Why AI Adoption Needs an Expedition Plan, Not Just an Announcement
why treating AI adoption as a genuine, phased change management effort works better than announcing a new tool and hoping people use it.
Part 1
Part 2
Getting Buy-In Before Setting Out: Committing the Whole Team to the Climb
why securing genuine stakeholder commitment before an AI rollout begins matters more than technical readiness alone.
Part 3
Starting With a Pilot: Basecamp Before the Summit Push
why a deliberately small, well-instrumented pilot project should come before any organization-wide AI rollout.
Part 4
Acclimatization: Why Training Can't Be Skipped
why genuine, paced training is what actually lets a workforce absorb new AI tools rather than merely being exposed to them.
Part 5
Altitude Sickness: Recognizing Genuine Resistance to Change
why distinguishing real resistance to AI adoption from ordinary friction is the first step in actually addressing it.
Part 6
Early Adopters as Lead Climbers: Who Goes First and Why It Matters
why identifying and supporting genuine early adopters shapes how an entire organization experiences AI adoption.
Part 7
Communication Plans: Radio Checks Between Basecamps
why a deliberate, scheduled communication plan matters more than ad hoc updates during an AI rollout.
Part 8
When the Climb Stalls: Handling Setbacks Without Losing the Team
why how a setback in AI adoption gets handled matters as much as the setback itself.
Part 9
Middle Management as Expedition Leaders on the Ground
why middle managers, not just executive sponsors, determine whether an AI rollout actually succeeds day to day.
Part 10
Change Fatigue: When the Team Has Already Climbed Too Many Mountains
why change fatigue from previous initiatives can quietly sink an AI rollout before it even begins.
Part 11
Measuring Progress: Altitude Gained, Not Just Distance Covered
why the right metrics for AI adoption measure genuine altitude gained, not just activity logged.
Part 12
Bringing in Outside Guides: When to Hire Consultants and When Not To
why the decision to bring in outside change management consultants deserves the same scrutiny as any other expedition resource.
Part 13
Sustaining Adoption: Staying at the Summit, Not Just Visiting It
why lasting AI adoption requires deliberate reinforcement long after the initial rollout excitement fades.
Part 14
AI Adoption Across Departments: Different Teams, Different Routes Up
why a single, uniform AI adoption plan rarely fits every department's genuinely different needs and starting points.
Part 15
Communicating Failure Honestly: When a Route Doesn't Work
why honest, specific communication about a failed AI initiative builds more trust than a quiet, unexplained reversal.
Part 16
Incentives for Adoption: Why People Actually Keep Climbing
why the right incentives, not just training, determine whether people keep using a new AI tool over the long run.
Part 17
Change Management for Generative AI Specifically: A Different Kind of Mountain
why generative AI's unpredictable, probabilistic behavior demands change management approaches earlier software rollouts never needed.
Part 18
Change Management in Regulated Industries: Climbing With More Gear
why AI adoption in regulated industries needs extra weight built into the change management plan from the start.
Part 19
Common Change Management Failures (and Teams That Turned Back)
why most failed AI adoptions trace back to a small, recognizable set of change management mistakes.
Part 20
The Future of AI Change Management: Building Organizations That Climb Continuously
why the future of AI change management is less about reaching one summit and more about building an organization that keeps climbing.