The AI-Ready Enterprise.
Adoption is no longer the differentiator — almost everyone has it. Our white paper makes the case that value comes from redesigning workflows around AI, not layering it on top of broken processes, and lays out what separates the few high performers from the rest.
Key findings.
AI adoption has gone mainstream, but enterprise value has not followed it evenly. This white paper synthesizes the latest Tier-1 research on where organizations actually capture value from AI — and why a small minority pull away from a large majority that have adopted the tools but not the operating model.
Published June 14, 2026 · Updated June 19, 2026
What the research says
- 1Adoption is mainstream: 78% of organizations now use AI in at least one business function and 71% regularly use generative AI — so simply having AI is no longer a competitive edge (McKinsey, The State of AI 2025).
- 2Value comes from workflow redesign: of all the changes linked to gen-AI success, fundamentally redesigning workflows correlates most strongly with bottom-line impact.
- 3Yet almost no one does it: only about 21% of organizations using gen AI have redesigned even some workflows — the rest layer AI on top of processes that were never built for it.
- 4The high performers are a small minority: roughly 6% of organizations attribute 5% or more of their EBIT to AI use, and they are disproportionately the ones redesigning how work flows.
- 5The takeaway for operators: being AI-ready is an operating-model problem, not a tooling problem — connect the systems, fix the process, then apply AI to the redesigned workflow. That sequence is the StreamlineLabs thesis.
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