Ai-Adoption

AI resistance shows which part of the work system is still missing: purpose, role, skill, environment, accountability, or flow. This guide begins where diagnosis ends. If an area is red, open the relevant section and choose 1–2 actions for the next sprint. People’s positions are not personality types. The same person can be an advocate in one scenario, a productive skeptic in another, and an avoidant participant in a third. The source of resistance shows what needs to be fixed. A person’s position shows how to act. ...

AI adoption checklist for organizations AI is already in the team. The question is where you are now and what to do next. This checklist is based on real adoption work: mistakes that repeat from company to company and practices that consistently work. Before using the checklist, take the diagnostic →. It will show which zones are burning red in your own team. Four phases Phase Main question Main mistake 1. Sense-making Why are we doing this? Starting without an answer to “why” 2. Preparation Is the environment ready, and are there rules? Giving access without context 3. Launch Who is responsible, and how do we verify? No agreement on responsibility 4. Scaling Why did acceleration fail to shorten delivery? Scaling before it works in one team Phase 1. Sense-making Before anyone gets access to an AI tool. ...

AI Resistance Map A working template for a team. It helps turn AI-resistance diagnostic results into a draft AI Working Agreement. The map does not ask you to collect quotes or label people. The entry point is different: the diagnostic highlights gaps in the work system, and the map helps you understand how those gaps show up in work and which agreement the team needs to make explicit. Where to start First, take the AI Resistance Diagnostic →. Twelve questions, five minutes. The questionnaire shows where gaps have appeared in the work system. ...

Diagnostic: how your team works with AI Twelve questions, six pairs. In each pair, the first question describes a real situation. The second checks the same zone from another angle. For primary questions, Often or This is our norm is a red signal. For control questions, Not us or a weak maturity answer is usually the red signal. If the primary question is “often” and the control question is “not us,” the problem is probably there. The team may not see it yet or may not be ready to admit it. ...

Why teams resist AI Every month, one question about AI in teams: how roles change, where processes break, and what to do about it. This is The Human Loop. The first issue: why teams resist AI — and what to do about it. Inside: a map of six sources of resistance, five positions people take, an E2E-team case, the diagnostic, the AI adoption checklist, and the AI Resistance Map as a working template. ...

We went from early LLM experiments to broad use of chats and coding agents across a large engineering organization at Raiffeisenbank. This article is based on Raiffeisenbank’s experience adopting LLM tools and coding agents across roughly 500 engineers. On the adoption dashboards, everything looked healthy: people opened the tools, tried them, came back, brought examples, showed demos, and tech leads helped their teams learn. The flow metrics did not move for a long time. ...