Forward-thinking leaders may seek to implement AI into their daily, high-level operations as more community members gain exposure to its upside. But aside from being an effective tool, the advent of the revolutionary technology can help institutions thrive in a changing landscape and improve their commitment to student equity, according to a new report from Complete College America.
CCA, the nonprofit advocate for equitable student college success, convened higher education leaders this past summer to engage in experimentation, embrace innovation and test the guardrails of AI. The resulting report outlines how they learned it could be implemented in a governed framework with viable checks and balances to ensure it’s used responsibly—and how to maximize its operational potential.
“The transformative power of AI in reshaping the national workforce and economy demands bold and timely action from higher education institutions,” the report reads.
A few of the leaders to have attended the meeting included Rasmus Lynnerup, the assistant vice provost of Academic Alliances at Arizona State University; Zun Tang, dean of Institutional Research at City University of New York and Steven Gentile, executive director of the Tennessee Higher Education Commission.
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In leadership and culture
If your institution is going to foster cabinet-wide buy-in to AI governance, it must appoint an “AI lead,” the preeminent source for all inquiries, questions and responsibilities, the report declares. This responsibility must be given to a specific position, not a person, to mitigate any roadblocks in personnel transitions. Institutions without the capacity to create an AI lead position should embed the role in an existing position and incorporate it into the job description.
Once the institution declares the AI lead, that individual should chair an AI governance committee or advisory board comprising students, faculty, staff, and administrators across its community to assess critical tasks. For example, they can focus on risk assessment and compliance monitoring, policy development and review and ethical oversight.
Diversity, equity and inclusion (DEI)
To ensure an institution complies with the tenets of diversity, equity and inclusion, the report suggests training AI models to identify potential biases in its institutional policies and practices. For example, you can train a large language model (LLM) tool on college catalogs and publicly available policy documents, which in turn can identify barriers to access.
You can also incorporate real-time feedback from AI to develop learning and comprehension to develop cultural competency training relevant to the students the institution serves.
Professional development
A key component of higher education leaders’ routine is continuously developing themselves professionally to keep their skills sharp and relevant. For those too busy to slog through fifty-page reports and whitepapers, leaders can share a conversation with AI on the content once the documents are uploaded.
Interacting with AI this way can work in different aspects, too. Whether drafting performance evaluations or setting goals for staff, leaders can use AI to simulate or role-play their role and observe how they’d handle it.
Institutional culture
Leaders are naturally curious about student and faculty sentiment on campus and strive to improve morale when necessary. One popular way of gauging community members is through surveys. Large language modeling tools can collect students’ and faculties’ qualitative statements and provide efficient reports on general themes and opinions, saving leaders time and reducing bias in their assessment.
Efficiency and capacity building
Finally, amid all of the multi-level decision-making and changes institutions face each year, it’s easy for institutions to fall into disorganization and redundancies. There are a few ways AI can help leaders streamline their operations and the use of their faculty’s time.
To bottle up all the complex and nuanced changes an institution experiences each year, leaders can implement a Knowledge Management System (KMS) that can serve as a one-stop-shop service for institutional memory that can track all developments.
