Start with a decision, not a demonstration
High-value AI work begins with a specific decision or workflow that needs improvement. The institution should be able to explain who benefits, what better performance means and where human judgement remains essential.
A narrow, measurable starting point creates stronger evidence than a broad technology showcase.
Treat data as an operational asset
AI systems inherit the quality, permissions and limitations of the data around them. Institutions need ownership, lineage, quality controls and clear rules for sensitive information before deployment becomes responsible.
- Defined business outcome
- Usable and permissioned data
- Security and privacy controls
- Human oversight and escalation
- Ongoing evaluation
Govern the full lifecycle
Responsible operation requires more than a launch review. Performance, bias, misuse, drift, cost and user impact should be monitored throughout the lifecycle, with the authority to pause or change the system when evidence demands it.