Every organization wants AI, but few have a coherent strategy. Here's a framework for moving from experiments to enterprise-scale AI.
Assess Readiness
Before AI, you need:
- Clean, accessible data
- Cloud infrastructure
- Technical talent
- Executive sponsorship
Identify Use Cases
Prioritize by:
| Factor | Weight |
|---|---|
| Business value | High |
| Technical feasibility | Medium |
| Data availability | High |
| Risk level | Medium |
Build vs. Buy
Not everything needs custom AI:
- Buy - Commodity capabilities (transcription, translation)
- Build - Competitive differentiators
- Partner - Complex solutions requiring expertise
Governance Framework
AI governance isn't optional:
- Model inventory
- Risk assessment
- Approval workflows
- Monitoring requirements
- Incident response
Change Management
Technology is the easy part. Helping people adapt to working with AI is the real challenge.