Consulting in the Age of AI

I was halfway through a client presentation in Munich when I noticed something odd. The junior analyst on our team had pulled together a competitive landscape analysis—something that would have taken our firm three weeks just two years ago—in less than four hours. The insights weren't just faster; they were better. More nuanced. The client leaned forward, asked sharper questions, and by the end of that meeting, I realized we weren't just witnessing a productivity boost. We were watching the entire premise of consulting work shift beneath our feet.

That moment crystalized something Mark Orlic, Partner at PwC Deutschland and one of the leading voices in AI innovation, helped me understand more deeply in our recent conversation: we're not simply adding AI tools to our existing playbook. We're fundamentally reimagining what it means to advise organizations in the first place. For decades, consulting thrived on information asymmetry—we knew things clients didn't, we had frameworks they couldn't access, we brought pattern recognition from hundreds of engagements. But when AI can instantly surface patterns across millions of data points, when clients themselves can prompt their way to frameworks that took McKinsey generations to refine, the entire value proposition changes. The question isn't whether AI disrupts consulting. It's whether we're brave enough to disrupt ourselves first.

Mark's work at PwC Deutschland sits at precisely this inflection point, and what strikes me most about his approach is how it rejects the comfortable middle ground. Traditional consulting has always moved in careful, billable increments—discovery phase, analysis phase, recommendation phase, implementation phase. Each stage meticulously scoped, each deliverable a monument to process. AI obliterates this rhythm. Machine learning models don't respect our phase gates. They surface insights in week one that we used to reserve for week twelve. They flag risks we didn't know to look for and identify opportunities in data we didn't know existed. This creates profound discomfort because it disrupts not just how we work but how we justify our fees and, more fundamentally, our expertise.

The evidence of this disruption shows up in every corner of our practice. Decision-making cycles that once required extensive scenario modeling and expert judgment now happen with AI-augmented speed and precision. I've watched teams use large language models to synthesize regulatory changes across fifteen jurisdictions overnight—work that used to require a small army of associates and multiple review cycles. More significantly, I've seen AI reveal second-order consequences our conventional analysis completely missed. In one recent engagement, an AI system flagged how a client's supply chain optimization would inadvertently trigger labor law complications in three countries—a connection our human team, despite deep expertise, simply hadn't mapped. This isn't about AI being smarter. It's about AI seeing differently, scanning for patterns across domains we've artificially siloed in our own minds.

But here's what Mark helped crystallize for me, and what I think many consultancies are still missing: the disruption isn't just operational. It's existential. When clients can increasingly access their own AI-powered insights, our traditional value shifts from knowledge transfer to something more profound—call it judgment architecture. We're no longer primarily in the business of telling leaders what to do. We're in the business of helping them build the systems, culture, and capabilities to make AI-informed decisions themselves. This requires us to be transparent about our own AI usage, to teach clients how to prompt effectively, to build their internal capacity even when it threatens our recurring revenue. It's a fundamentally different relationship model, one that treats clients as collaborators in capability-building rather than recipients of our wisdom.

The implications reach beyond our own industry transformation. As consultants, we've always served as a kind of immune system for the business world—we spot threats, we transfer best practices across industries, we help organizations adapt to change before it becomes crisis. In the age of AI, that immune function becomes more critical but also more complex. We're no longer just advising on AI adoption; we're helping clients navigate the ethical minefields, the workforce transitions, the strategic risks of moving too slowly or too recklessly. I've sat in boardrooms where executives ask me whether AI will make their core business obsolete, and the honest answer is sometimes yes—but our job is to help them see that obsolescence coming early enough to reinvent themselves. That's not a consulting deliverable you can scope in advance or price per hour. It requires deep partnership, sustained engagement, and a willingness to have uncomfortable conversations about fundamental business model shifts.

What energizes me most about this transformation—and what I hear in every conversation I have with innovators like Mark—is that AI is forcing us back to what should have always been our core value: human judgment in the face of irreducible complexity. The machines can surface insights, but they can't tell a CEO which of three equally data-supported strategies aligns with their risk tolerance and organizational culture. They can't sense the unspoken dynamics in a leadership team that will determine whether transformation succeeds or fails. They can't make the call on when to override the algorithm because context demands it. This is where consulting becomes not less valuable but more essential—and more honest about what we truly offer.

The consulting firms that will thrive aren't the ones with the fanciest AI tools or the biggest data science teams. They're the ones willing to completely reimagine their engagement model, their pricing structures, their definition of expertise. They're the ones who embrace transparency about their AI usage rather than hiding it behind proprietary methodology. They're the ones who see their ultimate value not in hoarding insights but in building client capacity to generate and act on insights themselves. This requires a kind of professional courage that runs counter to everything we've been trained to protect.

