When I wrote The Future of Leadership in the Age of AI, just after the announcement of Generative Adversarial Networks (GAN), but way before the transformers architecture, Generative AI, and ChatGPT, my key prediction and the thesis for the book was that AI would most profoundly disrupt knowledge work and leadership roles. At the time, most conversations about AI’s future revolved around smarter robots taking over blue-collar jobs—factory workers, truck drivers, and the like. Few were considering the seismic shifts coming for the boardrooms, consulting firms, and corner offices.
But here we are. The “future” I speculated about is unfolding before our eyes with the release of ChatGPT last month; and the consulting industry—my home turf for decades—is standing at the edge of a major transformation – even if most consultants are not realizing it yet, or refusing to realize it. If my original premise holds true—that knowledge work will face the brunt of AI disruption—then professional services are set to undergo nothing short of a revolution.
This article isn’t about rehashing my book predictions; it’s about examining the reality we’re starting to see. Consulting, with its tried-and-tested model of leveraging junior consultants’ time to deliver solutions crafted under senior partners’ guidance, is ripe for disruption. What happens when AI can do the heavy lifting traditionally assigned to those junior associates? What does a consulting firm look like when the bottom of the pyramid is replaced by the AI? What will be the value provided to our clients? How will we develop the talent?
In the coming sections, I’ll explore how AI will reshape the consulting landscape, why it’s happening faster than most people anticipated, and what it means for the future of this industry. From changing client expectations to the democratization of expertise, the rules of the game are evolving—and consulting firms need to adapt (very quickly!), or risk being left behind.
This isn’t just an evolution of consulting; it’s a fundamental redefinition of what it means to provide professional services in a world where intelligence, creativity, and expertise are increasingly augmented or even fully provided by machines.
The consulting industry is no stranger to change. Over the decades, it has evolved to meet shifting market demands, technological revolutions, financial crises, trust erosion, and increasingly savvy clients. But right now, as the AI revolution starts to play out in front of our eyes, it is becoming obvious that the consulting is about to find itself at the brink of an AI-driven transformation that will feel unlike anything we’ve seen before.
For years, the consulting business model thrived on its mastery of complexity and its ability to deliver tailored solutions through privileged access to information and structured frameworks and methodologies. Large teams of analysts and associates performed assessments, churned out research, strategies, policies, and implementation plans under the guidance of senior partners. Clients paid handsomely for this expertise, trusting that consulting firms offered something unique and unattainable elsewhere.
Enter artificial intelligence.
AI, once a buzzword confined to tech conferences and academic papers, is becoming a real and practical force that will soon start reshaping industries in profound ways.
For consulting firms, AI’s promise to automate data analysis, streamline processes, and generate insights (and churn out polished PowerPoint slides) isn’t just an opportunity—it’s an existential challenge. The grind work that forms the foundation of the traditional consulting pyramid is precisely the kind of labor that AI excels at. Why pay a team of fresh MBAs to sift through data and build PowerPoint decks when AI will be able to do it faster, cheaper, and often better—if not already, then certainly within months from now?
The implications go beyond operational efficiency. AI threatens to erode the information asymmetry that has historically given consulting firms their edge. When clients can access powerful generative and predictive AI tools that provide quick, nuanced answers, the gap between what they can do themselves and what consultants offer begins to shrink.
This shift is forcing consulting firms to rethink their value proposition. It’s no longer enough to deliver frameworks or reports—clients are looking for measurable outcomes, real transformation, and senior expertise that AI can’t replicate. This isn’t just an evolution of consulting; it’s a fundamental redefinition of what it means to provide professional services in a world where intelligence, creativity, and expertise are increasingly augmented or even fully provided by machines.
As someone who’s been in the consulting trenches for decades, I’ve seen the industry navigate countless disruptions. But AI feels different. It’s not just another tool in the consultant’s toolkit; it’s a force that will be reshaping the entire playing field.
As I mentioned, in the book I anticipated that knowledge workers—consultants, analysts, managers, and yes, even senior executives—would face the brunt of AI’s impact. These were the roles reliant on processing vast amounts of information, identifying patterns, and making decisions based on structured frameworks—all things AI was rapidly getting better at.
Looking back, that prediction feels more relevant than ever.
For decades, we dreamed that AI would handle the mundane—produce goods, clean our homes, drive our cars, and free us from tedious tasks so we could focus on creativity, art, and higher pursuits. Instead, AI is now mastering the higher pursuits, and we’re still stuck cleaning our houses.
AI is going to be a transformative force in professional services. It’s not simply replacing repetitive tasks; it’s encroaching on areas traditionally seen as requiring a human touch—areas like research, strategic planning, engineering, financial modeling, and even leadership decision-making. As AI grows more adept at generating insights, simulating scenarios, and tailoring solutions, the role of human consultants will undergo a massive transformation.
