Define Decision Rights for AI-Assisted Work

“Human in the loop” is too vague. Leaders must define which human, at what point, with what information, and with enough authority and time to change the outcome. This decision connects to Build an AI Strategy That Starts With Business Value and Turn Company Priorities Into an AI Opportunity Portfolio, which provide the strategic direction and portfolio context. Use this four-part leadership framework Classify the AI role — Separate information retrieval, drafting, recommendation, bounded action, and autonomous action. Classify consequence — Rate customer, financial, employment, safety, legal, and reputational impact. Assign authority — Name who approves, overrides, escalates, and stops the system. Preserve evidence — Keep source material, system output, human decision, and reason when required. A practical decision example A pricing assistant may summarize approved data and propose ranges, but a named manager approves customer prices. The interface shows supporting evidence and records overrides so leadership can review recurring weaknesses. This is a hypothetical example; use your own baseline, constraints, and evidence. Evidence, governance, and responsible use Use the NIST AI Risk Management Framework to connect the initiative to governance, context, measurement, and ongoing management. The companion NIST AI RMF Playbook turns those functions into questions leaders can assign and review. The GAO AI Accountability Framework is useful for examining governance, data, performance, and monitoring across the system life cycle. Compare the plan with the OECD AI Principles, particularly transparency, robustness, accountability, and respect for people affected by the system. For generative AI, review the NIST Generative AI Profile and test representative cases using OpenAI’s evaluation guidance. Use the OWASP Top 10 for LLM Applications to discuss application threats before a model can access sensitive information or take actions. Check performance statements against the FTC’s guidance on AI claims, and review information handling with the FTC’s privacy and security resources. For a broader organizational management approach, study the ISO/IEC 42001 overview. Take this to the next leadership meeting Create a matrix with AI role, decision consequence, human authority, evidence shown, time allowed, escalation path, and audit record for each important use case. Record the owner, evidence source, decision date, and what would cause the company to stop. The goal is not to make the document look complete. The goal is to make the next decision explicit, measurable, and accountable. Continue with Choose the Right Balance Between Central Control and Team Experimentation. Use Run a Quarterly AI Portfolio Review: Keep, Fix, Scale, or Stop to revisit the decision with current evidence.