Make AI usage controlled, understandable, and usable by the people who run the work
Adoption and governance work turns a technical capability into an operating practice. It defines who may use which systems, what must be reviewed by a person, how incidents are handled, and how teams learn to work with the new process.
When this service fits
- AI tools are already in use without shared rules or oversight.
- A workflow is ready for production, but staff trust and training are incomplete.
- Security, legal, or operations leaders need auditable controls before wider rollout.
Business problems addressed
- Shadow AI use without approved data boundaries
- Unclear ownership when an AI output is wrong
- Training that explains features but not the operating process
- Controls designed after an incident rather than before launch
Deliverables
- Governance policy tailored to the workflow and data sensitivity
- Human-review and escalation standards
- Access, logging, and retention requirements
- Role-based training plan and operating playbooks
- Adoption measures and feedback loops
Engagement process
- Map risk. Identify data sensitivity, decision impact, and failure modes for the workflow.
- Define controls. Set review requirements, access rules, logging, and escalation paths.
- Prepare people. Train operators and supervisors on the process, not only the tool.
- Operate and revise. Review incidents, sampling results, and adoption friction on a defined cadence.
Expected client involvement
- Executive sponsorship for policy decisions
- Security, legal, or compliance participation as required by the use case
- Supervisors who will enforce review standards
- Time for staff training and feedback sessions
Success measurements
- Approved usage paths replace informal experimentation for the scoped workflow
- Operators know when to trust, override, or escalate
- Review and logging requirements are followed in practice
- Adoption issues are found through feedback rather than silent workarounds
Relevant use cases
Common questions
Is this only a policy document?
No. Policy is one deliverable. The engagement also covers training, review design, and the operating habits that make controls usable.
Will governance slow everything down?
Good controls remove ambiguity. They add friction only where the risk warrants it, and they free teams from inventing rules case by case.
Related services
How this engagement is run
A tool that staff do not use, or use without a review rule, is an operating problem even when the model is capable. Adoption work names who may use the system, what they may paste into it, what must be checked by a person, and how an incident is reported. Governance work writes those rules so they match the actual workflow, instead of publishing a policy nobody follows on a Tuesday afternoon.
Training in this service is practice on the real process. People learn the handoff, the exception path, and the sample they are expected to review. Leaders get a simple view of usage and corrections, not a dashboard of model scores that the operation cannot act on. If the underlying workflow is still undefined, governance will not rescue it. The prior step is an Opportunity Review or an integration design.
Put controls and adoption on the same plan as the technology
Apply for an Opportunity Review when you need to decide what to govern first, or request advisory support for an existing rollout.