The consulting industry, with its reliance on the traditional pyramid model, is a perfect case study for how these changes will be unfolding. In The Future of Leadership in the Age of AI, I highlighted the looming need for leaders to adopt new paradigms—focusing on creativity, emotional intelligence, and the ability to drive and manage change in an AI-augmented world. These qualities, once considered “soft skills,” are becoming the hardest to replace and therefore the most valuable.
Or, as I illustrated in the Working With AI, a comic that I published at same time as the book:
But here’s the catch: while many leaders may grasp this concept intellectually, few have fully embraced what it means in practice. The same could be said for consulting firms. As AI will automate the grind work traditionally done by junior consultants, it will force a reckoning for firms that have long relied on selling hours over outcomes. This is a moment where my predictions intersect directly with the realities facing the consulting industry today.
The warning signs are clear. Firms that fail to move beyond the traditional leverage model risk becoming obsolete. As I argued in the book, the key to thriving in an AI-enabled world lies in recognizing where human strengths—like creativity, empathy, and judgment—add unique value that AI cannot replicate, yet. Consulting firms will need to restructure themselves around these principles, focusing on outcome-driven engagements, capability building, and delivering senior expertise in ways that AI cannot.
If I was right and the knowledge work is the first frontier for AI disruption, consulting firms are on the front lines.
For decades, the consulting industry has relied on a business model that’s as iconic as it is profitable: the pyramid structure. At its core, this model leverages a small number of highly compensated senior leaders at the top, supported by an expansive base of junior consultants and analysts at the bottom. It’s a structure built on scalability—selling the expertise of senior partners while delivering solutions through the efforts of junior staff.
Here’s how it works in practice:
Finders, Minders, Grinders: At the top of the pyramid are the “finders,” senior partners whose primary responsibilities are business development and client relationship management. Below them are the “minders,” mid-level managers who oversee project execution, ensuring deliverables align with client expectations. Finally, at the base are the “grinders,” typically junior consultants or fresh MBAs tasked with the heavy lifting—researching, analyzing, assessing, and preparing the PowerPoint decks and Excel models that drive most consulting engagements.
The Leverage Model: The genius of the pyramid lies in its ability to scale revenue. By hiring large numbers of grinders and charging clients premium rates for their work, firms generate significant profit margins. The higher up the pyramid, the less hands-on work is required, with senior partners overseeing multiple projects while contributing minimal direct labor.
Information Asymmetry: Traditionally, consulting firms thrived on their ability to access, analyze, and synthesize information that clients couldn’t. Grinders would comb through mountains of data, applying proprietary methodologies to create insights and strategies, which partners then sold as high-value deliverables. This asymmetry in expertise and information access created the perceived value that justified the hefty fees.
For decades, this model worked brilliantly. It allowed firms to grow, expand their client bases, and create a pipeline of talent rising through the ranks. It also offered a clear career progression for consultants, with grinders aspiring to become minders and, eventually, finders.
But the cracks in this model have been forming for some time, and AI threatens to widen them into chasms.
The traditional pyramid depends heavily on the assumption that junior consultants are essential to the process. They’re the ones crunching data, building models, and preparing client-ready deliverables. Margins on their hours is what pays the partners and generate firm’s profits. But what happens when AI can do most of that grind work in seconds? And when clients realize that AI can do the same or better work?
As AI tools like generative models and predictive analytics become more sophisticated, they’re automating many of the tasks that junior consultants were hired to perform. Data analysis, scenario modeling, policy writing, and even drafting detailed strategy documents are increasingly within AI’s capabilities. This shift doesn’t just challenge the pyramid model; it fundamentally upends it.
Suddenly, the leverage that made the pyramid so profitable starts to evaporate. Clients no longer see the value in paying for a team of grinders when AI can produce similar—if not better—results faster and cheaper. And without the base of grinders, the entire pyramid begins to collapse.
In a world where AI is becoming increasingly capable, the very tasks that define the grinder’s role are rapidly being automated. AI has proven to be exceptionally good at performing the kinds of tasks that grinders have traditionally handled. Here’s how:
In the past, junior consultants would spend countless hours gathering data from various sources, cleaning it, and analyzing it to find insights. Today, AI-powered tools can automate much of this process. Machine learning algorithms can sift through massive datasets in seconds, identifying patterns, trends, and anomalies that would take a human days or even weeks to uncover.
Tools like natural language processing (NLP) can pull relevant information from unstructured data sources—think market reports, social media feeds, or financial filings—without the need for manual effort. And with real-time analytics, AI doesn’t just crunch numbers; it delivers insights dynamically, adjusting as new data becomes available.
