The second and thoroughly updated edition of Rewired: McKinsey’s Playbook on How Leading Companies Win with Technology and AI isn’t some kind of reverie on the future. Instead, it’s a clear guide to digital and AI transformations, full of the practical details that are too often sidelined.
Its extensive focus on talent is an example of this. At the heart of every digital transformation is a talent transformation. That’s easy enough to understand. But how do you create an organization that frees up the best talent to scale impact? There are four key unlocks.
First, build the tech muscle of your business leaders. This is a lot more than just making sure the CEO is “AI literate.” It means finding, nurturing, and developing N-2 and N-3 leaders (that is, those two and three levels below the CEO) who can blend their domain expertise with data and technology and steer teams with an AI-first sensibility. Their “tech muscle” puts them at the center of your transformation. They are the visionaries who know how to put customers first. They work with domain experts and function leaders to reimagine end-to-end processes. They clear roadblocks for teams developing products and services. And when you’re ready to implement AI solutions, they will be the ones who steer the change.
Second, transform your IT talent. This is a kind of tactical surgery that has taken some pioneering companies up to three years. IT talent needs to become 70 percent in-house and 30 percent outsourced—a complete flip from where most companies are today. As Jamie Dimon at JPMorgan Chase said, “I don’t like outsourcing your heart, your soul, and your spinal cord.” Another “70–30” flip is moving from a manager-heavy structure to an IT cohort that is 70 percent engineers. A third flip is in the career pyramid. Most IT functions have doubled down on novices who can execute the grunt work in large teams. But IT teams function best when they are small and have highly competent engineers, designers, and product managers.
Third, create a workplace where tech talent feel they can learn and innovate without the encumbrance of bureaucracy and where they feel recognized for their unique technological expertise. Companies need to consider the needs of these creative talents from the first interview through to the construction of meaningful learning journeys.
Fourth, get ready for human–agentic collaboration. People will need to be upskilled so they can design, operate, and supervise complex workflows. The nature of many of their jobs will change as agents find their way onto the org chart. Managers will move from supervising tasks to orchestrating hybrid systems—guardrails, handoffs, and judgment at the edge, along with the emotional work of helping humans feel safe alongside machine colleagues. Experts will move from being the ones everyone queues for to being the ones who encode judgment—translating tacit mastery into rules, thresholds, data, and training regimes that agents can run under supervision. And domain leaders will become integrators—people who see end-to-end value flow, connect silos, and align incentives so people and agents complement rather than compete. These evolutions read less like HR taxonomy and more like power shifts.
Transforming the talent model means reshaping the organization design. Teams change shape. Squads can shrink as agent capacity grows. That’s a structural fact that demands honest workforce planning for three classes of capacity: people, agents, and (where relevant) physical automation, each with different reliability and governance profiles. None of that is “future of work” poetry. It is org design.