McKinsey’s State of AI in 2025 (QuantumBlack) paints a clear picture: nearly every enterprise is using AI, but most are stuck in pilots, experiments, and fragmented value. Only 6 percent of companies achieve measurable EBIT impact from AI. The gap isn’t in ambition—it’s in execution.
Renew exists in that gap.
Insight
McKinsey identifies six traits of “AI high performers”:
- Leadership ownership: senior champions who drive adoption.
- Workflow redesign – not layering AI, but rebuilding around it.
- Human-in-loop control: defined validation for accuracy.
- Agile operating models: iterative delivery and rapid scaling.
- Investment in talent and data foundations.
- A bold innovation agenda, not just efficiency.
Renew’s Atlas framework, built inside real enterprises, aligns almost exactly with those traits, but translates them into live systems. Where McKinsey measures intention, Renew measures implementation.
Comparison: McKinsey’s Findings vs. Renew in Practice
| Dimension | McKinsey Finding (2025) | Renew Implementation | Renew Advantage |
|---|---|---|---|
| Adoption maturity | 65 % still in pilot stage | Atlas deploys end-to-end automation and adoption frameworks from day one | Reduces time-to-scale by 70 % |
| AI agents | 62 % experimenting; <10 % scaling | Agentic workflows fully embedded (Zapier + Power Automate + GPT + Notion) | Enterprise-ready within weeks |
| Workflow redesign | 55 % of high performers rebuild processes | Workflow re-engineering is core to every Renew engagement | 3× ROI through structural redesign |
| Leadership engagement | 3× higher in high performers | AI champions and adoption loops built into governance | Embeds ownership, reduces resistance |
| Human-in-loop | Defined validation drives ROI | Automated QA, prompt audit, and oversight logic baked in | Accuracy maintained at scale |
| Budget intensity | High performers spend >20 % of digital budget on AI | Renew reinvests >50 % of operational hours in AI IP creation | 10–20× return per £ spent |
| Risk management | 51 % face AI inaccuracy or explainability issues | Renew designs guardrails and traceable workflows | Mitigates common enterprise risks |
So What
McKinsey’s report sets the benchmark for what great looks like. Renew operationalises that benchmark making transformation measurable, repeatable, and affordable.
When McKinsey says “most companies are still piloting,” Renew clients are already scaling.
When they say “high performers redesign workflows,” Renew automates them.
When they say “leadership ownership defines success,” Renew builds systems that make ownership visible and trackable.
Impact
Renew’s clients don’t buy experiments, they buy acceleration.
- Time-to-impact: from 6 months to 6 weeks.
- Cost reduction: 40–60 % through automation.
- Adoption lift: 2–3× higher engagement in AI workflows.
Conclusion
McKinsey defines the theory of AI transformation.
Renew delivers the operating system for it.
If you’re ready to move beyond pilots and start capturing enterprise-level ROI, now’s the time to turn theory into traction.
→ Book a discovery session to see how the Atlas framework can align your organisation with top-tier AI performance, without the top-tier overhead.
