In March 2026, McKinsey released the second edition of Rewired: The McKinsey Playbook on How Leading Companies Win with Technology and AI. Co-authored by QuantumBlack leaders and McKinsey AI veterans, it’s an expanded guide built on six enterprise capabilities: C-suite roadmapping, talent building, agile operating models, distributed tech platforms, embedded data, and disciplined scaling and adoption.
The book offers fresh analysis on agentic workflows, the new economics of technology and AI transformation, and industrialising AI safely at scale. If you are leading digital or AI change in a Benelux enterprise — especially in revenue-critical stacks like Adobe Marketo Engage, Salesforce, or Microsoft Dynamics — this is relevant executive reading.
But McKinsey’s playbook, like most strategic frameworks in this space, concentrates on the how of transformation. The question it does not fully answer is: where does durable economic value actually accumulate?
“The organisations capturing AI value in 2026 are not the ones with the most advanced AI tools. They are the ones with the most governed foundations underneath those tools.”
Where the Rewired playbook is strong
McKinsey’s six-capability framework is grounded in real transformation data. The emphasis on C-suite alignment, talent, and disciplined adoption addresses the execution failures that kill most enterprise technology programmes before they produce results. The research on AI industrialisation — moving from pilots to scalable production — is particularly relevant for enterprise marketing leaders facing board pressure to show AI ROI in 2026.
The updated analysis on agentic workflows is also timely. Early enterprise deployments of autonomous agents are surfacing a consistent pattern: agents that work in sandboxed demonstrations fail in production because they cannot connect to governed data, comply with consent frameworks, or hand off reliably to execution systems. McKinsey’s emphasis on building the right technological foundation before scaling agents reflects what practitioners are observing in the field.
The question Rewired doesn’t fully answer
What the Rewired playbook does not make explicit is the structural reason why foundation investment is systematically underfunded in enterprise organisations. It describes what good looks like. It does not explain why the gap between what good looks like and what most stacks actually look like persists despite years of transformation investment.
The Value Gravity™ framework offers an explanation. Enterprise marketing stacks have three layers with fundamentally different economic properties. The AI Capability layer at the top has the highest innovation velocity and the lowest switching cost. New tools appear constantly, capability gaps between platforms close quickly, and this is where vendor marketing concentrates and where budget announcements are made.
The Commercial Foundation at the base — CRM, CDP, identity resolution, data governance, consent management — has the highest switching cost and the highest integration depth. Value accumulates here slowly, over years, through data quality work and governance decisions that are operationally intensive and rarely promotable. But every layer above depends on it.
Investment follows announcement velocity. Announcement velocity is highest at the top. Foundation work has almost no announcement velocity at all. This is the structural reason why enterprise investment concentrates upward while the foundation remains underdeveloped — not through poor decision-making, but through the structural logic of how technology budgets get approved and where executive attention lands.
What this means for enterprise leaders in 2026
Platforms are becoming AI’s orchestration spine. Enterprise systems are not being replaced by agents. They are evolving into the stable, governed layer that agents plug into. Winners will be the organisations that own the context plane — governed data and workflow infrastructure — not just the tools at the top.
Governance is shifting from cost to accelerator. With EU AI Act timelines solidifying, proactive data, identity, and policy governance is becoming a speed-and-risk advantage, particularly in regulated B2B sectors.
Ecosystem depth beats isolated features. Hybrid stacks win when orchestrated well. AI tools that cannot connect to governed data and execution layers will not deliver at enterprise scale, regardless of the capability they demonstrate in controlled environments.
McKinsey’s Rewired is worth reading. But the most important question it raises — whether the foundation beneath your AI investment is ready to support what you’re building on top of it — requires a diagnostic answer, not a strategic framework. That is the question the Gravity Scan is designed to address.
The Gravity Scan maps your marketing stack across 28 assessment areas — identifying where foundation maturity is sufficient, where it is not, and what to address before the next AI investment decision.