Do I need to be technical to run this loop?

No. The loop is designed for business leaders who can explain the problem clearly and review the answer critically. A technical partner may help with data or systems, but the business owner should make the final decision.

Can I use this with ChatGPT, Claude, or another AI assistant?

Yes. Most sessions work in ChatGPT, Claude, Gemini, Copilot, or an enterprise assistant. Use Codex or Claude Code when the session involves an editable artifact such as a document, spreadsheet, site, repository, or prompt library file. For confidential customer, employee, supplier, pricing, or employer data, use the assistant your organization allows for that material.

When is the loop finished?

It is finished when the decision, next action, owner, evidence gap, and stop condition are explicit. If those are still unclear, rerun the evidence step before adding more people or tools.

Change Resistance Review Loop | AI Work Session

Change Resistance Review Loop

By Juan Beltrán — personal website on AI and digital growth for complex B2B industries.

Why will people resist this AI change, and what should we do before launch? Use this before rollout when adoption risk may come from incentives, workload, identity, trust, status, or manager behavior. Change Resistance Review Loop Task: Why will people resist this AI change, and what should we do before launch? Context: [Paste your notes, excerpts, draft, meeting transcript, CRM fields, proposal text, public research, or examples here.] Context I should provide: - Stakeholder map - Adoption data - Manager feedback - Workflow change - Incentives - Training plan Useful setup: Paste the change, who is affected, what they must do differently, incentives, fears, workload impact, and current feedback. Why this matters: Use this before rollout when adoption risk may come from incentives, workload, identity, trust, status, or manager behavior. Business problem: AI rollouts often treat resistance as communication failure when it is really fear, incentive conflict, workload, or loss of status. Instructions: Act as an AI change adoption reviewer. Analyze the rollout context below. Map stakeholder groups, classify resistance reasons, recommend targeted interventions, and define adoption proof beyond logins or attendance. Workflow: 1. Name the behavior change: Define what people must start, stop, or do differently. 2. Map stakeholder groups: Identify who gains, loses, decides, executes, supports, and blocks. 3. Diagnose resistance type: Classify each group by awareness, ability, incentive, workload, trust, or status. 4. Choose interventions: Match each resistance type with manager action, training, workflow redesign, or incentive change. 5. Set adoption proof: Define the usage, quality, or behavior signal that proves adoption is real. Quality bar: - Use only the context in this chat. - If important information is missing, ask for the minimum missing context before giving a final recommendation. - Separate facts from assumptions. - Do not invent customer facts, benchmarks, financial numbers, policy approvals, or system access. - Keep the answer useful for Transformation Lead. Output: A targeted change plan by stakeholder group, not a generic communication plan. - BLUF recommendation or draft. - Evidence from my context. - Assumptions and missing information. - Risks, objections, or failure modes. - Recommended next action, owner, and stop condition. Evidence checklist: - Behavior change - Stakeholder group - Resistance reason - Intervention - Adoption metric - Manager owner Stopping condition: Stop when every critical stakeholder group has a named resistance reason and intervention.

Key takeaways

Why will people resist this AI change, and what should we do before launch?
A targeted change plan by stakeholder group, not a generic communication plan.
Stop when every critical stakeholder group has a named resistance reason and intervention.
Behavior change
Stakeholder group

Canonical URL: https://juanbeltran.ch/operating-loops/change-resistance-review-loop