Navigating Identity and Access Management in the Era of AI

Whether you’re prepared for it or not, the AI revolution is here. While many organizations are scrambling to get their arms around artificial intelligence (AI) technology, others feel that they’re missing out on adding critical business functions to their identity and access management (IAM) program.

With all the new promises that AI technology brings to the identity space, where should your organization start when it comes to AI? Before implementing a solution within your IAM environment, it’s critical to understand and address the technical implications, privacy concerns and threats of social engineering that AI brings with it.

AI has brought significant transformation to the IAM landscape. However, the integration of AI into IAM systems is not without challenges, especially when it comes to data privacy and potential social engineering attacks.

AI's capacity to process and analyze vast amounts of data can inadvertently expose sensitive information if not carefully managed. Attackers may exploit AI tools to simulate legitimate access requests or impersonate trusted entities within IAM systems, breaching security protocols. AI also poses potential privacy concerns when used in identity verification processes, including:

• Credential theft: Attackers can use AI to compromise credentials or expedite password cracking.

• Social engineering: AI can be a double-edged sword when it comes to social engineering. On one hand, it can be used to detect and prevent attacks — on the other, it can be manipulated by malicious actors to stage attacks by impersonating IT help desks or those with high levels of access into corporate systems.

• Data misuse: Unprotected large language models may potentially misuse private data. For instance, consider what happens when a team member uses ChatGPT to summarize a long, confidential document. While that user may receive a summary of key points and close the application, the data present in that document still exists within the large language model and may be accessible by other users outside the company.

While AI offers powerful IAM tools for detecting and preventing threats like these, it requires implementing strong data loss protection controls, document management, and access control procedures. Organizations must remain vigilant, balancing the benefits of AI with comprehensive safeguards to protect against its misuse.

Amid all the AI discourse, the question of data privacy is discussed often. With all the data required for AI solutions, people everywhere have become increasingly concerned about who has access to their data, how it’s being used and whether it’s being used ethically.

AI-driven analytics enable organizations to effectively catalogue and assess the data they possess, ensuring that only essential information is retained and utilized. To align your organization with ethical and legal data privacy standards and optimize data storage, reducing unnecessary data accumulation is key. Swiftly identifying and categorizing data will allow your organization to better tailor access controls, reinforcing security measures and enhancing operational efficiency across digital ecosystems.

Consider these important steps before implementing an AI solution:

• Data identification: First, your organization must identify the data it has and understand its purpose. This is especially important when it comes to large language models trained on your data.

• Data minimization: To maintain data privacy and optimize data storage, organizations should only ask for and store necessary data.

• Compliance with regulations: In regions like the European Union, stringent regulations have been put in place to govern AI usage, while in the U.S., no national regulations exist; however underlying data regulations (like GDPR in the EU and HIPAA, FERPA and state regulations in the U.S.) still apply to all organizations. With varied AI regulations in different regions, organizations need to define acceptable use parameters for AI and ensure they align with regional regulations. If processing data on EU citizens, for example, organizations must adhere to EU-AI regulations.

With all the risks and rewards AI solutions bring to the IAM space, where should your organization start? The first and most important question that you’ll need to answer is, “Why does your organization want to implement an AI solution?”

Often, organizations feel like they must implement an AI solution to combat the fear of missing out. While it may feel like hesitation comes with the risk of being “left behind,” the decision to use AI in your IAM program is one that requires careful planning and consideration. Rather than immediately inputting all your company data into an AI identity solution and hoping for an ideal outcome, it’s critical to define how your organization will be using AI. What are the anticipated benefits? What are your use cases for it?

An organization in the airline industry, for example, may have a very specific need for AI to optimize performance or ensure that the right crew members have access to their systems at the right time. With a clear goal in mind, this airline will be able to outline their specific uses for it, put together policies and procedures around that AI solution for acceptable use and, ultimately, use that AI solution to help them achieve their goals safely. However, without a clear goal in mind, your AI solution may fail, break regulations or, in the worst cases, unknowingly expose your data to individuals outside of the company.

Whatever your AI or IAM maturity level, it’s important to recognize that there are already team members within your organization and customers outside of it who are using AI today. In fact, they may even have very well-developed software lifecycle onboarding for AI solutions. No matter the situation, it’s important to understand where AI already exists within your organization to focus on how best to use and govern it.

Once you’ve clearly defined the purpose and scope of your organization’s usage of AI within your IAM program and identified the areas in which AI usage already exists, your next task is determining how to use, manage and evaluate it. This involves establishing:

• Robust data privacy policies which adhere to relevant regulations
• Access controls to limit the use of sensitive data by unauthorized parties
• Continuous monitoring for any misuse or breaches in security protocols
• Actions which must be taken when misuse or security protocol breaches are detected

An artificial intelligence policy essentially codifies the concept of your organization’s use of AI. Within this policy, you must clearly define the purpose and scope of AI usage within your IAM systems, outlining specific use cases and policies. Those policies will shape your organization’s standards, procedures and, ultimately, your AI governance model.

How do you ensure that AI is going to be used in a trustworthy and explainable way?  Begin with a solid governance strategy informed by your organization’s culture. The National Institute of Standards and Technology’s AI Risk Management Framework (NIST AI-RMF) can help enable a risk-informed AI governance model. Following the NIST IAM Framework is also a great place to start. NIST's IAM Roadmap seeks to align diverse initiatives for a secure, interoperable and equitable identity ecosystem, emphasizing collaboration with federal, commercial and international partners to enhance the identity landscape and digital service delivery.

Though AI technology brings with it a myriad of potential benefits, especially in identity management, it is essential to also understand and address the technical impacts, privacy concerns and vulnerabilities that come with this new technology. With proper implementation and governance, AI can bring great value to identity management processes, enabling secure and efficient access to digital resources.

It’s also essential for organizations to stay informed and adapt as the AI landscape evolves. An expert partner with deep expertise in IAM as well as AI will understand your organization’s position within your AI journey and provide solutions tailored to meet your needs. CDW experts can help your organization harness the power of AI within your IAM program while navigating challenges and ensuring data privacy, security and compliance to help your organization take full advantage of the benefits AI has to offer.