AI Priorities and the People’s Problem
Source: AI-EDU Simplified
Author: Lance Eaton
Original source: https://aiedusimplified.substack.com/p/ai-priorities-and-the-peoples-problem
Published: 2025-11-21
Source type: essay
Private backup: the full article text is archived in the private repository at archives/articles/aiedusimplified-substack-com-ai-priorities-and-the-peoples-problem.source.md. It is not published on the public Quartz site.
Summary
Lance Eaton reports findings from an informal survey of roughly 140 higher education respondents about institutional AI priorities. The results suggest that campuses are less stuck on technical questions than on human and organizational ones: cultural change, guidance, policy, governance, confidence, and coordination. The article argues that education AI implementation has to start with trust, shared language, and human-centered change management before durable governance can take hold.
Pull quotes
Campus AI priorities are human problems
“We asked, “As institutions are looking to figure out what to prioritize around AI, what are the three main issues that your campus would benefit from learning more about?”. The three most selected responses were: cultural change, faculty and student guidance, and policy and governance. In other words, people are thinking about AI through the lens of how humans adapt to it.”
Fragmented leadership needs coordination
“Overall, the results suggest that higher ed is still in an early phase of distributed leadership with lots of people talking, experimenting, and coordinating loosely, but few institutions with an integrated, sustained strategy.”
Institutions change through people
“At the end of the day, AI doesn’t change institutions; people do.”
Big ideas
Claims
- AI adoption in schools is mostly a people-change problem
- District AI implementation needs living guidance and teacher-led redesign
Key evidence and examples
- Survey respondents identified cultural change, faculty/student guidance, and policy/governance as top campus AI learning needs.
- Leadership is distributed across task forces, IT, academic affairs, teaching centers, faculty governance, provosts, CIOs, libraries, and early adopters.
- Eaton characterizes many institutions as exploring “the elephant” without strategic coordination.
- Prosci data is cited: 43% of organizations identify the learning curve as the biggest AI adoption hurdle, and 38% cite user proficiency.
- The proposed pathway moves from leading the human side of AI, to guiding implementation and literacy, to governing AI wisely.
Education relevance
This is relevant to higher education AI strategy, leadership development, governance, faculty development, and institutional AI literacy planning.
Durability note
The human-centered change pattern is durable; the specific workshop pathway and survey snapshot should be read as 2025 higher-education context.