The junior analyst who built that competitive analysis in four hours? She's now teaching clients how to do the same work themselves—and our relationship with those clients has never been stronger.# Consulting in the Age of AI

I was halfway through a client presentation in Munich when I noticed something odd. The junior analyst on our team had pulled together a competitive landscape analysis—something that would have taken our firm three weeks just two years ago—in less than four hours. The insights weren't just faster; they were better. More nuanced. The client leaned forward, asked sharper questions, and by the end of that meeting, I realized we weren't just witnessing a productivity boost. We were watching the entire premise of consulting work shift beneath our feet.

That moment crystalized something Mark Orlic, Partner at PwC Deutschland and one of the leading voices in AI innovation, helped me understand more deeply in our recent conversation: we're not simply adding AI tools to our existing playbook. We're fundamentally reimagining what it means to advise organizations in the first place. For decades, consulting thrived on information asymmetry—we knew things clients didn't, we had frameworks they couldn't access, we brought pattern recognition from hundreds of engagements. But when AI can instantly surface patterns across millions of data points, when clients themselves can prompt their way to frameworks that took McKinsey generations to refine, the entire value proposition changes. The question isn't whether AI disrupts consulting. It's whether we're brave enough to disrupt ourselves first.

Mark's work at PwC Deutschland sits at precisely this inflection point, and what strikes me most about his approach is how it rejects the comfortable middle ground. Traditional consulting has always moved in careful, billable increments—discovery phase, analysis phase, recommendation phase, implementation phase. Each stage meticulously scoped, each deliverable a monument to process. AI obliterates this rhythm. Machine learning models don't respect our phase gates. They surface insights in week one that we used to reserve for week twelve. They flag risks we didn't know to look for and identify opportunities in data we didn't know existed. This creates profound discomfort because it disrupts not just how we work but how we justify our fees and, more fundamentally, our expertise.

The evidence of this disruption shows up in every corner of our practice. Decision-making cycles that once required extensive scenario modeling and expert judgment now happen with AI-augmented speed and precision. I've watched teams use large language models to synthesize regulatory changes across fifteen jurisdictions overnight—work that used to require a small army of associates and multiple review cycles. More significantly, I've seen AI reveal second-order consequences our conventional analysis completely missed. In one recent engagement, an AI system flagged how a client's supply chain optimization would inadvertently trigger labor law complications in three countries—a connection our human team, despite deep expertise, simply hadn't mapped. This isn't about AI being smarter. It's about AI seeing differently, scanning for patterns across domains we've artificially siloed in our own minds.

But here's what Mark helped crystallize for me, and what I think many consultancies are still missing: the disruption isn't just operational. It's existential. When clients can increasingly access their own AI-powered insights, our traditional value shifts from knowledge transfer to something more profound—call it judgment architecture. We're no longer primarily in the business of telling leaders what to do. We're in the business of helping them build the systems, culture, and capabilities to make AI-informed decisions themselves. This requires us to be transparent about our own AI usage, to teach clients how to prompt effectively, to build their internal capacity even when it threatens our recurring revenue. It's a fundamentally different relationship model, one that treats clients as collaborators in capability-building rather than recipients of our wisdom.

The implications reach beyond our own industry transformation. As consultants, we've always served as a kind of immune system for the business world—we spot threats, we transfer best practices across industries, we help organizations adapt to change before it becomes crisis. In the age of AI, that immune function becomes more critical but also more complex. We're no longer just advising on AI adoption; we're helping clients navigate the ethical minefields, the workforce transitions, the strategic risks of moving too slowly or too recklessly. I've sat in boardrooms where executives ask me whether AI will make their core business obsolete, and the honest answer is sometimes yes—but our job is to help them see that obsolescence coming early enough to reinvent themselves. That's not a consulting deliverable you can scope in advance or price per hour. It requires deep partnership, sustained engagement, and a willingness to have uncomfortable conversations about fundamental business model shifts.

What energizes me most about this transformation—and what I hear in every conversation I have with innovators like Mark—is that AI is forcing us back to what should have always been our core value: human judgment in the face of irreducible complexity. The machines can surface insights, but they can't tell a CEO which of three equally data-supported strategies aligns with their risk tolerance and organizational culture. They can't sense the unspoken dynamics in a leadership team that will determine whether transformation succeeds or fails. They can't make the call on when to override the algorithm because context demands it. This is where consulting becomes not less valuable but more essential—and more honest about what we truly offer.

The consulting firms that will thrive aren't the ones with the fanciest AI tools or the biggest data science teams. They're the ones willing to completely reimagine their engagement model, their pricing structures, their definition of expertise. They're the ones who embrace transparency about their AI usage rather than hiding it behind proprietary methodology. They're the ones who see their ultimate value not in hoarding insights but in building client capacity to generate and act on insights themselves. This requires a kind of professional courage that runs counter to everything we've been trained to protect.

The junior analyst who built that competitive analysis in four hours? She's now teaching clients how to do the same work themselves—and our relationship with those clients has never been stronger.