There's no shortage of headlines declaring that artificial intelligence is reshaping higher education. But headlines don't train faculty. They don't build governance frameworks, and they don't help a department chair figure out where AI fits into their curriculum, or whether it should.

The problem isn't interest. It's readiness.

Adoption is accelerating.

66 %

But readiness lags behind.

A partnership built around real outcomes

When a PE-backed, applied AI transformation firm was looking for a training partner to support one of their portfolio companies, they turned to Northeastern's Executive Education division.

It was a natural fit. Northeastern has long believed that meaningful learning happens through experience, not just exposure. The Executive Education team designed a program specifically for the higher education context: not a generic AI overview, but a structured, institution-wide adoption model built for faculty, academic administrators, and institutional leaders who are ready to move from curiosity to capability.

Dozens of higher education leaders completed the program; faculty, administrators, and institutional leaders who left with practical tools, a peer network, and the confidence to move AI adoption forward at their own institution.

Some really great useful takeaways from the training to support our own work streams as well as learning to incorporate for students.

Program participant

Found very useful to apply AI correctly in my classroom effectively.

Program participant

Enjoyed the interactive nature of the session as well as independent work carried out.

Program participant

Made me reflect on my own current practice and use of AI – enhancing prompts and ongoing interactive nature of tasks.

Program participant

What this AI Training program actually does

The program moves participants through interconnected modules; from AI foundations and responsible use, to hands-on prompting practice, to discipline-specific applications across academic affairs, student services, research, and administration. Each module builds on the last, so a faculty member and a finance administrator leave with shared language and compatible skills, not disconnected training experiences. Along the way, participants also develop the skills to teach students how to use AI, so the learning doesn't stop at the cohort, it spreads across the student body and departments. The program culminates in a capstone showcase where participants present implementation plans ready to activate in their own institution.

A group of four older adults gathered around a laptop and tablet in a bright classroom setting, engaged in a collaborative learning discussion.

While the structure is consistent, the program is never one-size-fits-all. Northeastern's Executive Education tailors each engagement to the partner institution's specific context, challenges, and goals; whether that means adjusting the pace, the use cases, or the governance frameworks that anchor the work. What the PE-backed, applied AI transformation firm brought to the table was a clear understanding of where their portfolio company needed to go; what Northeastern brought was the expertise to design a path that actually got them there.

What continues to set the approach apart is what happens after the program ends. Northeastern's Executive Education works with each partner institution to establish communities of practice that sustain adoption long after the cohort has completed the curriculum. These aren't add-ons. They're the cultural scaffolding that allows new capabilities to take root.

That last piece matters, and it applies whether an institution is just starting out or already mid-adoption. Scaling AI capability in a university requires more than a cohort of skilled individuals. It requires a culture that supports ongoing learning and infrastructure that holds when the program is no longer in the room. That's what this model is built to leave behind.

Why this moment calls for a different approach

Most professional development in this space follows a familiar pattern: a workshop, a certification course, a set of best practices handed down from a vendor. What's been missing is the institutional layer: the policy scaffolding, the governance infrastructure, the peer networks that make new capabilities stick.

That's the gap Northeastern's Executive Education is set out to close. And the results of this partnership suggest it's possible to do both: to build real, transferable skills and to embed them in institutional structures that last.

Higher education is at an inflection point. The question is no longer whether universities will integrate AI, most already are. The question is whether they'll do it in ways that are coherent, equitable, and built to endure. 


References 

Digital Education Council. (2025). Global AI faculty survey 2025https://www.digitaleducationcouncil.com/dec-insights/what-faculty-want-key-results-from-the-global-ai-faculty-survey-2025

Ellucian. (2026). Artificial intelligence in higher education: From widespread adoption to strategic integration (3rd annual survey report). https://www.ellucian.com/newsroom/ellucians-3rd-annual-higher-education-ai-survey-signals-shift-individual-ai-use

IREX & Development Gateway. (2026). From ambition to adoption: Insights into university AI readiness from around the worldhttps://www.irex.org/news/irex-and-development-gateway-release-higher-education-ai-readiness-research


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