AI models are becoming increasingly accessible, but turning them into products that work reliably remains a challenge, particularly when enterprises are dealing with fragmented data infrastructure.

At TechSparks 2026, Michael Cronin, Vice President, Sales, Asia-Pacific, Japan & India, Couchbase, joined Shivani Muthanna, Senior Director – Strategic Content & Video, YourStory, for a discussion on moving AI beyond experimentation, production failures, governance challenges, customer experience, and India's growing role in AI innovation.

Over the decades, large enterprises have adopted different databases and point solutions to address specific problems. While each solved an immediate need, the result has often been a fragmented data layer, with multiple systems that struggle to work together.

Cronin sees this fragmentation as a major barrier to AI adoption. Citing industry estimates, he said 70–80% of AI development projects never reach production, while an MIT study found that 95% fail to become profitable.

Couchbase’s operational data platform is designed to address this challenge by helping enterprises consolidate their data infrastructure.

Rather than trying to fix everything at once, Cronin advised companies to start small.

“My advice to founders and enterprises that are struggling with the fragmentation of the data layer is to pick your most critical use cases first,” he said.

Cronin cited the example of Tesco, the UK retailer with a large global Capability Center (GCC) in Bengaluru. Its multiple systems were affecting customer experience, particularly during busy shopping periods such as Black Friday and weekends.

Tesco began consolidating its data layer, starting with a single instance and use case before extending the effort across its technology stack.

Source link