Enterprise AI Struggles Mount Amid People-First Demands

The argument that successful AI transformation hinges on people and process, not merely technology, is gaining critical urgency as early enterprise AI projects stall. This perspective, articulated by former AWS leadership, frames the current moment not as a failure of AI itself, but as the predictable end of the hype-driven, technology-first phase. After a year of heavy investment in GenAI pilots with often disappointing ROI, boards are now demanding scalable, profitable applications. This shift mirrors the early days of cloud adoption, where initial tech enthusiasm gave way to the hard work of organizational change to unlock value. The strategic pivot from pure technology procurement to organizational redesign fundamentally alters the competitive landscape. Winners will be companies that treat AI as a business transformation, embedding it into core workflows and creating new operating models. This favors integrated platform providers like ServiceNow and enterprise-focused consultancies like Accenture, which guide this complex change management. The losers are internal IT departments that remain siloed technology brokers and pure-play AI model vendors whose APIs become commoditized inputs rather than end-to-end solutions. This forces a strategic recalculation for any firm selling undifferentiated model access. The forward-looking implication is a painful but necessary market correction over the next 12-18 months, creating a clear bifurcation between