Ready or Not, AI Copilots are Here to Stay

What steps can organizations take to prepare for AI copilot adoption?  

AI copilots are emerging as powerful productivity tools, acting as intelligent assistants that help employees work more efficiently by automating repetitive tasks, answering questions and suggesting next steps. As AI copilot tools become more integrated into daily workflows, their ability to streamline work and boost output is hard to ignore. However, alongside these benefits emerge security risks, particularly around data exposure and access control. While these concerns are valid, organizations can no longer afford to ignore or indefinitely postpone the adoption of AI copilots. Instead, security leaders need to proactively lay the groundwork for their secure and effective adoption, starting with data governance and identity and access management. 

AI copilots can quickly analyze vast amounts of information within an organization and use it to support employees in their day-to-day tasks. For example, AI copilots can almost instantly identify relevant details in a large pool of emails, documents and databases, saving employees time in digging through these files manually. Beyond information retrieval, it can discover patterns, trends, or anomalies in data, offering employees valuable insight. While AI copilots significantly increase employee efficiency with their ability to rapidly sift through vast amounts of information, these tools also introduce new data management risks. In its efforts to assist, AI copilot solutions may unearth forgotten or overly accessible information that should have been deleted or restricted. Additionally, outdated or poor-quality data can lead to inaccurate or misleading responses from AI copilots. This highlights the importance of adopting strong data governance practices before deploying AI copilots. Proper data governance controls will help prevent accidental data exposure and ensure compliance with privacy and security standards.  

The adoption of AI copilots is poised to significantly expand the volume of data organizations must manage. As these tools enhance employee performance and enable teams to accomplish more in less time, the pace of work and the rate at which data is generated accelerates. In essence, by helping employees do more, faster, AI copilots help drive the creation of more data. For security leaders, data management is already a pain point, and the integration of AI will only intensify this. While this may give security leaders pause, there are proactive steps they can take to get ahead of this challenge. Chief among them is to establish strong data governance controls before adopting AI copilot solutions. Without this step, organizations risk drowning in data and becoming more vulnerable to compliance headaches and unintended data exposures. 

A secure data governance program starts with implementing data classification and labeling to minimize the risk of accidental data exposure. When data is properly tagged, AI can recognize those labels and apply appropriate controls during processing. For example, AI copilots can be configured to exclude highly confidential information when retrieving or summarizing information. Training employees in secure data management practices adds another layer of protection, ensuring personnel understand how to securely handle sensitive information. Additionally, effective data lifecycle management practices prevent outdated or non-compliant data from being inadvertently accessed or utilized by AI copilots. Together, these practices form a strong data management program and lay the groundwork for a more secure and effective AI copilot implementation. 

Organizations can also strengthen their readiness for AI copilot adoption by putting a secure identity and access management (IAM) program in place. Too often, employees have broader access to sensitive information than they need. AI copilots, acting on behalf of the user, may leverage all the information a user can access to fulfill the user’s requests, sometimes surfacing information the user was not aware they had permission to see. This makes over permissive access a greater concern as it amplifies the risk of data exposure and leaks. To mitigate this, organizations should enforce strong access controls based on the principle of least privilege and conduct regular access reviews. 

Security teams also need to be working closely with their IAM vendors to determine how AI copilot tools can be treated as an identity type. AI copilots access sensitive information, perform tasks and even make decisions, much like humans. As such, they should be granted scoped access, meaning access that is limited to a specific project, workflow or timeframe rather than inheriting everything a user might need access to. For example, a marketing copilot may only need access to the marketing folder and some sales data with no ability to modify files or systems. By assigning access permissions to AI copilots, organizations can minimize access sprawl and reduce the risk of data exposure. Now is the time for security leaders to assess how their IAM vendors are evolving to accommodate AI solutions and prioritize investing in vendors that treat AI tools, such as copilots, as distinct identities. 

As AI copilots become more embedded in everyday workflows, these tools are driving productivity boosts. However, this adoption brings new security risks, from data exposure to identity challenges. To harness the benefits of AI copilots while minimizing the potential security threats, organizations must take a proactive approach in laying the foundation for an effective and secure AI adoption. This starts with strong data governance and robust IAM controls. The AI transformation is here to stay and securing it starts now.  

K logix can help organizations prepare for AI copilot adoption, establishing a comprehensive data governance program and designing a secure and scalable IAM strategy. For more information, please contact one of our experts: info@klogixsecurity.com.