One of the key responsibilities of junior consultants has been building detailed financial models and running scenario analyses. AI tools are not only capable of generating these models but can also simulate complex “what-if” scenarios at speeds no human could match.
For example, generative AI can instantly produce forecasts based on different variables, highlighting risks and opportunities without requiring manual input. This doesn’t just save time; it often produces more accurate and nuanced results, as AI can evaluate factors far beyond what a human might consider.
The “deck”—a hallmark of consulting—is no longer the exclusive domain of human consultants. AI-driven tools like ChatGPT and other generative models can draft professional, client-ready reports in minutes. They are getting better at it daily. From executive summaries to detailed strategy recommendations, AI will soon be able to tailor content to specific client needs, producing high-quality work that rivals (and soon exceeds) what junior consultants can deliver.
Even the visual components of presentations are being automated. Some AI models can already create charts, infographics, and dashboards that are not only aesthetically polished but also data-rich and highly customizable.
Grinders traditionally spent hours conducting research on industry trends, competitor analyses, and regulatory environments. AI has upended this dynamic. Generative AI models can produce comprehensive summaries of a given topic, pulling from vast repositories of data and presenting it in a digestible format. Or simply throw the latest laws and regulations at AI, and it will produce a summary just at the right level of detail and will highlight the most salient points.
For instance, instead of assigning a junior consultant to scour reports and write a 20-page industry analysis, firms can now use AI to generate that report almost instantly. The time savings are undeniable, but it also raises a critical question: when AI can do the research, what role does the human grinder play?
AI Capabilities Prediction
If you’re amazed by what AI like ChatGPT can achieve today, prepare to have your expectations shattered in the near future. The pace of advancement is staggering, and by the end of 2025, tools like ChatGPT are likely to outperform even seasoned fifth-year consultants with a PhD and an MBA. And that’s just the beginning. Research into self-improving AI is already underway, and once AI systems gain the ability to refine and enhance themselves, we could see capabilities evolving not year-by-year, but hour-by-hour. This could either be an exhilarating leap forward—or a daunting challenge for those unprepared to adapt.
At first glance, this level of automation seems like a massive win for consulting firms. Faster turnaround times, reduced costs, and consistent deliverables—what’s not to love? But this efficiency comes at a cost.
The traditional pyramid model depends on leveraging junior consultants to create value while charging clients a premium for their time. If AI automates the bulk of the grind work, it eliminates a major revenue stream for consulting firms. Additionally, without the need for grinders, firms lose their traditional talent pipeline. After all, grinders weren’t just doing the work—they were learning the ropes, developing skills, and rising through the ranks to eventually become mid-level managers and partners.
AI’s ability to automate grind work leaves consulting firms with a paradox: how do they maintain profitability and develop talent when their foundational model no longer works?
As the pyramid flips, a new foundation will emerge: one built on expertise rather than leverage, outcomes rather than outputs, and direct client engagement rather than hierarchical delegation.
The consulting industry’s pyramid structure has always been the cornerstone of its profitability and scalability. But as AI disrupts the foundation—automating the grinder work that underpins the model—the pyramid will undergo a dramatic inversion. The roles that once drove the business will be upended, and the consulting model will have to shift from leveraging junior consultants’ time to maximizing senior expertise and delivering measurable outcomes (my intentional highlight).
With AI automating much of the grind work, clients will no longer see value in paying for what machines can now do faster and cheaper. This shift will place senior consultants and partners in the spotlight. Their ability to deliver unique insights, strategic foresight, and creative problem-solving—skills that AI cannot replicate, yet—will have to become the core value proposition.
In this new model, clients won’t be paying for labor, and why would they when they will be able to get most of that knowledge labor for a $60 per month GenAI subscription? They will want 40-50% of a senior partner’s time, not the traditional 1% they might have gotten under the old pyramid. They will expect their senior consultants to engage deeply, build capabilities, and drive results—not just oversee teams of analysts. They will want measurable results: increased revenue, reduced costs, improved efficiency, and tangible technology transformations.
This change will require consulting firms to rethink their engagement models. It will no longer be enough to deliver strategies and recommendations. Firms will have to follow through on implementation, driving measurable change, and ensuring that the outcomes justify the investment.
AI will play a dual role here. While it will automate tasks that improve efficiency, it will also raise client expectations. Clients will increasingly view AI-powered insights as table stakes and demand consulting firms deliver value beyond what they could achieve themselves with similar tools.
