on human intervention.
More Network Attacks on Physical Hardware
As AI tools become increasingly accessible, 2025 is set to witness an uptick in sophisticated cyberattacks targeting physical hardware and networked infrastructure. Generative AI has democratized advanced hacking capabilities, enabling malicious actors to develop stealthier, more destructive exploits without needing technical expertise. Physical security systems—such as access control devices, surveillance networks, and smart lockers—are particularly vulnerable as attackers leverage AI to exploit weak points in IoT-connected devices.
To mitigate these risks, organizations must adopt robust security protocols, invest in hardened hardware systems, and implement AI-powered threat detection tools to monitor and secure both software and hardware layers.
AI Driving IoT Adoption and Business Integration
The IoT ecosystem continues to expand, connecting access controls, smart storage solutions, inventory management, and environmental systems into unified networks. While this integration streamlines operations and boosts efficiency, challenges persist for businesses using outdated legacy systems.
In 2025, AI solutions will play a critical role in bridging the gap between legacy infrastructure and modern IoT tools. These AI-driven systems can automate the data exchange between segregated systems, simplifying workflows and reducing manual intervention. By doing so, organizations can unlock the full potential of IoT, ensuring seamless operations across their infrastructure.
Learn More: What is an IoT-Based Asset Tracking System?
Revolutionizing Security with Advanced Analytics Tools
AI-powered analytics tools are expected to further transform security monitoring and forensic investigations in 2025. Behavioral analytics will evolve to detect subtle anomalies in individual actions by analyzing access logs and live video feeds, and flagging potential threats in real time. These pre-analyzed insights allow security personnel to focus on high-priority responses, saving critical time during incidents.
Forensic analytics will improve investigative efficiency by automatically scanning historical data and video archives for notable patterns or events. These insights can be directly integrated into case files, speeding up resolution and supporting legal or regulatory processes. These advancements highlight how AI will continue to empower security teams with actionable intelligence to stay ahead of evolving threats.
The Expanding Role of AI in Physical Security
AI's influence on physical security is set to grow even more in the coming years. Video analytics will continue to evolve, offering more precise motion detection and object recognition capabilities that enhance real-time threat identification. Emerging tools, like advanced behavioral analysis systems, will provide deeper insights into patterns and anomalies, enabling security teams to act proactively.
Innovative applications, such as predictive analytics, are beginning to demonstrate their potential, with some organizations piloting systems that forecast risks and identify high-priority areas for intervention. Early successes suggest these tools could redefine how security teams operate, pushing the industry toward a future where intelligence-driven strategies dominate. As AI becomes more integrated into security practices, it will transform physical security into a more adaptive and responsive field.
Learn More: Everything You Need to Know About Artificial Intelligence and Physical Security
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