| Analyze tasks: Define input, judgment, action and responsibility boundaries around specific roles and work outcomes. | Produce the task map, baseline and problem classification, distinguishing suitable assistance from conditions that first need improvement. | Provide representative tasks, operating records and role confirmation, specifying completion states, quality requirements and known exceptions. | Confirm tasks worth further study, responsibilities that cannot be transferred to the system and foundational work still needed. |
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| Choose use cases: Compare value, implementation readiness, evaluation capability and consequences to allocate adjustable validation funding. | Produce the use-case portfolio, alternatives and pilot agreement, specifying budgets, owners and conditions to continue or exit. | Provide value hypotheses, dependencies and evidence gaps, explaining priorities and the choice of technology. | Approve initial validation scope and resources, commission additional evidence for unready cases and defer unsuitable directions. |
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| Design controls: Connect knowledge, tasks and authorization within explicit human–AI collaboration and approval boundaries. | Produce application architecture, knowledge specifications and a permissions matrix, with human review, exceptions and takeover practices. | Provide knowledge provenance, tool behaviors and scenario cases demonstrating that important information and actions can be checked. | Determine whether experimental design and accountability are sufficient, and proceed to controlled validation or add necessary controls. |
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| Validate with evidence: Examine content, actions, adoption and costs together, defining evidence sufficient for a limited launch. | Produce evaluation findings, failure cases and launch recommendations, distinguishing conditions met, restricted uses and required remediation. | Provide task results, key actions and expert judgments, comparing human review, rework and operating costs. | Use pre-agreed standards to launch, limit use or continue remediation, recording residual risks and conditions for later expansion. |
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| Operate at scale: Manage changes in knowledge, models, tasks and roles, feeding actual experience into renewed validation. | Establish operating ownership, change regression and value reviews, defining improvement, expansion, downgrade and exit arrangements. | Provide incident handling, repair verification, adoption differences and cost records, demonstrating evidence behind scope changes. | Decide whether to continue investment or adjust scope, restrict or pause where needed, and retain takeover and recovery arrangements. |
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