As the pyramid flips, the role of mid-level consultants—the minders—also comes into question. Traditionally, they bridged the gap between senior partners and junior consultants, ensuring projects ran smoothly and deliverables met client expectations. But if AI can automate grind work and clients demand direct access to senior expertise, the middle layer risks being squeezed out. For more on this idea, see my aforementioned book.
This doesn’t mean the end of all mid-level roles, but it does mean a redefinition. Managers will need to evolve into specialists who can oversee AI systems, integrate data-driven insights into strategic discussions, and act as facilitators of value-driven transformation.
The inversion of the pyramid isn’t just a challenge—it’s a threat to the traditional consulting culture. Many senior partners, particularly in legacy firms, are deeply invested in the old model. They’ve built their careers on leveraging networks, managing teams, and scaling through junior talent. Asking them to change—by focusing more on direct client engagement and measurable outcomes—and re-learning their old areas of expertise— requires a seismic shift in mindset.
As the pyramid flips, a new foundation will emerge: one built on expertise rather than leverage, outcomes rather than outputs, and direct client engagement rather than hierarchical delegation.
This transformation won’t happen overnight, and it won’t be easy. But for firms willing to embrace the change, it represents an opportunity to redefine consulting for the AI era—moving beyond the traditional model to deliver value in ways that truly matter to clients.
Firms that resist this transformation will risk irrelevance. While senior, traditional partners may be slow to adapt, tech-savvy firms and MBB competitors are already positioning themselves to capitalize on this inversion. The firms that succeed will be those that embrace the shift, redefining their value proposition around expertise, innovation, and results.
For most of its history, consulting has thrived on its ability to access and control information that clients couldn’t easily obtain. This expertise, combined with structured methodologies, expensive subscription to industry analyst reports, expansive internal knowledge bases, re-usable assets or “accelerators”, gave consulting firms a distinct advantage. Clients relied on them not just for their analysis but for their ability to uncover insights hidden in complex datasets, industry trends, and competitive landscapes. Consulting firms were the gatekeepers of knowledge—an advantage that justified their hefty fees.
Information asymmetry worked because clients often didn’t have the resources, time, or expertise to gather and analyze the data necessary to solve complex problems.
AI is already dismantling that dynamic. And it’s just starting. With advancements in generative AI, machine learning, and natural language processing, tasks that once required entire teams of junior consultants can be done faster, cheaper, and often better by machines. The playing field is becoming more level, as clients can now access the same tools and insights that once set consulting firms apart.
For example, sophisticated AI platforms can analyze industry data, generate predictive models, and produce tailored recommendations in minutes. AI will be able to synthesize information from unstructured sources like market reports, news articles, and social media feeds. It can detect patterns and trends that might take human analysts days or even weeks to identify. Furthermore, AI tools don’t suffer from cognitive biases or fatigue; they process information consistently and with unparalleled speed, making them a powerful equalizer in decision-making.
The implications are profound. Clients who previously felt reliant on consulting firms to decode complexity will very soon start discovering that AI can handle much of the heavy lifting. This doesn’t just threaten the value proposition of traditional consulting—it shifts the balance of power. Consulting firms are no longer the sole keepers of insights; clients will gain the tools to independently navigate challenges that would have once seemed insurmountable.
This leveling of the playing field will create new pressures on consulting firms. It will no longer be enough to present data or deliver recommendations that an AI platform could easily replicate. To stay relevant, firms will have to focus on delivering value that goes beyond what machines can offer. This will mean contextualizing AI-generated insights within the unique realities of each client’s business, navigating the cultural and operational hurdles that AI alone cannot address, and fostering outcomes that AI-powered tools can enable but cannot achieve on their own.
In this new environment, consulting firms will have to reckon with the fact that their traditional gatekeeping role has diminished. The democratization of expertise through AI will demand that firms redefine their purpose, shifting from providing information to delivering transformation. The burden of proof will shift: consulting firms will have to show why their expertise and insights are worth paying for in a world where information is no longer scarce.
The end of information asymmetry isn’t just a challenge; it’s an opportunity. For consulting firms willing to adapt, this new era will allow them to redefine their value proposition. Instead of relying on exclusive access to information, they can focus on helping clients navigate complexity, implement AI solutions effectively, and build internal capabilities that create lasting impact. Firms that will embrace this shift will thrive in a landscape where information is no longer a barrier but a shared resource.
Staying relevant means not only adopting AI tools but also fundamentally rethinking how value is created and delivered together with AI.
As AI transforms the consulting landscape, it won’t just reshape how firms operate—it will also fundamentally alter what clients expect. Clients will become more sophisticated, leveraging AI tools themselves and demanding far more from their consulting partners. Clients will no longer be impressed by standard deliverables or conventional methodologies—they will expect consultants to bring something truly transformative to the table.
