The Rewired Enterprise

CULTURE & CODE

Every few years, a business book arrives at exactly the right moment.

The second edition of Rewired: McKinsey’s Playbook on How Leading Companies Win in Tech and AI(copyright April 2026) feels like one of those books.

The original edition was already considered essential reading for leaders navigating digital transformation. But the updated edition arrives in a very different world. Since its first publication, Generative AI has exploded into the mainstream. AI agents are beginning to perform increasingly sophisticated work. Entire industries are experimenting with agentic workflows, copilots, digital twins, and autonomous systems.

 In response, McKinsey did not simply revise the book.

 They rewrote the conversation.

 The updated edition recognizes a reality that many leaders are only beginning to appreciate:

 The challenge is no longer whether organizations will adopt AI.

 The challenge is whether organizations are capable of creating value from it. 

That distinction matters. 

Because over the last two years, thousands of organizations have launched AI pilots. Employees have gained access to copilots. Executives have announced AI strategies. Entire conferences have emerged around prompts, agents, and automation.

Yet many organizations continue to struggle to generate meaningful business impact.

The reason, according to Rewired, is surprisingly simple: Technology is rarely the constraint; organizations are.

The book’s central thesis is both elegant and provocative:

Competitive advantage does not come from technology itself.

It comes from building organizational capabilities that allow an enterprise to continuously harness whatever technology comes next.

In other words, winning in the age of AI is not primarily a technology challenge.

It is an organizational challenge.

And that may be one of the most important leadership lessons of the decade. 

The Six Pillars of a Rewired Enterprise

At the heart of the book is a framework built around six mutually reinforcing capabilities that McKinsey argues separate leading organizations from everyone else.

The brilliance of the model is that it does not begin with AI.

It begins with the enterprise.

Because AI alone does not create value. It creates potential. The organizations that consistently convert potential into results are those that develop six capabilities simultaneously: a business-led roadmap, talent, operating model, technology, data, and adoption and scaling.

Think of them as the six pillars of a rewired enterprise.Remove one, and the structure weakens. Strengthen all six, and technology becomes a force multiplier.

Pillar One: A Business-Led Roadmap

One of the strongest messages throughout Rewired is that transformation must be led by the business, not by technology teams. 

That may sound obvious, yet many organizations continue to approach AI as a collection of disconnected experiments. A chatbot in one department. A pilot project in another. A handful of AI use cases sprinkled throughout the enterprise.

McKinsey argues that leaders should stop asking: “What AI use cases should we pursue?”

And start asking: “Which business domains should we reinvent?”

That shift changes everything.

LATAM Airlines learned this lesson the hard way.

Like many organizations, LATAM initially invested in digital initiatives that looked impressive but delivered limited enterprise value. New digital products were launched, but the underlying operating model, customer journeys, and technology architecture remained largely unchanged. Innovation was happening, but it was not compounding.

The turning point came when leadership reframed the challenge.

Instead of pursuing isolated projects, they focused on a single business domain: the passenger experience. They mapped the entire customer journey — from purchasing a ticket to arriving at a destination — and asked a simple but transformative question: “What would it take to put an “airline in the pocket” of every customer?”

That vision became their North Star.

Cross-functional teams were empowered to challenge decades-old assumptions. Why should passengers check in manually? Why should customer service be tied to call centers? Why should travelers be forced into company-preferred channels instead of using WhatsApp or other tools they already preferred?

The answers fundamentally changed the business.

Passengers began receiving digital boarding passes automatically upon ticket purchase. Self-service capabilities expanded dramatically across multiple channels. Digital interactions became frictionless. 

The business impact was extraordinary. LATAM recovered its investment within 18 months. Self-rebooking rates increased from approximately 10% to 95%. Call-center volume was cut by more than half. Customer satisfaction more than tripled. 

But perhaps the most important lesson was this:

The transformation succeeded because the company started with a customer problem, not a technology solution. 

Pillar Two: Talent as a Competitive Advantage

The second pillar may be the most underestimated.

Every Tech and AI transformation is fundamentally a people transformation.

Organizations often focus on platforms, algorithms, and vendors. Yet the companies highlighted in Rewiredrepeatedly demonstrate that sustainable advantage comes from talent capability.

DBS Bank offers one of the most compelling examples.

A decade ago, DBS looked like many traditional financial institutions. Technology was important, but much of the capability sat outside the organization. The bank relied heavily on external partners, while internal business leaders often lacked the technical fluency needed to drive digital innovation.

Leadership recognized this model would not survive in a world increasingly shaped by data and AI.

They made a bold decision: move from approximately 20% in-house technology talent to more than 70%.

This was not simply a recruiting strategy. It was a capability-building strategy.

DBS launched its Tech Academy to continuously upskill employees in cloud computing, machine learning, and modern software engineering. Simultaneously, it created the Data Heroes program to build technology fluency among managers, product owners, and business leaders.

The goal was not to turn bankers into programmers. The goal was to create leaders who could speak both the language of business and the language of technology.

That investment paid enormous dividends.

When Generative AI emerged, DBS was already prepared. The bank rapidly deployed DBS-GPT, AI-powered customer service assistants, and numerous internal productivity tools. By 2025, the organization was generating more than USD$1 billion in economic impact directly from AI initiatives.

