Why most Enterprise AI initiatives never scale — And what can fix it
Enterprises have no shortage of AI models. What they lack, according to Sanjoy Ghosh, Global Head of Technology, Engineering and R&D Services at HCLTech, is the engineering data foundation to run them at scale. In a wide-ranging conversation, Ghosh argues that the real barrier to enterprise AI isn’t the model — it’s a data problem hiding in plain sight, inside the walled-off world of engineering and operational systems that most enterprise AI strategies never touch.
The pilot-to-scale trap
Pilots succeed because they’re built on a single, curated dataset. Production AI has no such luxury — it has to work across an organization’s full complexity: fragmented IT systems, operational technology, engineering technology, and decades of accumulated institutional knowledge. “That is a fundamentally harder problem,” Ghosh says, “and it is the one HCLTech has invested in solving.”
HCLTech’s answer is what it calls an AI-ready intelligence layer that unifies enterprise IT,...
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