One major risk for consulting firms is underestimating how quickly clients will be adapting to AI. Many firms assume they can remain a step ahead, offering expertise that outpaces clients’ in-house capabilities. But this gap will narrow rapidly. Clients will not just use AI for routine tasks; they will experiment its strategic applications and cutting-edge tools and approaches. A firm that remains focused on delivering insights or frameworks that a client could replicate using ChatGPT or similar, risks being seen as redundant.
Another challenge lies in clients’ evolving perception of value. The traditional model of billing for hours or outputs—like detailed reports, assessments, and presentations—is already losing its appeal. And AI will wipe out any perception of value embedded in junior consultants’ hours. Clients will be looking for measurable outcomes: tangible improvements in efficiency, cost savings, or competitive positioning. Firms that fail to align their offerings with these expectations will struggle to justify their fees.
This shift also highlights a broader cultural risk for consulting firms. Clients are increasingly expecting partnerships rather than transactions. They will want consultants to act as enablers, integrating AI-driven insights into their operations and building internal capabilities that create long-term value. Firms that cling to outdated delivery models risk alienating these clients, who will turn to more innovative competitors capable of offering deeper collaboration and outcome-driven engagements.
Finally, there’s the reputational risk of falling behind. In an industry built on the perception of expertise and cutting-edge knowledge, failing to keep up with client expectations can damage a firm’s brand. Once seen as out of touch or overly reliant on legacy models, a consulting firm may find it difficult to regain credibility, especially in a market where nimble competitors are quick to capitalize on gaps.
The risks of falling behind client expectations are not theoretical—they are already materializing. Clients are moving quickly, and consulting firms must do the same. Staying relevant means not only adopting AI tools but also fundamentally rethinking how value is created and delivered together with AI.
For decades, consulting firms have relied on a tried-and-true formula: deliver strategies, assessments, target operating models (TOMs), and similar as core outputs of their engagements. These deliverables, often polished to perfection in PowerPoint, have long been the bread and butter of consulting work. Clients paid handsomely for them, believing they represented deep expertise, rigorous analysis, and actionable guidance.
But as AI revolutionize the way insights are generated and delivered; this model will lose its luster. Strategies, assessments, TOMs, and similar deliverables will become commodities, no longer the premium outputs they once were. Clients will be demanding more than slide decks and static plans—they will want measurable results, tangible transformations, and a clear path to implementation.
AI will erode the value of traditional consulting deliverables in several ways. First, generative AI tools will be able to produce strategy-like outputs at a fraction of the cost and time. These outputs may not yet be as nuanced as those crafted by experienced consultants, but they’re already good enough for many clients, especially when cost and speed are priorities. However, with the rapid advancement of AI, and especially when AI starts improving AI (already happening in labs), my prediction is that by the end of 2025 – in just three short years – the output of AI will be of better quality than what a PhD and MBA educated junior consultant will be able to produce.
Second, AI will introduce a level of adaptability and dynamism that static deliverables can’t match. Traditional TOMs and strategies are snapshots in time, reflecting assumptions and conditions that may quickly become outdated. In contrast, AI-driven models will be able to continuously update and refine recommendations as new data becomes available, providing clients with insights that remain relevant in a rapidly changing environment.
Third, clients will rapidly become aware of what AI can achieve. They will no longer be impressed by deliverables that consist of well-designed slides or neatly formatted reports. Instead, they will expect consulting firms to integrate AI-driven insights into their work, leveraging these tools to deliver smarter, faster, and more actionable solutions.
The decline of traditional deliverables doesn’t mean clients no longer value what consultants bring to the table—it means the bar has been raised. To stay relevant, firms must redefine their deliverables around:
Dynamic insights: AI-enabled recommendations that evolve as new data becomes available.
Implementation pathways: Detailed plans that go beyond theory and show exactly how results will be achieved.
Measurable outcomes: Deliverables that tie directly to key performance indicators, allowing clients to see the impact of their investment.
In this new landscape, the consulting firm’s role is not to create plans but to enable transformation.
At its core, the devaluation of traditional deliverables reflects a broader shift in client expectations. Organizations will no longer want consultants to stop at recommendations; they will expect them to deliver measurable outcomes. A beautifully crafted strategy is meaningless if it doesn’t result in tangible business improvements.
For example, a client might once have been satisfied with a 50-page report outlining a transformation plan. That same client will want to know how the plan will be implemented, what the expected ROI is, and how success will be measured.
This shift will be particularly pronounced in areas like digital transformation and operational efficiency, where AI tools are already delivering outcomes.
