Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI by Eric Lamarre, Kate Smaje, and Rodney Zemmel
Digital transformation is never finished. There will always be new technologies that allow a company to improve customer experience and lower costs. Wanting to go beyond the headlines and build a playbook on how to do that in the age of AI, I took another look at this book, based on McKinsey’s experience leading digital transformation.
Key Takeaway: Rewired offers credible frameworks for aligning transformation efforts to business value—but its much of its operating model remains locked in legacy thinking. It’s a guide for companies still learning what digital transformation means, not for those ready to test, learn, and build fast in the AI era.
Despite the promise of helping readers compete in the age of AI, the book feels like it is clearly directed at the C-Suite of companies who are still trying to grasp what digital transformation actually is. As you’d expect from a book drawing on experience with senior leadership, the most effective frameworks are around building alignment and understanding, selecting right-sized bets, and allocating the resources to succeed.
The authors also understand that teams will have to change and adjust as AI drives the need for better data, risk assessment, and compliance. What I was wishing for more is exactly how to tackle organizational design considerations — how do we help companies like financial services move functions, which were traditionally seen as a stage gate, within the agile teams themselves.
Finally, the author’s investment and delivery model still assumes large, heavy bets with up-front planning. This is partially a function of their understanding that transforming a business domain is requires a change of platforms, data, capabilities, and teams. But their heavily stage-gated waterfall process is exactly the kind of traditional planning that sinks investments in bad bets.
The Good: Alignment and Outcomes
Rewired gets one thing right — many transformation efforts aren’t tied to real business outcomes. The two frameworks that are most valuable are at the beginning:
- How to prioritize where to transform, and
- How to create the business case linking your transformation budget to measurable business impact More often than not I still encounter companies investing heavily in digital solutions without a real line of sight on how their business will be improved. More often than not the project sponsor has an intuition of driving customer value, but hadn’t made a quantified hypothesis on how that would happen.
Choosing Your Transformation Target
- Identify a few important business domains
- Prioritize on an axis based on value potential and transformation feasibility
- Value levers
- Customer experience (Stronger weighting)
- Financial benefit
- Speed to value
- Synergy across domains
- Feasibility
- Executive sponsorship
- Data and technology readiness
- Ease of adoption
- Ease of scaling
I once worked with a mid-market brand investing heavily in a composable Contentful-based design system. It was robust, expensive, and technically elegant. The promise was that internal teams could quickly spin up experiences that were on brand and rapidly go to market are reach customers quickly .
But they were shipping static marketing pages. There’s no personalization, no experimentation, no scale problem. A well-designed WordPress site would have delivered the same business value at a tenth of the cost.
What was missing was a quantified customer or commercial rationale behind the build. We all have dozens of stories in our careers — projects that have a vision of success, but not real connection on how value will accrue to the customer and the business.
Creating the Transformation Business Case
- Clearly articulate the business problem
- Customer unmet needs — User interviews and journey design
- Process pain points — Process mapping
- Align unmet needs or pain points against a specific value lever
- Core business outcomes that are driven by the transformation of the domain, such as new customers, churn, cost to serve, NPS, etc.
- For each, identify potential digital solutions that users or customers will use as part of the improved experience
- Evaluate the technology and data aspects of the proposed solution. What is the current state, and what will need to be changed
- Assess the assessments and expected benefits, with a target of a 5x return on investment. What Rewired offers is a framework for avoiding that kind of over-investment. By forcing teams to tie initiatives to value drivers and KPIs, however loosely, the business case creates avoids dead weight by connecting the project to real ROI.
Even if those KPI estimates are wrong by ±30%, the act of doing the exercise disciplines the conversation. It aligns tech with strategy. If you can’t answer the value question, don’t launch.
The Just-Ok: Expanding the Cross Functional Team
The common statistic is that 70% of a successful AI transformation is about transforming the business process.
The book says the right thing about agile pods, and presents a framework for senior leaders to estimate resource needs at each stage of the project life cycle, which can help right size a 12-18 month investment.
They also call for functions like data, risk, compliance, and even legal to “shift left”—moving closer to real-time cross-functional collaboration with delivery teams, especially as AI products demand continuous iteration and governance.
Often clients in financial services still struggle to integrate QA into agile teams, continuing to make it a separate phase for each batch of work. For one bank DXP project this failure to effectively integrate QA caused a 2x time and cost overrun on what was essentially a lift and shift of existing content.
As AI solutions require more risk and compliance assessment, to avoid similar delays teams will require tighter collaboration with a broader team of SMEs that will be essential to project success, both through guidelines — e.g. incorporating risk checklists in a definition of done — and through dedicated resources that will sit at the team level.
The authors discuss a few operating models (Digital Factory, Product & Platform, Enterprise-wide Agile), but like many books and white papers on digital transformation, the hard parts — culture and organizational design — is glossed over.
- How to shift entrenched middle management behaviours
- How to handle competing incentives between product and compliance
- How to govern with clarity across pods without falling back into functional silos
The change management section—arguably where 70% of digital transformations fail—is the thinnest part of the book.
The Ugly: Waterfall Investment Models
Despite the upfront talk of “right-sizing” efforts, where the book breaks down is in its investment and planning model, which is still built on heavy bets. Each stage gate (L1–L5) assumes:
- Heavy upfront planning and business casing
- Locked OKRs before any real-world learning
- Teams and budgets committed before prototyping
This is waterfall dressed as agile, and replicates the worst parts of SAFe. I am not totally against everything in SAFe in the enterprise context.
But there’s no mention of lean experimentation, prototype loops, or fast feedback. No guidance on testing hypotheses before assigning budgets. No acknowledgment that with AI and cloud tools, you can validate a customer problem or UX flow in hours, not months.
They define a “business domain” as the right scale to direct investment, which makes sense given the complexity of modern platforms and their interconnectedness across digital products. But they treat each domain as a full-scale build commitment—not as a series of hypotheses to be validated through small, fast, customer-facing experiments.
The book lacks any concept of portfolio thinking—of balancing large transformational bets with small, fast innovation loops. It assumes you’ll plan your way to success, rather than test and adapt before allocating serious headcount and capital.
Conclusion
For traditional enterprises that are still aligning technology investments to business value, Rewired can be a worthwhile read. It provides strong frameworks to help focus efforts, building cases, and sizing investments. These are aspects I can see myself using when building solutions with clients.
But if you already understand the need for agile teams, if you are pushing into AI-enabled workflows, or you are trying to unlock speed and experimentation, the book won’t help you move faster or smarter.
Its stage-gated investment logic reflects the constraints of legacy transformation, not the opportunities of modern, lean product delivery.
What I was really hoping for was initial thinking around how AI would drive true organizational change. But I didn’t get that here.