When Amazon Web Services (AWS) partnered with Rehrig Pacific Company for a recent hackathon, I had the privilege of joining leaders from across the organization to explore how AI can act not just as a tool, but as a thought partner.
At first glance, the day’s agenda seemed highly technical: hands-on sessions setting up infrastructure, making queries and creating agents within a new AWS application. But beneath the commands and code, a deeper insight emerged: Technology may be evolving faster than our capacity to think about it strategically.
The Maturity Gap Between Technology and Thinking
One of the most striking realizations from one of the participants in the session was this: The maturity of thinking among problem solvers is not yet ready for the maturity of the technology they’re being asked to adopt.
For boards and executives, this gap represents both a risk and a responsibility. It’s no longer sufficient to approve AI investments or demand dashboards of data. Boards must ensure organizations are prepared to transition from simply managing information to cultivating insight and, ultimately, applying wisdom.
That shift requires a phased, system-of-systems approach to change management, one that moves the enterprise from:
• Information management to knowledge acquisition.
• Knowledge acquisition to insight cultivation.
• Insight cultivation to judgment determination.
• Judgment determination to wisdom application.
Guiding the Human Side of AI Integration
To navigate this transition, boards should be attuned to three constants in the age of agentic AI:
- Technology will augment human capabilities. Competitive relevance now depends on embracing AI as a strategic ally, not a threat.
- Quality data will be paramount. Decisions of consequence must be rooted in reliable, ethical and unbiased data.
- Teaching will transform. Organizations must invest in AI fluency to ensure employees know how to use AI effectively and responsibly.
The ADKAR model — awareness, desire, knowledge, ability and reinforcement — offers a simple yet powerful framework for ensuring that AI transformation includes both people and process. ADKAR stands for:
• Awareness of what generative AI means for each job function.
• Desire to increase curiosity and decrease consternation.
• Knowledge to train for partnership, not replacement.
• Ability to integrate AI as a collaborative thought partner.
• Reinforcement through leadership modeling and shared learning.
Lessons in Leadership and Learning
People resist change that is done to them, but they embrace change they help define and drive. That’s where board oversight plays a critical role. Part of effective leadership requires effective followership, which means directors and executives alike must model curiosity, transparency and humility in their own AI learning journeys.
As Harvard professor Amy Edmondson reminds us in The Right Kind of Wrong, progress depends on our willingness to learn through intelligent failure. Boards that adopt that mindset will lead organizations not only through technological transformation, but toward cultural maturity.
The Call to Directors
The questions before today’s boards are:
• What does the AI transition mean for corporate governance and oversight?
• How can directors influence enterprise-wide AI adoption in ways that protect people and performance?
• Where should boards anticipate real, measurable value from AI integration?
The answers will define not just the future of business, but the wisdom with which we lead it.