Why AI’s biggest challenge lies beneath the model
At TechSparks 2026, Couchbase's Michael Cronin highlighted that while AI models are increasingly accessible, enterprises struggle to turn them into reliable products. The core issue is fragmentation across multiple databases and point solutions in large organizations. Industry estimates suggest 70-80% of AI development projects never reach production, with MIT research indicating 95% fail to become profitable. Cronin advised companies to focus on critical use cases first rather than attempting wholesale data infrastructure overhauls, citing Tesco as an example of successful consolidation.
Key points
- Fragmented data infrastructure is the main barrier to enterprise AI adoption
- 70-80% of AI projects fail to reach production due to data layer issues
- Companies should start with critical use cases rather than fixing all systems at once
- Couchbase's platform aims to help consolidate enterprise data infrastructure
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