How AI Has Transformed Traditional Access Control Security Implementations

People need to feel safe. It’s one of our most foundational and fundamental needs. 

Before a company’s compelling product, groundbreaking service, or disruptive technology makes a market impact, its people and spaces need to feel (and be) secure. It’s always a priority, but companies struggle to address this issue in their messaging and practices.

According to the Harvard Business Review, 97% of employees say physical security is essential at work, while just 54% believe their employers share this opinion.

The result? 

Employee productivity declines, turnover increases, and the brand's reputation suffers.  Historically, companies have combated safety concerns with access control solutions. First, they protected their entrances with locks and keys, rudimentary mechanisms that inevitably gave way to technology-driven solutions, such as keycards, PINs, and badge swipes.

Manual oversight often filled the gaps, with security personnel visually verifying identities or monitoring access points to ensure security. While these traditional methods provided a foundational layer of protection, their inherent limitations—such as lost cards, forgotten codes, the potential for human error, and their reactive nature—are becoming increasingly apparent. 

A Paradigm Shift in Access Control

Artificial intelligence (AI) is now transforming access control and physical security. This isn’t a subtle change or an incremental improvement. 

In 2025, AI is doing more than augmenting access control and physical security. It’s reimagining what’s possible, allowing next-generation access control systems to move beyond simple authentication and offer intelligent, context-aware security that supports broader operational goals.

The Evolution from Traditional to AI-Powered Access Control

For thousands of years, people have prioritized access control. The Egyptians leveraged sliding stones and a wooden pin lock to secure their doors. Robert Barron introduced lever tumbler locks, which required a key to lift internal levers to a precise height in 1778, and Linus Yale patented a cylindrical pin tumbler lock in 1848.

Access control was electrified in 1952 when Frank Best introduced the first electronic access control system, which allowed keyless entry and alarm integration. In other words, humans have been inventing and refining access control solutions for a while. Of course, today’s access control technologies are significantly more sophisticated than a stone.

Modern access control began to shift in the late 20th century with the introduction of magnetic stripe cards, keypads, and RFID readers. However, these systems still relied heavily on physical credentials and were limited in gathering and analyzing real-time data, as well as in dynamically adjusting access rights.

While groundbreaking when they first emerged, traditional access control systems often struggle to keep pace with the sophisticated security challenges faced by modern organizations. Today, issues such as tailgating, credential sharing, and the inability to quickly adapt to new threats highlight their shortcomings.

Meanwhile, the need for the most sophisticated security solutions is more urgent than ever before. Incidents of workplace violence are on the rise, increasing by 11% between 2015 and 2019, with a subsequent spike following the COVID-19 lockdowns and work-from-home movement.

As a result, employee expectations, regulatory requirements, and the increasing sophistication of threats are making workplace security a non-negotiable priority. The latest technologies are making it more possible for companies to tackle all these problems simultaneously. AI-powered access control leverages facial authentication, machine learning, and behavior-based authentication to make real-time decisions and proactively identify and mitigate threats. These systems reduce human error and administrative burden, offering scalability and adaptability that traditional systems often lack.

More specifically, they allow organizations to become proactive in their security posture. Rather than reacting to threats after they occur, AI enables systems to learn, adapt, and make informed decisions in real time, fundamentally changing how organizations protect their assets, people, and premises.

In short, badges = "something you have," pin codes = "something you know," and biometrics = "something you are." Fundamentally, we are moving away from "something you have" and "something you know" to "something you are,” which eliminates many shortfalls of legacy methods, such as items being lost, shared, stolen, or forgotten.

Key Transformations Driven by AI in Access Control

AI is in the midst of an undeniable hype cycle, making it easy to overpromise and underdeliver on the technology’s potential.

Private investment is surging, reaching over $130 billion globally in 2024, while AI investment from other entities, including public companies, corporate R&D, government funding, data center infrastructure, and talent development, is similarly surging.

This high spending creates an incentive structure that encourages overhyping the technology’s capabilities, and the marketplace is flooded with products touting their AI capabilities. The result is a product and service ecosystem in which it can be challenging to differentiate real-world value from future promises and potential value. 

AI’s integration into access control is different. It’s not a single innovation but a multifaceted evolution with real effects on how security is perceived and implemented. Some of the key transformations include: 

Intelligent Decision-Making

AI can make decision-making more sophisticated by introducing a layer of data-driven discernment to access control.

For example, AI-powered access systems don’t rely on credential checks, badge swipes, or code entries, which can be forged, stolen, or lost. Instead, AI-powered access control systems can dynamically assess the legitimacy of an access request by analyzing various data points, including: 

●  Contextual information such as the specific door or turnstile, the time of day, a user's GPS-verified proximity to the entry point, and the security level of the accessed area.

●  Behavior patterns within the physical environment, such as an individual's typical entry and exit times for specific buildings or zones, common pathways taken through a facility, or even dwell time near sensitive access points, can be observed and learned.

●  Environmental factors, such as localized security alerts for the area, unusual activity detected by nearby sensors, or extreme weather conditions that impact building access protocols, are also taken into consideration.

AI enables systems to assess user identity and access requests based on context, behavior patterns, and environmental factors, reducing false positives and enhancing security accuracy.

Enhanced Integration

AI-powered access control systems integrate seamlessly with video surveillance, intrusion detection, and building management platforms to provide unified situational awareness.

