Trends in AI Consulting

McKinsey has 40,000 employees and 25,000 AI agents. Now it is adjusting remuneration to AI. An entire industry is being disrupted by AI. And it is not the only one. Less than 2 years ago McKinsey had just 3,000 AI agents. Its CEO originally expected to reach one AI agent per employee by 2030. Now it might be months away. 𝗕𝘂𝘁 𝘄𝗵𝗮𝘁 𝗱𝗼 𝗮𝗴𝗲𝗻𝘁𝘀 𝗱𝗼 𝗶𝗻 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗶𝗻𝗴? • Consulting is full of work that is structured, repeatable, research-heavy, and analysis-driven. Exactly the type AI can replace. • Agents can help consultants search internal knowledge, summarize documents, compare markets, draft first versions, structure analyses, test hypotheses, build models, prepare client materials, and accelerate the kind of linear problem-solving that used to consume large amounts of junior consultant time. This does not mean McKinsey no longer needs consultants. It means consulting is changing. If AI can produce the first draft, the benchmark, the synthesis, the model, or the analysis, humans have to become better at the parts AI cannot reliably do: • setting the right ambition • applying judgment • challenging answers • managing the client • connecting politics with strategy • turning analysis into decisions This is much bigger than automation. Consulting firms are now redesigning the economics of consulting around a new execution layer. 𝗟𝗲𝘁’𝘀 𝘁𝗮𝗸𝗲 𝗼𝗻𝗲 𝘀𝘁𝗲𝗽 𝗯𝗮𝗰𝗸. For decades, the consulting model was built around senior partners selling the work, large teams delivering it, and clients paying for expertise, time, and execution capacity. If now AI agents are doing an increasing part of this work, clients will ask why they should pay the same way for work that now takes less human effort. That means consulting firms need to adjust their business model: from selling hours and advice to selling outcomes. Savings, cost reduction, productivity improvement, revenue increase, real transformation. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗮𝘁 𝗠𝗰𝗞𝗶𝗻𝘀𝗲𝘆 𝗶𝘀 𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝗻𝗼𝘄: Partners will receive a smaller share of profits in cash and a larger share in equity. In practice, part of the money that would have been paid out immediately stays inside the firm. 𝗪𝗵𝘆? • Because consulting cash flows may become more volatile. If more projects are tied to savings or performance improvements, the firm may only get fully paid once the client actually delivers the result. • McKinsey needs more capital inside the business: to absorb delayed payments, take more outcome risk, and invest in the technology needed to deliver work differently. Consulting companies are adopting 𝗼𝘂𝘁𝗰𝗼𝗺𝗲-𝗯𝗮𝘀𝗲𝗱 𝗽𝗿𝗶𝗰𝗶𝗻𝗴. Any industry built on expensive expert work, repeatable analysis, and billable hours will face the same pressure: to move from selling activity to selling outcomes. Opinions: my own, Graphic source: CB Insights Subscribe to my newsletter: https://lnkd.in/dkqhnxdg

AI Agents Are Reshaping Consulting — Faster Than Most Expect Enterprise demand for AI is exploding. In 2024 alone, private AI agent solutions (and the LLMs powering them) generated $10B+ in revenue — a number expected to double this year. That growth poses an uncomfortable question for consulting: 👉 What happens to the traditional model when clients can tap AI-powered expertise directly? We’re already seeing the shift: McKinsey has deployed 12,000+ AI agents internally, enabling leaner project teams. Accenture announced a new “reinvention services” unit to help clients rebuild operations with AI. Since 2023, top firms have executed 100+ AI agent-related partnerships, acquisitions, and investments (CB Insights). The pattern is clear: advisory alone won’t cut it. The firms that move from slides to systems — that can build, orchestrate, and scale AI agents — will lead the next era of the industry. From my conversations with senior AI and data leaders, four imperatives stand out: 1️⃣ Orchestrate the fragmented AI agent stack. 2️⃣ Unlock proprietary data as fuel for intelligent agents. 3️⃣ Turn services into scalable AI products. 4️⃣ Build the human–AI workforce. The graph shows snapshot of the partnerships already in motion. This is just the beginning — but the window to act is short.. The future of consulting won’t be billed by the hour — it will be built by the agent.

