AI & Higher Education: Charting a Successful Future with Appreciative Inquiry
Appreciative Inquiry, introduced in 1987 by David Cooperrider and Suresh Srivastva at Case Western University, remains remarkably relevant today. Despite its pre-digital origins, its strengths-based approach is especially well-suited to managing the deep structural changes driven by Artificial Intelligence (AI). Appreciative Inquiry can effectively support transformation by aligning leadership priorities, accelerating prototyping and scaling, and building a shared vision—all of which are critical to successful AI integration.
The benefits of a strengths-based approach to change are especially evident in complex organizations and industries like higher education, which is in a period of significant disruption. Buffeted by funding constraints, political pressures, and rapid technological change, higher education leaders face the challenge of guiding institutions through an increasingly uncertain landscape.
AI has the potential to fundamentally reshape every facet of higher education—from admissions and curriculum design to classroom instruction and pedagogy, and student support. The effects will extend to every corner of the academic community, reaching faculty, staff, and students alike.
Successfully adapting to and integrating AI in this context requires a carefully designed strategic change framework—one that acknowledges and respects the sector’s distinct culture and complexity. Appreciative Inquiry provides a compelling model for leading such transformation, enabling institutions to move beyond resistance and deficit-thinking by focusing instead on strengths, possibilities, and shared aspirations.
In early 2025, EnSpark Consulting conducted an informal pilot survey of higher education leaders to explore their experiences with implementing AI. As an independent organization with no ties to AI vendors or service providers, our focus wasn’t on promoting specific tools or technologies. Instead, we examined the larger picture—how AI adoption intersects with the deeper, structural changes unfolding across higher education.
Survey respondents identified the following as key goals for AI efforts at their institutions:
Equipping students with workplace skills and competencies
Enhancing learning experiences
Increasing administrative efficiency
Additional goals included:
Greater accessibility for diverse learners
Increased organizational flexibility
Easier compliance with government regulations
Their single biggest concern was “Data security/privacy”. Other concerns cited:
Data bias
Equitable access for students
Data quality
Cost and budget impacts
Most respondents did not have a formal change management team focused on managing AI implementations.
These findings echo a broader shift happening across higher education. In an April 2025 webinar titled The AI Dilemma: Balancing Innovation with Academic Integrity, hosted by Grammarly, speakers noted a telling change in institutional conversations—from “Should we use AI?” to “How do we do it right?” That same sense of urgency came through clearly in our survey results. When asked, “How important is AI to your institution’s strategic planning?”, every respondent rated it as either “very important” or “extremely important” over the next two to five years.
Survey respondents did not see a clear pattern of the impact of AI. One respondent said, “There haven't been widespread cultural shifts yet. The organization is too large and diffuse.”
Aligning Leadership
One key point that the pilot survey illuminates is the need to achieve leadership alignment. When asked about the biggest obstacle to implementation of AI applications, the most common reply was “approval and/or coordination of applications across departments/schools/institution”, followed by “lack of alignment on the overall strategy.” When asked one thing they would change about the implementation of AI at their school/institution, one respondent answered “more focused leadership on AI from Academic Affairs.”
Accelerating Prototyping and Scaling
Another key element of strategic change in the AI era is adopting a rapid prototyping and scaling mentality. An April 2025 Chronicle of Higher Education article, AI Will Shake Up Higher Ed. Are Colleges Ready?, highlighted the tension between the fast pace of AI technology advances and higher education field propensity to slow change. “Higher education and the field of artificial intelligence, though, are fundamentally mismatched in a number of ways. AI and GenAI technologies are maturing rapidly, while colleges are historically slow to evolve”.
Creating sandbox environments and streamlining approval workflows can significantly reduce operational bottlenecks and enable more agile innovation. One survey respondent shared that the most surprising outcome of adopting AI was “the ability to rapidly scale curriculum revision processes upstream from faculty and SME approval.” When asked what they would change about their institution’s AI implementation, another respondent didn’t hold back: “Giving departments and offices secure instances of AI to use in our educational and operational functions—without having to go through two years of approvals.” Their comments reflect a growing call for faster, more flexible pathways to responsible AI adoption.
Building a Shared Vision
Research shows that a strong shared vision is one of the greatest predictors of innovation and success. But this vision must be truly inclusive—it should reflect the voices, concerns, and aspirations of everyone impacted by AI strategies. Respondents reported that the most unexpected result of implementing AI applications so far has been the “Level of ethical concern across the university community.”
The Right Time for Positive Impact AI Framework
Our Positive Impact AI Framework uses Appreciative Inquiry principles to uncover strengths, align teams, and drive innovation with purpose. By focusing on positive impact, this framework ensures AI initiatives generate measurable outcomes that matter: improved performance, stronger engagement, and long-term value for both people and the organization.
Colleges and universities can benefit from integrating the Positive Impact AI Framework into their AI governance efforts to:
Develop targeted business cases for AI adoption that address administrative operations, curriculum design, and pedagogical innovation
Align faculty, administrators, and students around a shared institutional vision
Surface and address concerns related to data security, workforce implications, and implementation readiness
Facilitate timely prototyping and feedback loops for curriculum design and student applications
Maximize positive outcomes while streamlining adoption and scaling
Foster a culture of innovation, adaptability, and shared ownership
Support collaboration across departments and institutions through the exchange of insights and lessons learned
Positive Impact AI Framework and Sustainable Culture Change
A strengths-based change model that is both scalable and repeatable offers an added advantage in the higher education context. It creates a common language for navigating change, bridges decentralized organizational structures, and supports long-term success in AI strategy and execution.
In a time of rapid technological evolution, higher education leaders need tools that honor institutional complexity while fostering innovation. The Positive Impact AI Framework invites institutions to lead with strengths—not fear—as they chart their AI futures.
Want to explore how the Positive Impact AI Framework can drive positive outcomes for your school? Reach out to EnSpark and start shaping your AI future today.
About the Author
Laura Gramling has the experience and expertise to help you transform your organization in an AI-driven world. Together with her talented team, she builds on the strengths of your people to help them embrace the future with confidence. Laura approaches every client engagement knowing that each person brings a unique and vital perspective — unlocking a greater collective willingness to move forward.
With over 20 years as a change, leadership, and performance consultant, Laura has guided organizations across industries including higher education, tech, and pharma. She is an expert in organizational performance, meeting design and facilitation, and navigating complex change.