Another factor already driving the decline of PowerPoint-based deliverables is the increasing demand for continuous transformation. Many industries are evolving so rapidly that static deliverables are no longer sufficient. Clients will need ongoing support to adapt to shifting conditions, implement strategies, and fine-tune operations in real time. As a result, consulting firms must shift from delivering episodic solutions to partnering with clients for continuous transformation.
This demand for continuous engagement will require of consulting firms to rethink their service models. Instead of delivering a one-off assessment or TOM, firms will have to provide end-to-end solutions that include strategy, implementation, and ongoing optimization. The days of presenting a deck and moving on to the next client are over.
Continuous transformation will also redefine the relationship between consulting firms and their clients. Instead of transactional engagements, firms will have to cultivate long-term partnerships built on trust, collaboration, and shared success.
While continuous transformation offers significant benefits, it will also present challenges for consulting firms. Transitioning from episodic engagements to ongoing partnerships will require changes to service models, pricing structures, and talent strategies. Firms will have to invest in AI and digital tools, retrain their workforce, and develop the infrastructure needed to support long-term engagements.
However, the opportunities far outweigh the challenges. Firms that embrace continuous transformation can position themselves as indispensable partners in their clients’ success, building deeper relationships and securing a steady stream of revenue. More importantly, they can align their services with the realities of the modern business world, ensuring they remain relevant and competitive in the age of AI.
The Devaluation of Organizational Bullshit
Organizational bullshit—a term rooted in academic study (and not just swearing) and popularized through critical reflections on workplace culture—has long been a feature of corporate life. As explored in my earlier articles – We need to free organizations of bullshit – Part 1: Why? and We need to free organizations of bullshit – Part 2: How?, the phenomenon is pervasive, often cloaked in jargon-heavy language, vague mission statements, and hollow deliverables designed to obscure more than they illuminate . While this culture of inflated nonsense has persisted due to information asymmetry and the prestige of traditional hierarchies, the arrival of AI is poised to dismantle its stronghold as well.
AI, by its very nature, disrupts the foundations on which organizational bullshit thrives. By democratizing access to information and making the processes behind decision-making transparent, AI exposes the gaps between perception and reality. The shiny veneer of “well-packaged but empty” deliverables will no longer suffice in a world where actionable, measurable results are the expectation. This shift will be a reckoning for many organizations, especially those reliant on their ability to project authority and expertise without necessarily delivering substance.
Drawing from my previous writing, organizational bullshit isn’t harmless. It leads to poor decision-making, reduces job satisfaction, and ultimately detracts from the authentic value organizations are meant to create. These effects are exacerbated when this behavior becomes embedded in deliverables, whether it’s consultants inflating the value of their work or internal teams prioritizing optics over outcomes. The stakes have always been high, but AI’s ability to strip away pretenses adds a new urgency to addressing this issue.
Ultimately, this is a chance for the industry to rid itself of this baggage. Just as my earlier articles argued for the necessity of cutting through workplace nonsense to achieve clarity and purpose, the age of AI will demand a similar reckoning.
Long-term partnerships in an AI-driven world hinge on trust. Clients must feel confident that their consulting partners are not only competent but also aligned with their goals and values. Trust is particularly important in the context of AI, where decisions about data, ethics, and implementation carry significant risks and implications.
Consulting firms can build trust by:
Demonstrating transparency: Clearly communicating how AI tools and methodologies are used, what clients can expect, and how outcomes will be measured.
Delivering consistent results: Meeting or exceeding expectations across multiple engagements to establish a track record of reliability and impact.
Prioritizing client interests: Sharing the benefits of AI, offering fair pricing, and focusing on outcomes that genuinely benefit the client, rather than maximizing the short-term firm’s profitability.
Trust isn’t built overnight, but it’s the cornerstone of any successful long-term partnership.
The future of consulting lies in AI-driven, tech-supported, end-to-end delivery models that emphasize outcomes over outputs, integration over abstraction, and measurable impact over static recommendations.
In an AI-driven world, clients will increasingly expect their consulting partners to see projects through from start to finish. This means firms will have to go beyond advising and take responsibility for executing strategies, embedding solutions, and ensuring their impact is sustained over time.
AI will play a central role in enabling this shift. Tools like predictive analytics, generative AI, and machine learning platforms will allow consultants to move seamlessly from analysis to implementation. For example, an AI-powered model that identifies operational inefficiencies can be paired with automation tools to streamline processes directly, reducing the time and effort required to achieve tangible results.
This ability to integrate AI solutions into client operations will transform consulting engagements. Deliverables will no longer be just plans; they will be living systems that evolve with the client’s needs, driving continuous improvement and delivering measurable value.
