Build a secure Zero Trust foundation for AI

AI is transforming the way businesses operate and innovate in the era of hybrid and remote work. It also brings new challenges and risks, especially when it comes to data security and privacy. As businesses seek to innovate and support their employees from anywhere, they also need to be able to protect their valuable information. Zero Trust is a security framework that adapts to the modern workplace to better protect employees and their devices. It also provides protection for AI technologies, which can be implemented to strengthen security.

Managed data fuels AI models, which relies on large amounts of information to learn, analyze, and generate insights. This need for secured data makes it a vulnerable asset that must be protected from unauthorized access, misuse, and theft. Any breach—endpoint, identity, app, infrastructure, network—can have serious consequences for businesses, such as reputational damage, legal liability, and loss of trust.

By adopting a Zero Trust security framework, businesses can safeguard their access while providing their employees what they need to get work done. Zero Trust follows three basic principles:

1.      Verify explicitly. Zero Trust requires continuous verification of identity and permissions before granting access to data and resources.
2.      Use least-privileged access. Limit user access with Just-In-Time and Just-Enough-Access (JIT/JEA) risk-based adaptive policies.
3.      Assume breach. If something seems off, immediately minimize any potential threat by segmenting access, then use analytics to identify the issue and strengthen defenses.

Zero Trust security ensures that sensitive information is always protected, regardless of where it is stored, processed, or accessed—which is why it’s critical for AI adoption. As organizations embrace AI, having a security model in place to continuously protect their most valuable assets will allow them to drive innovation and be more productive.

Along with stronger security measures, Zero Trust principles can be applied to AI implementation:

Having accurate, complete, and consistent information is essential because it determines the quality of the AI output. If anyone manipulates or tampers with app permissions or managed data, they become corrupted, which will cause the AI tool to produce inaccurate, unreliable, or biased results. Zero Trust protects data integrity by blocking unauthorized access throughout the identity lifecycle.

Access controls are crucial to preventing unauthorized and inappropriate use of AI and the data that informs it. A Zero Trust strategy strengthens these controls by enforcing the principle of least privilege, which prevents employees from accessing any sensitive data, app, endpoint, or identity from potentially using AI for malicious purposes.

As with any modern technology, AI is vulnerable to breaches and cyberattacks—especially with remote devices. Security threats can compromise the confidentiality and availability of managed data, endpoints, and the network—which can have a major impact on the privacy and safety of employees and customers. Zero Trust enhances security through multifactor authentication and sync identification across every device their employees use.

Zero Trust security is not a specific product or solution. It’s a set of principles, practices, and technologies that work together to achieve a high level of security to protect every app, data source, endpoint, infrastructure, and any type of environment, whether your organization is cloud-based, on-premises, or hybrid.

To build and maintain a strong foundation in Zero Trust, businesses should include these important security features and capabilities:

The first principle of Zero Trust security requires explicit verification of all identities and devices before granting access. Trust is never assumed or granted permanently, which makes it dynamic and contextual, meaning that it can change based on situation, location, time, or device.

Least privilege only grants the minimum level of access necessary for a specific task or role. This principle helps reduce the attack surface and any potential damage of a breach by limiting exposure of data, infrastructure, network resources, apps, or endpoints to only those who need them. It also enforces the separation of duties and information as need-to-know, which prevents certain employees from accessing highly sensitive information.

Zero Trust security divides networks and infrastructure into smaller zones or segments based on the sensitivity of data, apps, roles, and business functions. This measure isolates and protects everything from unauthorized or malicious access and will contain and limit the spread of a breach by restricting the movement and communication between segments. Micro-segmentation also helps improve network performance and visibility, as it reduces congestion and allows for more broad monitoring and control.

This capability allows security teams to monitor the network and infrastructure for any anomalies or suspicious behaviors and take immediate action to isolate or mitigate risk. Real-time threat detection and response reduces the impact of a breach while identifying and addressing the root cause. It also helps improve the organization’s security posture through actionable feedback that encourages continuous adaptation and resilience.

Building a secure foundation in Zero Trust is not a one-time project, but a continuous journey that requires a strategic vision, a holistic approach, and a cultural shift.

These steps provide a broad path for organizations to assess where they are currently, where they want to be, and how they can achieve their security goals:

The first step is to evaluate your existing security measures, identify strengths and weaknesses, and determine any gaps and potential risks. An audit will help you understand your current security posture and prioritize your actions to allocate resources accordingly.