Many people are talking about the Bloomberg story on former McKinsey, BCG, and Bain consultants training AI models to automate parts of the strategy consulting work (The link to the article is in the comments). Some see this as the beginning of the end for the consulting industry. It is not. It is the end of one model of consulting and the emergence of another. For decades, the consulting value chain was built on analysis: gather data, benchmark competitors, synthesize findings, deliver a deck. Today, AI can perform much of this faster, cheaper, and at scale. If consulting was only about analysis, then yes, AI would replace it. But strategy was never just analysis. The real work has always been about judgment, interpretation, decision-making, alignment, mobilization, execution, and building strategic capability inside the organization. This is the shift I wrote about in "Strategy Consulting Reinvented: A New Partnership Model" (The link to my article is in the first comment) - AI is commoditizing data and insights - The differentiator is now the ability to help organizations think strategically - Clients no longer want answers delivered to them - They want capacity built with them The future of strategy consulting will be defined by: (1) Partnership, not prescription Strategy is co-created, not handed over. (2) Contextual intelligence, not generic best practices What works in Silicon Valley does not automatically work every where else. (3) Capability building, not dependency The goal is to leave behind stronger leaders and stronger strategic muscles. (4) Continuous strategy, not episodic projects Strategy becomes an ongoing system of sensing, learning, and adjusting. So yes, AI will replace a certain kind of consulting. The kind that equates thinking with slide production. The kind that confuses frameworks with judgment. The kind that treats strategy as analysis rather than synthesis and leadership. But the consulting firms and advisors who will shape the next decade are those who help organizations build strategic capability: the ability to embrace complexity, navigate uncertainty, resolve ambiguity, explore futures, make trade-offs, act with agency, and learn continuously. The question is no longer: Can we get the analysis? The question is: Can we think strategically, together, in a world where the answer keeps moving and generates more questions? The future of strategy will belong to those who learn faster, adapt faster, and co-create the path forward. #Strategy #Consulting #Leadership #CapabilityBuilding #StrategicThinking

At the weekend, the The Wall Street Journal published a feature on McKinsey & Company’s AI transformation, presenting the firm’s adoption of new tools as bold and forward-thinking. But look more closely, and the picture is far more defensive than disruptive. The article highlights McKinsey’s deployment of 12,000 AI agents and a move to outcomes-based pricing, now covering around 25% of its work. Framed as innovation, this reads more like a late-stage response to structural pressure: a quiet pivot away from the old playbook of long, people-heavy engagements. What the article doesn’t contextualize is how fundamentally the Consulting model is being rewritten. Graduate hiring is collapsing as delivery teams become leaner and AI-fluent. Modular teams built around productised IP, outcome-based pricing, and nearshore hubs are replacing the traditional pyramid. Many of the challenger firms we’ve benchmarked are much further ahead, already embedding sector-specific AI solutions into their core offerings and building recurring revenue streams from subscriptions and managed services. The real transformation is happening not in how firms decorate the old model with AI tools, but in how they replace it. That means every manager leading blended teams of humans and machines. It means turning proprietary tools into licensable products. It means capturing and recycling internal knowledge to create an “insight flywheel” that scales without adding headcount. It’s not about bots that write in your tone of voice, it’s about whether your firm can deliver faster, more repeatable outcomes without relying on brute force. McKinsey has brand strength and institutional capital, no question. But the Consulting firms winning in this new era aren’t just experimenting with AI, they’re building businesses around it. The real question now isn’t whether AI will reshape consulting, that’s already underway. It’s who will have the conviction to redesign their operating model fast enough to lead the next era.