AI and other advanced technologies will no longer be just tools for analysis—they will be the backbone of end-to-end consulting delivery. To thrive in this new paradigm, firms will have to embed technology into every stage of their engagements:
Discovery and Diagnosis: AI tools analyze data at scale, identify trends, and pinpoint root causes faster and more accurately than traditional methods.
Strategy Development: Generative AI platforms produce dynamic, adaptable strategies that clients can implement in real time, rather than static documents.
Implementation Support: Automation tools and AI models help firms deploy solutions directly, from optimizing supply chains to enhancing customer experience to automate security operations.
Performance Monitoring and Optimization: Once solutions are in place, AI ensures they remain effective, using real-time data to adjust and refine as conditions change.
This approach will enable firms to deliver results that are not only faster but also more sustainable, creating long-term value for clients.
End-to-end delivery will require a fundamental shift in how consulting firms engage with their clients. Instead of handing over deliverables and moving on, firms will have to adopt a collaborative approach, working alongside clients to ensure solutions are successfully implemented and integrated into their operations.
This partnership model will involve:
Co-creation: Developing solutions in collaboration with clients to ensure they align with organizational goals and culture.
Capability Building: Training client teams to use AI tools and processes, empowering them to sustain improvements long after the consultants are gone.
Shared Accountability: Taking joint responsibility for achieving outcomes, rather than simply providing recommendations.
By embracing collaboration, consulting firms will be able to strengthen client relationships and position themselves as trusted partners in transformation.
Transitioning to AI-driven, tech-supported, end-to-end delivery isn’t optional; it’s essential for consulting firms that want to remain competitive in an AI-augmented industry. This shift requires more than just adopting new tools—it demands a cultural transformation. Firms must move away from seeing themselves as advisors and embrace their role as enablers of change.
For those willing to take the leap, the rewards are significant. End-to-end delivery models allow firms to build deeper client relationships, deliver greater value, and secure their place as leaders in the next era of consulting.
The adoption of AI in consulting will create a double-edged sword. On one hand, it will offer unprecedented opportunities for efficiency, automation, and scalability, allowing firms to deliver insights and solutions faster than ever before. On the other hand, it will raise expectations among clients, who will demand that these benefits translate directly into greater value for their businesses—not just increased profitability for consulting firms.
The shift toward AI-driven consulting will demand a new model of partnership—one in which firms are transparent about how AI is being used and actively share its advantages with their clients. This approach won’t just meet evolving client expectations; it will foster trust, deepens relationships, and ensures long-term success for both parties.
Historically, consulting firms have tended to retain the benefits of efficiency gains. For example, if a new tool or process allowed junior consultants to work faster, it often translated into higher margins rather than reduced costs for the client. This approach worked in a world where clients had limited visibility into a firm’s operations and relied on the perceived effort behind deliverables to judge value.
AI will fundamentally change this equation. Clients will be increasingly aware of how generative AI, automation, and advanced analytics streamline consulting work. They will understand that tasks that once took weeks will now take hours and will start to question why cost savings aren’t being passed on to them. Without transparency, firms risk eroding trust and damaging their reputations.
To remain competitive, consulting firms must embrace a more collaborative approach—one that positions AI not as a profit-maximizing tool for the firm but as a value-creating enabler for the client. This requires rethinking both pricing models and engagement strategies.
Transparent Pricing: Firms should openly acknowledge the role AI plays in reducing time and effort and reflect those savings in their pricing. This doesn’t mean undercutting the value of their work; rather, it’s about demonstrating fairness and aligning fees with the outcomes delivered.
Shared AI Capabilities: Instead of using AI exclusively behind the scenes, firms can integrate these tools into client engagements. For example, consultants can work alongside client teams, using AI platforms collaboratively to co-create solutions. This not only empowers clients but also positions the firm as a partner invested in their success.
Outcome-Based Agreements: Moving away from billing by the hour or deliverable, firms can adopt pricing structures tied to measurable outcomes. For instance, a firm implementing an AI-driven cost-reduction strategy might tie its fees to the actual savings achieved, ensuring that both parties benefit from the results.
One of the most effective ways to share the benefits of AI with clients is will be by helping them build their own AI capabilities. Instead of fostering dependency, firms can position themselves as enablers, equipping clients with the tools, skills, and processes needed to sustain improvements independently.
For example, a consulting firm implementing an AI-powered customer segmentation solution might also train the client’s marketing team to use the underlying technology, ensuring they can continue refining and applying the model long after the engagement ends. This approach strengthens the partnership by demonstrating a commitment to the client’s long-term success.
By sharing AI benefits transparently and equitably, consulting firms will be able to build trust—arguably their most valuable asset in an increasingly competitive market. Clients who see their consultants as genuine partners, rather than profit-driven vendors, are more likely to engage them for future projects, recommend them to peers, and collaborate on deeper, more strategic initiatives.