The lesson is increasingly clear:

Future competitive advantage may belong to organizations with the highest density of tech-capable leaders — not merely the largest technology budgets. 

Pillar Three: An Operating Model That Outruns the Competition 

Technology does not create speed.

Operating models do.

Toyota Motor North America provides a masterclass in this principle.

When the pandemic disrupted supply chains, Toyota found itself confronting a fundamental challenge. The traditional automotive planning process could no longer keep pace with rapidly changing customer demand.

The company could have responded by implementing new forecasting software.

Instead, leadership chose to rethink the operating model itself.

Toyota recruited entrepreneurial business leaders as product owners and embedded them directly into cross-functional teams. Rather than organizing around departments, teams were organized around solving customer and supply-chain problems.

Most importantly, business leaders — not IT — owned the transformation.

The company developed machine-learning models capable of predicting demand for thousands of vehicle configurations using hundreds of market variables. It then created a digital twin capable of simulating production plans years into the future.

The results were remarkable.

Demand forecasts achieved 85% accuracy at the local market level. Inventory levels dropped from approximately 60 days to 20–25 days. Working capital requirements fell significantly. Profits increased by hundreds of millions of dollars.

Yet the technology was only part of the story.

Toyota’s true innovation was organizational.

The company transformed planning from a slow, hierarchical process into a dynamic, data-driven capability capable of continuously adapting to market conditions. 

Pillar Four and Five: Technology and Data as Enterprise Multipliers

If LATAM demonstrates the power of customer-centric transformation and Toyota illustrates operating model reinvention, Freeport-McMoRan showcases what happens when technology and data become strategic assets. 

Facing declining ore grades and mounting pressure to improve yields without major capital investments, Freeport chose a different path.

Rather than building new mines, they sought to extract more value from existing ones.

The company began by applying AI to concentrator operations through a system known as TROI. The results were immediate. Copper production increased by 10% to 15% across major sites, generating approximately 200 million additional pounds of copper annually.

But leadership quickly recognized a far larger opportunity. 

Their attention turned to “Leaching” — a complex process that can take up to 300 days and is influenced by countless variables including weather, geology, and chemical interactions.

To tackle this challenge, Freeport created HELENA, an AI-powered digital twin capable of predicting copper recovery and recommending optimal leaching strategies.

The journey revealed a familiar truth: before AI could create value, data foundations had to be rebuilt. Sensors required recalibration. Data standards had to be established. Collection methods needed modernization.

Only then could the AI generate meaningful insights.

What happened next was extraordinary.

HELENA helped identify billions of pounds of copper trapped in decades-old stockpiles previously considered unrecoverable. The company effectively discovered value hidden inside assets it already owned.

That may be one of the most powerful lessons in the book:

AI is not merely helping organizations work faster.

Increasingly, it is helping them see opportunities that were invisible before.

Pillar Six: Adoption and Scaling

The final pillar is where most transformations succeed —or fail.

Technology creates potential. But adoption creates value.

Again, Toyota offers a powerful example.

 Leadership understood that sophisticated AI models would fail if planners and operators did not trust them. Instead of imposing solutions from above, Toyota embedded respected sales and manufacturing experts directly into development teams. These subject matter experts became translators between algorithms and frontline employees. They helped shape the tools, validate outputs, challenge assumptions, and build confidence across the organization.

At the same time, Toyota launched a massive reskilling effort affecting approximately 60% of its workforce.Employees who once spent their days manually updating spreadsheets learned how to analyze trends, evaluate scenarios, and guide AI-driven decision-making.

The result was not simply technology adoption. It was workforce transformation. 

This pattern appears repeatedly throughout all four case studies.

LATAM designed around customer behavior.

Freeport designed around operator trust.

Toyota designed around workforce confidence.

DBS designed governance and explainability directly into its AI platforms.

Each organization recognized the same truth:

Technology implementation is an engineering challenge.

Technology adoption is a leadership challenge.

And in the AI era, leadership may be the ultimate differentiator.

The Leadership Imperative: Becoming a Forever Transformer

Perhaps the most profound insight in the new edition of Rewired appears almost in passing. McKinsey suggests that today’s leaders will likely spend the rest of their careers rewiring their organizations.

That statement deserves reflection.

For most of modern business history, transformation was episodic. Organizations underwent a merger, implemented a new system, restructured a function, or launched a strategic initiative. Then stability returned.

AI may be changing that reality.

The future appears less like a series of transformations and more like a permanent state of transformation.

Which means the role of leadership is evolving. Leaders must become architects rather than administrators.Capability builders rather than project sponsors.Orchestrators rather than controllers.

They must learn to lead organizations where humans and intelligent systems continuously work together, adapt together, and create value together.

In many ways, this is the deepest lesson running through all four case studies:

LATAM, Toyota, Freeport-McMoRan, and DBS did not win because they adopted AI.

They won because they rewired themselves so AI could succeed.

And that may ultimately be the defining challenge for every organization entering the next decade.

The question is no longer whether your company will use AI.

The question is whether your company is becoming the kind of organization that can continuously create value from it.

Because in the age of AI, the winners may not be those with the smartest technology.

They may be those that become the most REWIRED.

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