This holistic integration provides unified situational awareness of the physical environment, offering security teams a comprehensive, real-time map-based view of access events, alarm statuses, and visual data. This leads to faster, more informed, and more effective interventions against physical threats.

Predictive Security

Machine learning algorithms identify anomalies and predict potential threats before they occur, enabling preemptive action.

Advanced AI models can go further, correlating multiple, seemingly minor physical anomalies to predict potential physical threats, such as an impending forced entry attempt or reconnaissance activity by a possible intruder.

Frictionless Access

Increasing security while introducing unnecessary friction into the process is a recipe for frustrated employees and cutting corners. AI-powered access controls accomplish both without compromise.

Facial recognition, biometric analysis, and tailgate detection enhance user convenience while maintaining robust authentication protocols.

Scalability and Adaptability

AI systems can evolve in response to changing organizational needs, user behavior, and evolving threat landscapes, offering long-term flexibility and resilience.

As new intrusion techniques or physical security risks emerge, AI models can be updated with new threat signatures or identify novel suspicious activities through anomaly detection capabilities. 

This continuous learning ensures the physical access control system remains effective over time, protecting the organization’s premises, assets, and personnel against current and future physical risks without requiring frequent, costly system overhauls.

Navigating Ethical Concerns with Care

As AI systems become increasingly powerful and mainstream in security applications, there is a corresponding increased focus on their ethics. Put differently, employees want security but don't want to compromise their privacy, and regulators are increasingly scrutinizing the deployment and governance of AI technologies.

Parsing the ethics of a constantly changing technology can be difficult. They encompass everything from how the data used to train AI models is collected and whether it’s representative of all demographics and use cases to the types of decisions the AI models are authorized to make and specific considerations around technologies like Generative AI. For companies looking to leverage the AI-powered access control technologies to make their facilities safer, key ethical considerations include:

Data Privacy and Collection

Data privacy regulations, such as the European Union’s General Data Protection Regulation (GDPR) and California’s Consumer Privacy Act (CCPA), impose strict rules on data privacy and collection, particularly concerning AI-powered access control systems and biometric data.

Companies must ensure that biometric data is collected lawfully, stored securely, and processed with explicit consent from the user.

Employees, visitors, and other stakeholders have the right to access, rectify, erase, and restrict the processing of their data. Additionally, companies must inform users about their data usage and provide clear, transparent privacy policies. 

Before implementing AI-powered access control solutions, it is essential to understand how user data is collected, stored, and protected, as well as how individuals will be informed about how their data is being used. 

Algorithmic Bias and Fairness

AI models are trained on data, and if that data reflects existing biases, the AI can perpetuate or even amplify them. That’s why AI-driven access control systems must be trained on representative datasets, so they operate fairly and accurately.

A prominent MIT Sloan School of Management report found that AI often reflects societal biases, including gender and racial disparities.

AI models should be trained on datasets that encompass a diverse range of demographics to prevent biased results. When coupled with regular evaluations to measure disparities in accuracy across different groups, companies can proactively identify and mitigate potential biases, allowing their access control solutions to improve progressively over time.

Transparency and Explainability

When an AI system makes a decision, like denying access, can the reasoning behind that decision be understood and explained? Black-box AI systems can be problematic in sensitive applications; explainability is needed to build trust, ensure accountability, and identify potential errors or biases in the system’s logic.

Confidentiality with LLMs

A large language model (LLM) may utilize a company's internal data to train, enabling it to perform tasks more effectively specific to that organization. However, providers of this technology must ensure that company secrets and proprietary information remain confidential.

This is especially important when that data includes people’s biometric information.

Ethical AI in Action

Aligning with a standard like ISO 42001 sends a powerful message to organizations implementing AI, particularly in sensitive areas like security and access control. It demonstrates a proactive commitment to responsible AI governance, moving beyond mere compliance to actively manage the risks associated with AI technologies.

Following these frameworks can help build crucial trust with customers, employees, and regulatory bodies, assuring them that the organization is not only leveraging the power of AI but is also dedicated to its ethical and transparent application. It can also introduce a more formal approach to AI management systems, streamlining internal processes, fostering a culture of accountability, and providing a clear roadmap for improving AI systems.

For C-suite decision-makers tasked with selecting and implementing AI-driven access control solutions, ISO 42001 offers a valuable benchmark. 

When evaluating potential vendors, inquiring about their alignment with or certification against this standard can provide significant insight into their commitment to ethical AI development and robust governance practices. 

Selecting technology partners who adhere to such standards can help mitigate potential reputational, legal, and operational risks associated with AI deployment. It also ensures decision-makers and stakeholders that their AI-powered access control solutions are being deployed with integrity, transparency, and intentionality. 

The Intelligent Future of Access Control

AI is here. It’s reshaping the products we use, the services we rely on, and the processes that improve both over time. It’s also reimaging access control solutions in real-time. This can be great news.

AI-driven systems provide enhanced accuracy, predictive capabilities, seamless integration, and a more convenient user experience, all while adapting to the evolving needs of modern enterprises. Even so, the implementation challenges are real as companies strive to balance technological advancements with robust ethical frameworks, transparency, and uncompromising attention to privacy. 

Keeping people safe is non-negotiable, as is using the best solutions available to achieve that goal effectively, responsibly, and ethically.