There’s been a lot of chatter in the press lately: Is AI going to replace consultants? Is this the end of the industry as we know it? Are consultants adding value in the age of AI? I feel compelled to respond. 🙂 The reality looks very different for those inside the industry. Rather than displacing consulting, AI is reshaping it—creating a moment of enormous opportunity for those prepared to meet it. AI is disrupting every sector. Leadership teams everywhere are rethinking their business models, operations, and capabilities. And that makes this a defining era for consulting—not because AI makes advice obsolete, but because sound judgment, real partnership, and hands-on problem-solving have never mattered more. Yes, AI is rapidly transforming core activities like research, analysis, and content creation. And if you're a body shop—if you're simply doing rote work, assembling slides, synthesizing obvious answers, or engaging in staff augmentation—this moment is indeed threatening. But the best consulting has never been just about those things. I’ve been on both sides of the table and have seen it my whole career. The value lies in helping clients create competitive advantage and win—by navigating complexity, making hard decisions, driving change, and delivering real financial outcomes. That takes more than tools. It takes judgment earned from experience. It takes the ability to translate technology into action. And it takes trust—built by showing up for clients in moments of real disruption. Used well, AI is a force multiplier. It elevates the work by automating the repetitive, accelerating the analysis, and freeing up capacity for what truly differentiates great consulting: creativity, problem-solving, and impact. And remember: consulting competes in two markets—the market for clients and the market for talent—and the value proposition in both has never been stronger. Even as AI changes how we work as advisors, the best firms offer the next generation of talent something unique: the opportunity to work at the frontier of technology and transformation. This next generation won’t just use AI—they’ll lead teams of humans, agents, and robots. And they’ll do it with tools and experiences that will shape their careers for decades to come. What a time to be a consultant! The learning curve has never been steeper. And for the kind of people this industry has always attracted—people who want to grow, stretch, and solve hard problems—that’s an incredibly exciting place to be. AI is changing consulting. That’s undeniable. But it’s not the end—it’s the next chapter in how we help clients create lasting advantage.

Every industry gets disrupted—but right now, consulting is on the edge of a transformation that most aren’t ready for. I’ve spent over 30 years in enterprise tech and watched wave after wave of innovation hit consulting. But artificial intelligence is different. AI isn’t just another tool or trend—it’s fundamentally changing what clients expect, how insights are delivered, and where value comes from. The hard truth is that most consultants and firms are not prepared. Today’s clients can access powerful AI analytics and strategy tools on their own—what once required a team of experts now happens in minutes, in-house. The gap is growing between what many consultants offer and what the market truly needs: hands-on AI expertise, real integration skills, and measurable business outcomes. I dive into this topic and the future of consulting in my latest article: “Why Most Consultants Are Ill-Prepared for the Coming AI Wave—And What That Means for the Future of Consulting.” In it, I explore why traditional consulting models are under threat, how client expectations have changed, and what consultants must do to stay relevant and valuable in the era of AI. If you’re an industry leader, consultant, or just interested in where AI is taking us next, I invite you to read and share your thoughts. Let’s start a real conversation about reinventing consulting for the AI age. #AI #Consulting #DigitalTransformation #ArtificialIntelligence #FutureOfWork #Leadership

OpenAI’s move into consulting highlights something crucial. AI’s biggest challenge today isn't the technology itself, it's execution. The reality is that powerful models and platforms alone rarely deliver clear, immediate value, especially in specialised verticals and complex use cases. There's a "last-mile" execution gap where deep industry knowledge, context, and thoughtful implementation determine whether AI projects succeed or stall. It's this gap that's the culprit behind so many failed AI pilots. Yet, while OpenAI and others focus primarily on large-scale enterprise deployments (often above $10m), there's enormous untapped potential at the mid-market and sub-enterprise level. Projects under $10m can deliver significant practical value without breaking budgets. AI doesn't have to be expensive to be transformative. Another issue emerging is the rapid proliferation of AI models causing what I'd call "model fatigue." I'm seeing this consistently in my conversations with executives we deal with at hedgehog lab who feel overwhelmed by the pace of change and trapped by the fear of missing out (FOMO). Navigating this fatigue is now itself becoming an essential skill, even for consultancies. Additionally, as autonomous agents increasingly embed themselves into daily workflows, they profoundly disrupt traditional operating models. If you're leading a professional services organisation and not actively rethinking your structure, capabilities, and operating frameworks in response, you're already behind. Ultimately, implementation excellence in AI won't be driven primarily by PhD-level technical skills. It will rely heavily on core consulting capabilities like navigating complex organisational structures, aligning stakeholders behind clear goals, being genuinely agile rather than simply following agile methodologies, and thoughtfully addressing the very human fears around job losses and loss of control. These are things consultancies like ours have honed over 2 decades. In other words, making AI work in the real world requires as much empathy and human understanding as it does technical expertise. Pretty exciting what's coming up in the horizon for us. #humanplusAI

