3 Steps for Navigating Successful AI Initiatives

AI is here. Period.

Artificial intelligence (AI) is the talk of the town in higher education. Many students, staff, administrators, executives, and constituents are already using AI—leveraging tools for everything from calendar management to communication workflows. Yet despite the rising popularity and presence of AI in higher education, institution-wide AI adoption programs are relatively uncommon. Why? Most stakeholders and proponents of AI do not have a clear path forward—no strategy, no policy, and no roadmap.

Generally, sentiment toward AI in higher education is becoming more positive, at least according to a recent Jenzabar surveyof nearly two hundred institutional stakeholders, including staff, administrators, IT leaders, faculty, and cabinet members. The takeaway from the survey is clear: While people feel relatively positive about AI and want to use it, they are often unclear about the best steps forward due to lack of policies, governance structures, and knowledge.

While there is no one-size-fits-all approach to adopting AI, there is a formula institutions can follow to increase their odds of success and minimize risk: Build a foundation in trust, focus on the long run, and run pilots with AI champions.

1. Demonstrate Value and Build Trust

Transparency is important for all institutional technology investments—and AI is no exception. When it comes to AI, context is critical. According to the Jenzabar survey, doubts about accuracy surfaced among every role group, indicating that AI investments should be made in tools that can demonstrate accuracy and in processes that can improve accuracy.^Footnote1 Champions and users need to demonstrate the value of their AI investments to strengthen confidence and trust.

The survey results indicate that stakeholders should share resources, information, and the rationale for AI technology programs across campus. They should develop a library of readily available and easily understandable resources that show how AI features are leveraged in various processes or use cases. Together, these efforts can address some of the "unclear value" concerns that many would-be AI users share.

Institutions can also benefit from researching what their peers are doing and where they are succeeding, as well as whether following a similar strategy can yield similar results. Witnessing and communicating successful AI projects at other institutions can raise confidence and strengthen internal AI initiatives, possibly addressing concerns before they arise.

One such concern is human involvement. Every role group within the Jenzabar survey described human oversight as a prerequisite to securing confidence in AI.^Footnote2 This should not be an optional setting. Institutions should invest in AI tools that ensure humans stay in the loop not only to build trust internally, but to keep up with rapidly evolving compliance regulations that require human oversight whenever AI is involved in a process. As one survey respondent said, "I view AI as a positive addition to the campus experience when it is used ethically and as a supplement to human knowledge and connection, rather than a replacement for it."

Trust comes in many forms and is shaped by different perspectives. As such, institutions looking to implement campus-wide AI programs may benefit from forming cross-departmental committees that can share input regarding policy and governance. At the user conference where the survey results were originally shared, many Jenzabar clients shared that they were building cross-departmental committees to guide AI policy, tool choice, and governance.^Footnote3 Forming these types of committees is a long-standing and accepted practice for establishing policy at higher education institutions. Bringing together diverse roles, especially more reticent groups such as faculty, into a shared committee allows institutions to better understand how different departments would leverage AI. That understanding can then inform specific policies, targeted AI deployments, or broader plans that cover a range of use cases.

Institutional decision-makers can build trust with users over time by leveraging visible proof, documentation, and training. Having credibility with staff and IT departments may create conditions for broader campus adoption and less resistance.

2. Focus on Long-Term Strategy

As regulations evolve, institutions may want to implement AI infrastructure now, as retrofitting existing systems to new requirements down the road can be costly—both financially and in terms of brand trust. Additionally, an AI platform built around transparency can be more appealing to groups that evaluate technology through a governance or security lens before considering efficiency.

There is no doubt that artificial intelligence is gaining traction. While there can be barriers to AI adoption, skeptical stakeholders, and many unanswered questions, institutions can set themselves up for success by developing and communicating policies now, choosing tools carefully, building audit trails, and implementing measures that will improve trust and adoption over time.

