Focus Feature: McKinsey’s Agentic Foray
McKinsey’s Agentic Foray: My Take on McKinsey's AI Pivot
Let me start with a confession: I read McKinsey (and BCG, etc.) interviews and stories with a mix of professional curiosity and personal interest. I’ve worked with Strategy Seven consultants in several capacities, colleagues, compatriots, gatekeepers, and precursors to implementation work. So, when I read Bob Sternfels’s recent interview about making McKinsey “better” for the AI era, I didn’t just see corporate strategy. I saw a blueprint for what’s about to happen to all of us in white-collar work. (For those of you who haven’t read it, here is the link:).
https://hbr.org/2026/01/we-want-to-make-ourselves-better
Sternfels said McKinsey is moving “to focus less on traditional consulting services and more on delivering outcomes.” In founder-speak, that’s what we call a pivot—and not a small one. It’s like a factory that built its reputation on crafting the world’s best hand tools, suddenly announcing it’s going to sell fully automated construction robots instead. The tools are still involved, but the game has completely changed.
The “Employee” is Dead. Long Live the “Human in the Loop.”
We all remember corporate roles, each had a clear division: the “thinkers” (strategy, product) and the “doers” (engineers, sales). AI is vaporizing that line. What Sternfels is really describing at McKinsey is the rise of a new hybrid professional: the human orchestrator.
Here’s what I mean. Take a few common examples. The junior analyst who used to spend 80 hours a week building financial models in Excel? That job is being automated. But the analyst who can frame the right question for an AI, interpret its bizarre but brilliant output, and weave it into a compelling narrative for a CEO? That person is now ten times more valuable. They’ve gone from being a calculator to being a conductor.
This is the part that excites me most as a builder of tech teams. The grunt work that burned people out, the data wrangling, the slide formatting, is diminishing. What’s emerging is space for more creativity, more judgment, and yes, more humanity. But there’s a catch: it requires us to value different skills. We used to promote the person who never missed a detail. Now we need to encourage the person who knows which details the AI probably got wrong.
The Consulting Melt-Up (And Why It Matters to You)
Let’s talk about the consulting industry itself, because what’s happening there is a precursor to what’s coming next in law, finance, and accounting.
The old model was simple: sell wisdom by the hour. A team of smart people flies in, studies your problem, and gives you a beautiful, “bindered” answer. Companies pay a small fortune. The model’s weakness was always implementation, the “OK, now what?” moment after they left.
AI attacks the core of that model. Why pay a team of MBAs to analyze market data for six weeks when an AI can do a first-pass analysis in six hours? You wouldn’t. So consultants are being forced up the value chain. They can’t just deliver answers; they have to provide the system that finds and implements the answers. This is Sternfels’s “outcomes” shift.
For businesses that buy these services, this is a double-edged sword:
The Good: More accountability. You’re paying for results, not just advice.
The Tricky: Deeper entanglement. When a consultant’s AI is embedded in your operations, firing them is like ripping out a vital organ.
This creates a fascinating power shift. The client gains leverage on pricing (pay-for-results!) but loses some control over the process. It’s a more mature, but riskier, partnership.
Your Career Just Got Weird (In a Good Way)
To the students and young professionals reading this: the career ladder your parents knew is gone. It’s not broken; it’s been replaced by a career jungle gym.
The straight path, analyst, manager, director, VP, assumed each role was just a bigger version of the last. That doesn’t work when the foundational tasks of each level keep being automated out from under you.
The new path will be spikier and less linear. You might be a “Prompt Engineer & Strategy Associate” one year, lead a human-AI hybrid team the next, and then take a six-month “externship” to get certified on a new regulatory AI framework. Your value won’t come from having done a thing for ten years. It will come from having successfully navigated change three times in five years.
This isn’t hypothetical. I see it in hiring. We don’t look for “5 years of experience in X.” We look for “demonstrated ability to master a hard domain in Y months.” The skill that matters most is accelerated learning.
The Unavoidable Human Question
All this tech talk brings us to the most human question of all: what are we for?
If AI handles optimization, analysis, and prediction, then the irreducible human role becomes everything else: ethics, empathy, inspiration, and navigating the unknown. Sternfels hints at this with his focus on governance and client selection. It’s not just about doing things right; it’s about doing the right things.
The consultants (and managers, and founders) who will thrive are the ones who can look at a perfectly logical, data-driven AI recommendation and say, “No. This will destroy team morale,” or “This ignores our long-term brand promise,” or “This feels wrong.”
Judgment is becoming the ultimate competitive advantage. Not the judgment that comes from having seen it all before (AI has seen more), but the judgment that comes from human experience—the kind that understands fear, trust, hope, and resilience in ways an algorithm never will.
The Bottom Line
McKinsey’s pivot is a canary in the coal mine for the professional world. It signals that the age of selling pure intellectual horsepower is over. The new age is about blending that horsepower with technology to create tangible change.
For businesses, the mandate is to stop thinking of AI as a cost-saving tool and start seeing it as a capability multiplier. For professionals, it’s time to audit your own skills: what can you do that a large language model can’t? Your ability to answer that question honestly is your new career security.
Sternfels wants to make McKinsey better. The rest of us should take that as our cue. The goal isn’t to compete with AI. It’s to become the kind of human an AI would be lucky to work with.
What’s the one task in your current job that feels most “human”? That’s likely the core of your future role. Start there.