Is Your Organization Messing Up AI Adoption?
Paul Boag · 16 October 2026
Read the originalPaul Boag argues that companies stall their own AI adoption by buying one tool, adding long rules and leaving staff no time or safety to experiment.
Paul Boag is a user experience consultant who wrote a book on digital transformation in 2014. He argues that companies are now repeating that era's mistakes with AI. They buy one tool for every employee, give generic training and write long rules, and staff then either stop trying or use personal accounts.
- Boag describes a user experience team whose plan for an AI research repository stalled because the approved tool could not do it and a steering group had to approve another.
- He hears of staff reprimanded for using too many AI tokens weeks after being told to adopt AI.
- He recommends starting with staff who already experiment, and letting them show colleagues what works.
- He argues that personal AI accounts show where the official tools fall short and are worth studying rather than banning.
A product or design team that wants new AI tools can collect what its members already do outside the approved tools and use it as the case for change. This is an inference and is not the author's claim.
Ask staff which tasks they do with personal AI accounts, and use that list as the case for which AI tools the company approves next.
Ask the people already using AI tools to show colleagues in similar roles what works for them, before training the rest of the team.
Derived by Working Surface from the article; more in the Playbook. Source line: Shadow AI is a symptom, and a useful one, because it shows exactly where the official tools are falling short.
18 October 2026: as AI agents make code and prototypes cheap, teams are writing down which work needs a human check and which ideas have earned more effort.