Part of this process involves identifying and communicating approved tools or vendors, prohibited use cases, and best practices. These strategies will make the entire adoption process more coordinated and secure, allowing institutions to build on successful programs instead of retrofitting broken strategies.

"I believe AI is one of those tools that if we do not adopt and adapt, then we will be left behind," one survey respondent noted.^Footnote4

Recordkeeping is particularly important for long-term AI success. According to the Jenzabar survey, explainability was the top comfort condition named by IT teams.^Footnote5 Audit trails, specifically, are becoming mandatory in a growing number of state-level requirements, including Colorado's Consumer Protections for Artificial Intelligence Act, which prioritizes transparency, disclosures, and consumer rights when using automated technologies in consequential decisions.

Partnerships will also play a significant role in AI strategies. Colleges and universities should work with trusted partners that share transparent documentation regarding the top anxiety across every role: data usage. When asked about AI concerns in the survey, the most common responses were related to which data is used in AI tools, how that information is scoped, and where it goes.^Footnote6 Providing clear documentation and communicating successes may increase AI adoption over time.

3. Run Pilots with Champions and Communicate Frequently

The Jenzabar survey found that 80 percent of respondents plan to adopt AI tools.^Footnote7 In most instances, participants said they believe AI will save them a meaningful amount of time or improve their work overall. In the words of one respondent, "I could not get my job done efficiently without AI. It helps me manage emails, build reports, and troubleshoot problems."

However, different roles expressed slightly different perspectives. Cabinet members—the most active users of AI in the survey—said they were generally positive about the technology. The next most-active group—staff and administrators—indicated that they were the most prepared to adopt AI, recognizing that AI tools can accelerate tedious tasks and free up time to spend on other critical work. IT leaders expressed similar optimism about the potential benefits of AI but also shared concerns over governance and trust. Faculty expressed mixed views on AI, citing concerns about values, ethics, student learning, and data privacy.

Based on an analysis of the survey results, the best place to start AI initiatives is to run pilots with AI champions, likely comprising staff and administration, as they seem to be the readiest to leverage AI and shared the most specific requests about what they wanted. By adopting tools that support in-demand features such as report building, chatbots, etc., institutions may see AI advocacy and trust rates increase.

Communicating wins about successful AI projects can also go a long way toward building trust in these tools. If institutions start campus-wide initiatives by demonstrating their commitment to long-term outcomes instead of short-term gains and showcasing positive experiences with champion-led pilot programs, then overall trust and confidence in AI may improve.

The Best Way Out Is Through

AI holds promise for institutions, presenting opportunities to accelerate processes, reduce costs, eliminate bottlenecks, improve accuracy, increase the use of relevant and timely data in myriad operations, and so much more. But there is a lot of buzz about AI in higher education, leading to strong differences in opinions across campus. Regardless of how institutions move forward with AI, getting involved will take some work.

From what we've seen at Jenzabar, most institutions are willing to get into the water if they have a strategic and practical approach to AI that doesn't compromise security, ethics, or values. To get started, AI stakeholders should find champions across administration, staff, faculty, and student groups, tailoring their approach to each group's unique needs, and then scale successful efforts across the institution. Once a foundation of value and trust is established, campuses may see the pendulum swing toward adoption, allowing them to establish better policies and governance structures that keep sensitive information safe and operations running smoothly.

Thank You

Notes

1. Jenzabar, Understanding AI Readiness on Campus (forthcoming). Jump back to footnote 1 in the text.↩
2. Ibid. Jump back to footnote 2 in the text.↩
3. "2026 AI Pulse: As Optimism Grows, So Does the Need for Policy," Jenzabar (blog), June 10, 2026.Jump back to footnote 3 in the text. ↩
4. Jenzabar, Understanding AI Readiness. Jump back to footnote 4 in the text. ↩
5. Ibid. Jump back to footnote 5 in the text.↩
6. Ibid.Jump back to footnote 6 in the text. ↩
7. Ibid.Jump back to footnote 7 in the text. ↩

Chris Morgan is Associate Vice President of Innovation at Jenzabar.