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AI can’t fix a business system with broken processes
Brief published October 4, 2026 · Original source published October 2, 2026
Original reporting by Dessy Pavlova at thenextweb.com.
Automated brief. Verify important details at the original source.
What happened
A commentary piece in The Next Web, citing McKinsey figures, reports that 88% of organizations use AI but only 7% have scaled it successfully. Author Dessy Pavlova argues the gap stems from enterprises deploying AI onto fragmented, unreformed workflows rather than first redesigning those processes. The piece frames this pattern as a costly misconception: AI is being applied as a patch rather than as an accelerant on already-functional operations. The target users are enterprise teams and decision-makers who are adopting AI tools without addressing underlying operational dysfunction.
Why it matters
The 88%-to-7% scaling gap signals a structural adoption constraint that tooling alone cannot resolve. Builders and platform vendors targeting enterprise customers face a ceiling if client organizations have not standardized their workflows before integration. AI deployment on broken processes may automate inefficiencies rather than eliminate them, making the constraint a product and go-to-market concern, not just an organizational one.
What to watch
Whether enterprise AI vendors begin offering process-audit or workflow-redesign services as prerequisites to deployment, and whether the scaling rate cited by McKinsey shifts in subsequent reporting periods.