Enterprises Treat AI Scaling As Business System
An industry analysis warns that most AI pilots fail at the production handoff and urges organizations to treat scaling as a business-system design problem rather than a model-selection issue. It synthesizes research from Hofmann, Kreuzberger, John and others on strategy taxonomies, MLOps as a production contract, and NIST-aligned governance to recommend capability investments, evidence chains, and lifecycle controls for regulated environments.
Key Points
- 1Prioritize capability investments over isolated model pilots to avoid production handoff failures.
- 2Treat MLOps as a production contract to enforce ownership, versioning, validation, and rollback responsibilities.
- 3Build evidence chains, governance, and lifecycle processes to secure ROI and survive audits.
Scoring Rationale
Strong practical guidance and credible references drive high impact, while limited novel research reduces transformational novelty.
Sources
Public references used for this report.
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