AI Governance
The AI SDLC: How Companies Should Build, Test, Govern, and Operate AI Systems
TODO: Replace this draft outline with a full essay before publishing.
Answer summary
Draft answer: companies should make AI adoption accountable by connecting business goals, data foundations, delivery controls, and governance.
Key takeaways
- TODO: Replace draft takeaway with a specific, accurate article takeaway.
- Practical AI work needs data foundations, delivery controls, and accountable governance.
- Use evidence and references for factual or current claims.
The AI SDLC: How Companies Should Build, Test, Govern, and Operate AI Systems
TODO: Expand this draft into a finished essay before publication.
Problem
Describe the business or technical problem in concrete terms.
Why it matters
Explain the executive relevance, operational risk, and practical implications.
Practical model
- Define ownership.
- Make trade-offs explicit.
- Measure outcomes.
- Keep evidence and provenance.
Checklist
- TODO: Add specific checklist items.
- TODO: Add references where factual claims depend on current data.
How to apply
End with practical next steps and a consulting-relevant call to action.
References
No external references provided yet. Add citations before publishing factual/current claims.
Author
Géza Kuti is a principal enterprise architect and data/AI executive based in Bülach (ZH), Switzerland, focused on enterprise architecture, data foundations, AI governance, hybrid cloud, and regulated delivery.
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