Alaska University Drafts AI Policy for Campuses
University of Alaska leaders propose a new framework to manage artificial intelligence use, balancing educational benefits with data security concerns.
Leadership at the University of Alaska has presented a draft policy to its Board of Regents, aiming to establish mandatory artificial intelligence plans for all three campuses. If approved, the directive would require faculty, staff, and students to adhere to specific guidelines regarding the use of AI tools in academic and administrative settings. The proposal seeks to standardize how the institution handles these emerging technologies while addressing long-standing questions about data privacy and institutional control.
The draft emphasizes that AI should augment human talent rather than replace it, while prioritizing the security of sensitive data. According to Ben Shier, the university’s Chief Information Technology Officer, the core challenges presented by AI are not entirely new but are significantly amplified by the technology's reach. He noted that issues such as monitoring usage and protecting privacy have always existed in higher education, but AI brings these concerns into sharper focus by expanding the volume and variety of data processed.
AI adoption is widespread among students
The push for formal policy comes against a backdrop of rapid adoption in higher education. A 2025 survey by Inside Higher Ed indicates that approximately 85% of college students now use generative AI for coursework. This type of AI, powered by large language models, generates text and content based on user prompts. The sheer scale of this usage has made it difficult for institutions to ignore, prompting the University of Alaska to seek a structured approach rather than leaving usage to individual discretion.
Data security remains a primary concern
A significant trade-off in adopting these tools is the potential risk to data integrity. Regent Christine Ressler raised questions about the university's ability to maintain security standards given the current volume of AI usage. While the university provides general guidance on its website regarding safe data practices, Shier acknowledged that the institution cannot currently track or control every individual interaction with AI services. This gap between policy and technical reality represents a key limitation in the current infrastructure.
To manage this risk, the university currently assesses specific tools against sensitive data categories, such as health records. Shier explained that this process involves determining which platforms are safe for certain types of information and which are not. This guidance is available today, but it is an ongoing effort as new tools emerge and the nature of AI applications evolves. The policy aims to formalize these assessments to ensure consistent protection across all departments.
Feedback process is still incomplete
The draft policy was developed over the summer, a period when many faculty and students were not engaged in the academic cycle. Shier admitted that the university did not have sufficient opportunity to gather input from these groups before presenting the document to the Regents. Recognizing this gap, leadership plans to conduct listening sessions and online surveys this fall to collect broader feedback. These dates have not yet been scheduled, leaving the timeline for public input uncertain.
According to GN technics/ai (en-US), the university intends to submit a finalized draft for approval at the November regents meeting. This process highlights the challenge of regulating fast-moving technology in an academic environment. While the policy aims to bring clarity and security, it also introduces bureaucratic hurdles that may slow down innovation. The final outcome will depend on how well the university can balance these competing needs between regulatory control and academic flexibility.
