"McKinsey's latest global survey says it plainly: AI use is broad, but most organizations still have not embedded it deeply enough into workflows and processes to create material enterprise-level benefits. It also finds that workflow redesign is one of the strongest contributors to meaningful business impact."
Enterprise AI failures stem from architecture rather than enthusiasm, adoption, or raw model capability. Large language models are fundamentally text-prediction systems, while companies operate through memory, context, feedback, and constraints. Progress requires shifting from tools to systems, from answers to outcomes, and from copilots to systems of action. Enterprise AI cannot be session-based; it must remember. Recent signals of value come from organizations embedding AI into processes and treating intelligence as infrastructure. A global survey reports broad AI use but insufficient workflow embedding for material enterprise benefits, and identifies workflow redesign as a strong driver of meaningful business impact. The key issue is where AI is placed, not whether it answers well.
Read at Fast Company
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