Agentic AI Readiness Is A Data Problem, Not An AI Problem

InnovationAgentic AI Readiness Is A Data Problem, Not An AI ProblemByVivek Ahuja,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 02, 2026, 07:00am EDTVivek Ahuja, VP-IT at rSTAR, spearheading business and IT transformation with a focus on manufacturing, energy/utilities and construction. gettyEvery enterprise technology leader I talk to wants to deploy AI agents. Autonomous systems that handle customer service, orchestrate field dispatches or manage workflows without human intervention. The pitch is irresistible: lower costs, faster resolution, happier customers.But here is what I have learned after deploying AI-powered solutions across utility and manufacturing enterprises: The reason most agentic AI pilots stall has nothing to do with the model. It has everything to do with the data underneath it.The numbers back this up. Gartner predicted that through 2025, at least 30% of generative AI projects would be abandoned after the proof-of-concept stage, citing poor data quality, inadequate risk controls and escalating costs as the primary reasons. A 2024 RAND Corporation study examining dozens of AI projects across industries arrived at the same conclusion: The top cause of failure was not model limitations but data-related issues, including a lack of clean, well-organized, integrated data.We have an industrywide blind spot. The conversation around agentic AI is dominated by model selection, prompt engineering and orchestration frameworks. These matter, but they are not the bottleneck. The real question most enterprises cannot answer: "Can your systems provide an AI agent with clean, connected, real-time data to act autonomously?"Why Agents Need More From Data Than Co-Pilots DoA co-pilot assists a human. It can tolerate ambiguity because a person is there to catch errors, fill gaps and apply judgment. An agent...