AI isn’t disrupting consulting. It’s revealing what was already broken. For decades, consulting has been about frameworks, deliverables, and expertise. The model worked because problems unfolded slowly and could be managed through structured thinking. But the world that made that model useful has changed. Enterprises no longer want advice that ends with recommendations. They want solutions that deliver, adapt, and improve in real time. In our new HFS Research x IBM study of 1,000+ executives, the verdict is in: 🟣Only 13% believe traditional consulting still delivers real value. 🟣 83% say AI-powered consulting outperforms it—and adoption will triple within two years. 🟣 Human expertise still matters, but it belongs upstream—where strategy and creativity define direction, not in every delivery layer. 🟣And nearly half of consulting contracts still charge by the hour… a model just waiting to collapse. What is emerging is something very different. Consulting is being rebuilt as a continuous system of intelligence—a delivery model that looks less like a project and more like a platform. We call this Services-as-Software. In this model, outcomes are delivered through embedded AI, orchestrated workflows, and reusable agent networks. The result is not faster consulting. It is a fundamentally different kind of consulting—one that learns and scales. Phil Fersht Saurabh Gupta Joel M. Tony Filippone Divya Iyer Ashwin Venkatesan Ashish Chaturvedi Warren Lewis Matthew Candy Mohamad Ali Anthony Marshall Richard Thompson Eileen Lowry Sia Rostami Ravari Jacob Dencik

Last week, OpenAI made headlines with a bold move: launching a $10M+ AI consulting business. But this isn’t just about offering access to powerful models like GPT-4o—it’s about embedding engineers directly into client operations to drive real-world outcomes. We’ve seen tech giants take this route before, building consulting arms to help industries adopt their innovations. But the speed at which AI has evolved is truly unprecedented. Just 2–3 years ago, generative AI was a novelty. Today, it’s being deployed at scale across enterprises. For those of us in the energy sector, this feels familiar. We’ve long had access to transformative technologies—smart grids, renewables, digital twins. But the real challenge has always been adoption: integrating new tools into legacy systems, rethinking workflows, and upskilling teams. AI is now on the same path. The technology is ready. The differentiator? Deployment, integration, execution. This transformational shift will not just be led by technologists, but by those who can bridge strategy, operations, and culture. Let’s take a page from both the AI and energy playbooks—and lead the change.

The next big consulting war won’t be about who has the best AI demo. It’ll be about who can permanently lower a client’s cost base. That’s the real message buried inside Boston Consulting Group (BCG) ’s latest AI commentary. The battle is no longer just McKinsey & Company vs Deloitte vs Accenture. It’s who can prove AI actually changes the P&L. Because clients are moving past AI experimentation. Now they want: → Lower operating costs → Faster workflows → Leaner organizations → Higher margins → AI tied directly to EBIT There are 4 ways companies can create a lasting cost advantage from AI: 1. Start with proven AI applications that fund the journey Not every company needs 200 pilots. Look to procurement as an early win: → Supplier optimization → Pricing standardization → AI-assisted negotiations Potential impact: → 5%–25% savings in 3–6 months 2. Redesign workflows, not just workflows with AI attached This is where most companies fail. According to Boston Consulting Group (BCG): → 10% of value comes from algorithms → 20% from data and technology → 70% comes from process redesign That’s a brutal statistic for companies treating AI like a side project. The real advantage comes from rebuilding how work gets done. 3. Use agentic AI where it actually matters The important distinction: → Simple tasks → standard automation is enough → Highly regulated work → humans still matter → Complex operational work with manageable risk → ideal for agentic AI That’s where major cost reductions start showing up across HR, finance, IT, and customer service. 4. Track value aggressively The dirty secret of many AI programs: Productivity improves… but the savings never hit the P&L. Without hard decisions around: → Staffing → Talent reallocation → Capacity deployment → Investment priorities …the “AI gains” quietly disappear inside the organization. The bigger implication? The consulting market itself is being reshaped. The winners won’t be the firms selling the most AI pilots. They’ll be the firms that can prove: “We helped permanently improve your cost structure.” The irony: The firms still selling AI pilots may be the first ones disrupted by AI cost pressure themselves. So we should be asking who is best positioned for this shift.. strategy firms like Boston Consulting Group (BCG)/McKinsey & Company, the big 4 (Deloitte, PwC, EY, KPMG),or IT services giants like Accenture, Tata Consultancy Services, and Infosys? #AI #Consulting #DigitalTransformation #AgenticAI #Strategy