Nitesh Mirchandani is Chief Business Officer at Mindsprint, delivering AI-led modernization for enterprise operations.
Without that context, even the most advanced AI can produce outcomes that are technically correct but commercially wrong.
There is no shortage of excitement around agentic AI. Every boardroom conversation seems to include promises of autonomous agents that can negotiate with suppliers, resolve customer issues, optimize inventories or orchestrate complex workflows with minimal human intervention. There is clearly an appetite for AI, with CIOs, CPOs, CFOs and other enterprise leaders across the board actively evaluating solutions.
But amid all the excitement, one thing that concerns me is when I see many enterprise leaders asking the wrong questions. As AI advances, the leaders need to start asking more important questions like "How capable is the organization behind the AI?" instead of simply raising questions on AI capabilities.
AI does not operate in isolation, but instead within the context of our business, our processes, our customers, our regulations and our appetite for risk. Without that context, even the most advanced AI can produce outcomes that are technically correct but commercially wrong. As AI moves from generating recommendations to making decisions, success depends less on the sophistication of the model and far more on the depth of business understanding that shapes it.
