One strategic signal. One human prompt. One subtraction opportunity.
Signal: Planning for AI Adoption in 2026
Consumer adoption of innovation comes first. Enterprises come later, usually while insisting they’re “preparing” for the change.
We’ve seen this before:
- Video (2010s)
- Mobile (2000s)
- Internet (1990s)
- PCs (1980s)
For the 2020s, the wave is AI. People everywhere are using it. Expecting it. Depending on it. Just not yet at work.
Pew’s latest AI study shows the tipping point is here. Employees are using AI at home and wondering why their workplace feels so behind. Meanwhile, teams are locking in 2026 budgets with “AI acceleration” bullet points baked in.
The trouble is, AI is currently sitting right where adoption usually breaks: the Trust Gap.
Ev Rogers mapped how innovations spread over 60 years ago. In the 1990s, Geoff Moore showed where they stall. Today, AI faces the same stall point:
- Architects are building amazing things faster than ever
- Catalysts are piloting at speed and evangelizing
- Integrators are waiting on workflows that actually work in their hands
- Conformers need policies and proof before they’ll join in
- Legacy Loyalists are holding back and digging in
Strategic (Human) Prompt
You probably have each of these in your org today. Map them.
Now ask yourself: how do our Catalysts build trust with Integrators?
Strategic Subtraction: Integrators or Bust
Proof of Concept is only useful for Architects and Catalysts. Everyone else doesn’t care that something could work. They care that it does work.
Integrators care about what they can integrate into their existing workflow. They’ll do the work to integrate only what they can depend on.
Of all the AI pilots so far, which have the most potential appeal to the Integrators?
Leadership funds the pilots. Integrators decide if AI actually sticks. Refocus projects to win them over — or watch implementations stall.
Analogy: Freeway Onramp
AI transformation is like an onramp to the freeway. If it’s short, crooked, or missing guardrails, cars might lurch onto the road — but pileups follow at freeway speeds.
The faster the freeway, the longer and smoother the onramps need to be. Cars need time, stability, and visibility to reach speed before merging in. The same is true for AI: speed at scale requires room for smooth, safe acceleration.
Closing
AI adoption isn’t waiting for anyone. Employees are already ahead. Budgets are being set. The Trust Gap is upon us.
Integrators hold the keys to real implementation. Win them, and AI can pay off. Lose them, and you’re stuck at pilot forever.