Identify any endpoints, apps, infrastructure, networks, data, and resources for your business operations that could cause significant harm if lost or compromised. Classify each asset based on value, sensitivity, and impact. Identifying critical assets will allow you to focus your efforts on protecting what matters most.

Create and document specific rules and policies to govern your defense areas. These policies should be based on the three key principles of Zero Trust: explicit verification, least privilege, and assuming breach. These rules won’t be set in stone but will lay the groundwork for the future.

Deploy technologies that enact and support your Zero Trust policies, such as identity and access management, data encryption and hashing, network segmentation and isolation, threat detection and response, and security analytics and intelligence. These solutions should be integrated and aligned with your business processes, systems, operations, and objectives.

Once your technologies are in place, educate your employees about the importance and benefits of Zero Trust security, along with their roles and responsibilities in implementing and maintaining it. Employee training and awareness can help foster a culture of enhanced security and trust and can increase their engagement and compliance. This training can also help prevent or reduce human error, which are a common cause of security breaches.

Now that everything is up and running, plan time to evaluate your security performance, identify any issues, and find opportunities for improvement. Continuous monitoring will help you maintain and enhance your security posture and become more resilient as the threat landscape evolves over time.

Adopting a Zero Trust foundation can also provide key benefits for AI and for your business:

Zero Trust security ensures that everything—network, identities, endpoints, apps, data, AI tools—are protected, verified, and monitored at all times. Having secure AI communicates trust and credibility to your customers and partners by using the technology responsibly.

A Zero Trust framework helps you meet and exceed the regulatory requirements and standards for data security and privacy, such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), or the Health Insurance Portability and Accountability Act (HIPAA). It also helps you prepare for and respond to new and evolving regulations for AI ethics and governance, such as the AI Act from the European Commission or the AI Principles from the OECD.

By applying the principle of "never trust, always verify" to your data, you can enhance data privacy for AI use by making it accessible only by authorized employees for legitimate purposes. It also helps you respect and protect the rights and preferences of your data subjects, such as customers, employees, or partners, as it provides transparency, control, and consent over their data.

This capability allows security teams to monitor the network and infrastructure for any anomalies or suspicious behaviors and take immediate action to isolate or mitigate risk. Real-time threat detection and response reduces the impact of a breach while identifying and addressing the root cause. It also helps improve the organization’s security posture through actionable feedback that encourages continuous adaptation and resilience.

Explore practical use cases of how having a strong Zero Trust foundation helps AI integration and security

Zero Trust can help protect proprietary AI algorithms, trained AI models, and AI intellectual property. It can also prevent unauthorized or malicious access, modification, or theft, which keeps their integrity and authenticity intact. 

• Scenario: Safeguard your AI algorithms in research and development by hashing your AI code, isolating unique AI environments, and making sure your AI developers have only adequate access.

AI data pipelines include the processes and systems that allow the flow of data from collection to analysis. Zero Trust keeps that data protected, verified, and monitored throughout its lifecycle and makes sure that its quality and accuracy are maintained. 

• Scenario: Secure your data flow from your IoT devices to your cloud platform by tracking and verifying every IoT device, encrypting data in transit and at rest, and segmenting network zones to restrict two-way communication.

AI governance lays the framework and process to ensure your AI use is ethical, responsible, and accountable. Zero Trust security can help you monitor and audit AI access and activity to maintain compliance with your company’s policies and regulations.

• Scenario: Monitor AI performance and behavior by continuously verifying anyone using AI and their devices, encrypting and hashing your AI outputs and logs, and implementing real-time threat detection and response.

Building a foundation in Zero Trust with AI in mind creates a model that effectively adapts to the complexity of the modern environment, embraces hybrid and remote work, and better protects employees, their devices, apps, and data—not matter where they are. It allows businesses to leverage AI technologies with confidence, create new value, and empowers them to innovate and secure their future.

Zero Trust and AI complement each other. As organizations continue to adopt and embrace AI, they need Zero Trust principles to secure and protect their investment. Similarly, as their security posture becomes more complex and dynamic, implementing AI to automate certain functions will reduce the strain on IT teams so they can focus on more important tasks.

Building a secure Zero Trust foundation for AI is crucial for an efficient and secure AI experience. It helps businesses protect their networks, endpoints, apps, identities, data, and infrastructures, enhance their AI performance, and mitigate AI risks. Zero Trust also helps businesses build trust and confidence in their AI systems, improve their regulatory compliance, and enhance their data privacy.

Visit the Microsoft Zero Trust Guidance Center to learn more about how to build a secure Zero Trust foundation for AI.