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Go Slow to Go Fast: Navigating AI in Higher Education's Shared Governance
In higher education, university leaders face a far more decentralized landscape than their primary education counterparts when developing artificial intelligence guidelines. While a school district superintendent can push out a single guidelines package, colleges must balance the perspectives of department chairs, faculty senates, and individual professors, all while respecting academic freedom and integrity.
During a recent "EDU on Air for Higher Education" live broadcast, academic leaders gathered to discuss how colleges can transition from restrictive policies to constructive, instructional enablement. The session featured host Zac Chase, Global Lead of Scaled Programming for Google for Education, and Kristina Ishmael, a consultant and Program Manager supporting Google's policy and guidance programming, who previously served as the deputy director of the Office of Educational Technology at the U.S. Department of Education.
Shared Governance and the Decentralization Dilemma
Ishmael, who began teaching as an adjunct professor in an online master's program in 2025, noted that a top-down mandate simply does not work in academia. "In any institution a top-down mandate creates resistance," Ishmael said. "It just does. When we talk about higher education, we of course then look at academic freedom and academic integrity within like this larger institution and that is really challenging."
Instead of starting from scratch to create an entirely separate set of guidelines, Ishmael and Chase recommended auditing what is already there. "One of the ways that we've approached it in all instances is really looking at existing policies and guidelines or any sort of guidance that could then be edited and accommodating of generative AI," Ishmael said.
Chase emphasized this approach, describing it as an "audit of existing policies" to identify where to make room for AI rather than adding unnecessary layers of bureaucracy. "We so often think especially with a new technology and a new tool like this, we need to start from scratch when that is simply just not the case," Chase noted.
The Patchwork Syllabus and Student Friction
Leaving policy entirely in the hands of individual instructors has created what Ishmael called a "patchwork of policies." Citing the research of Dr. Lance Eaton, who compiled a global database of more than 200 distinct college syllabi policies, Ishmael explained that guidelines range from absolute bans to mandatory AI use.
This patchwork places an immense cognitive load on students who must navigate mismatched requirements across their schedules. "I could now conceivably have six different AI that I'm trying [to use]," Chase said, pointing out the ease with which a student could accidentally misstep. To reduce this friction, Ishmael recommended establishing co-designed, high-level institutional principles that department chairs can then interpret for their specific disciplines, such as computer science or humanities.
Addressing Equity and Intellectual Property
Another major concern for university provosts is the emergence of a two-tiered system where some students can afford paid, high-powered AI models while others rely on free tiers. To promote digital equity, Ishmael suggested viewing AI through the lens of academic libraries, which historically procure enterprise-level subscriptions to research databases to make them universally accessible to the campus community.
Chase pointed out that Google for Education helps address this equity gap while simultaneously resolving faculty concerns over data privacy and intellectual property. By enabling free Gemini access with enterprise-grade data protections built-in, universities can ensure that academic data is never used to train external models. "Turn on this free version and all of those enterprise level pieces of security and data privacy and sovereignty are embedded within that model," Chase explained. "And then you know that all of your students are having a shared experience."
Success Stories and Assignments Redesigned
Globally, collaborative efforts are yielding positive results. In Malaysia, the Ministry of Higher Education and local universities convened to co-create explicit guidelines following Google's AI Policy and Guidance Labs. In Ireland, higher education authorities have established flexible national frameworks that allow local institutional customization. Colombia has adopted an even broader systems-level approach, aligning basic education, higher education, and government agencies.
On a practical level, Chase highlighted the success of the ongoing assignment redesign cohorts within the Google Faculty Groups. Rather than banning AI, professors are actively incorporating AI as a "feature and not a bug." For example, speech communication students use Gemini as an interactive brainstorming partner to overcome blank-page anxiety, while other courses require students to critically edit and grade peer feedback drafted by an LLM.
"This is a piece that says, okay, let's bring the AI in. Let's let's be a little critical in our consumption here," Chase said. This critical evaluation is a cornerstone of the "double loop inquiry" featured in the labs, which moves the technology from "human in the loop" to "educator in the lead."
The Hook: Overcoming Policy Paralysis in Higher Ed
Are your faculty and students struggling to navigate a patchwork of conflicting AI guidelines on campus? The friction of academic misalignment can be paralyzing. Rather than waiting for a slow-moving, top-down mandate or letting a thousand isolated syllabi bloom, leaders must actively build collaborative, institutional principles.
Learn & Try: Recommended Higher Education Modules
To help faculty and administrators bridge the gap between AI potential and ethical academic implementation, explore these recommended, direct learning paths from our official Google AI Educator Series (GES) and Gemini Academy libraries:
1. Build Your Core AI Literacy Workspace Before redesigning policies, get hands-on experience with how AI can securely manage academic materials. Learn how to ingest course syllabi, lecture notes, and research papers into an organized, private workbook with Introduction to Gemini Notebook (goo.gle/ges2).
2. Transition from Banning to Leading AI in Assessments Address academic integrity by redesigning course activities. Shift from reviewing only final written outputs to grading the student's critical inquiry and step-by-step editing process. Explore how to build these frameworks with Create Process-Based Assessments (goo.gle/ges19) and design structured grading metrics with Create Rubrics for Assessments (goo.gle/ges20).
3. Streamline Higher Ed Research & Grant Administration Leverage AI as a powerful, secure collaborative thought partner for high-level administrative tasks. Learn to safely accelerate literature reviews across diverse disciplines with Synthesize Research Findings (goo.gle/ges26) and align complex funding objectives with institutional criteria using Write Better Grants (goo.gle/ges25).
Try This Prompt: Copy and paste this prompt template into Gemini to kickstart your own syllabus alignment audit:
"Act as a university instructional designer. Review the following academic integrity syllabus policy: [Insert Syllabus Text]. Based on the double-loop inquiry framework, suggest three specific adjustments to rewrite this policy. The new policies should shift AI from a banned 'bug' to an approved 'feature,' specifying how students can responsibly use an LLM for brainstorming while keeping the human in the lead."
Reflect
How can your institution begin shifting from a mindset of compliance to a culture of active collaboration? Share your perspective in the comments below using this thinking routine:
I used to think... [Your original view on decentralized syllabi guidelines]
Now I think... [Your new perspective on shared principles and digital equity]
