From software engineering to AI engineering: Lessons from the front lines of enterprise AI deployment
Enterprises are struggling to move generative AI from pilot to production, and the reason is rarely the model. In a wide-ranging conversation, Rajesh Sinha, Founder and Chairman of Fulcrum Digital, argues that the industry has fixated on large language models (LLMs) as the unit of value, when the real bottleneck sits elsewhere — in data architecture, security governance, orchestration, and process redesign. His firm’s experience building and deploying enterprise AI systems offers a useful, if self-interested, window into why so many organisations remain stuck at the proof-of-concept stage. Sinha himself acknowledges the firm has not yet commissioned third-party benchmarking. Still, the framework he describes — and the operational difficulties he candidly admits to — track closely with what other enterprises report when they try to operationalize AI at scale.
Sinha’s starting point is a segmentation that most enterprise AI strategies skip. He divides the “AI journey” into two domains —...
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