Trust also allows firms to justify premium fees where appropriate. Clients are willing to pay for expertise, innovation, and results when they believe the engagement is built on fairness and shared success.
The integration of AI into consulting will be not just about improving margins or scaling operations—it will be about redefining the relationship between firms and their clients. By openly sharing the benefits of AI, consulting firms will be able to move beyond transactional engagements to build true partnerships.
This shift is not just good ethics; it’s good business. In an industry where trust and outcomes matter more than ever, the firms that embrace transparency and collaboration will be the ones that thrive in the age of AI.
The consulting career ladder has followed a predictable trajectory: junior consultants (the “grinders”) would start at the bottom, tasked with executing the labor-intensive work of gathering data, performing analyses, and preparing deliverables. As they honed their skills and gained experience, they moved up to managerial roles (the “minders”), overseeing projects and guiding the grinders. Finally, after years of developing client relationships and mastering the art of selling, they could ascend to partner-level positions (the “finders”). This hierarchical system wasn’t just a structure—it was a proven pipeline for developing talent and ensuring the sustainability of consulting firms.
AI, however, will disrupt this model at its core. Tasks that once served as a training ground for junior consultants—such as creating financial models, drafting reports, and conducting market analyses—will (very) soon be performed by AI faster and more accurately. This shift raises a fundamental question: if the grinders’ work is disappearing, what does the first rung of the consulting career ladder look like?
The answer is both complex and transformative. The focus of entry-level roles will have to shift from repetitive execution to developing deeper, more specialized expertise. Instead of spending their early years crunching numbers or building slide decks, junior consultants must now learn to leverage AI tools effectively, interpret AI-driven insights, and apply them within the context of a client’s unique challenges. The emphasis is no longer on doing the work but on understanding the work and adding value beyond what AI can provide.
This evolution will require consulting firms to rethink their approach to talent development. The traditional “sink-or-swim” model, where grinders learned by doing under pressure, must give way to structured training programs that emphasize strategic thinking, creativity, and problem-solving. Entry-level consultants will need to be equipped with skills that allow them to complement AI, rather than compete with it. This includes areas like:
Interpreting complex data outputs from AI tools.
Contextualizing AI-driven insights for specific industries or markets.
Developing innovative, human-centered solutions to problems that AI alone cannot address.
As the role of junior consultants changes, so too does the pathway to advancement. The middle rung of the ladder—the “minder” roles—will likely focus less on managing teams of grinders and more on guiding clients through the complexities of implementing AI-driven solutions. Managers will need to act as translators, bridging the gap between technical capabilities and business realities. This requires a mix of technical proficiency, strategic insight, and emotional intelligence—skills that haven’t traditionally been emphasized in these roles. For some more in-depth discussion, see my book.
At the partner level, the impact of this shift will be equally profound. In a world where AI will commoditize much of the grind work, partners will have to bring more to the table than their ability to sell projects or leverage networks. They will need to be thought leaders and domain experts, capable of solving complex problems and delivering measurable outcomes. The career path to partnership, once defined by time and tenure, will increasingly prioritize expertise and the ability to drive transformative value for clients.
This changing career path also has significant implications for how consulting firms attract and retain talent. In the past, the promise of steady advancement through the ranks was a key draw for ambitious professionals. Now, firms must offer a reimagined value proposition: one that highlights opportunities for continuous learning, rapid skill development, and meaningful impact from day one.
In this new reality, the consulting career ladder isn’t disappearing—it’s evolving. The days of grinders may be numbered, but the rise of expertise-driven roles presents an opportunity to create a more dynamic, fulfilling career path for the next generation of consultants. Firms that embrace this change will not only future-proof their talent pipeline but also position themselves as leaders in the age of AI-driven consulting.
The rise of AI is reshaping not only how consulting firms deliver value but also the kind of talent they need to succeed. Traditional hiring strategies, which emphasized raw intelligence, adaptability, and a willingness to grind through demanding workloads, must now evolve to reflect the realities of an AI-augmented industry. With much of the repetitive, labor-intensive work being automated, consulting firms need to rethink who they hire, what skills they prioritize, and how they prepare new hires for a rapidly changing consulting landscape.
Historically, consulting firms recruited from a relatively narrow pool: high-achieving graduates with strong analytical and problem-solving skills, often sourced from elite universities and business schools. These individuals were expected to learn the ropes by doing—spending long hours on data-heavy tasks and building deliverables under tight deadlines. However, as AI takes over much of the grind work, firms need to shift their focus toward hiring candidates who bring a different set of competencies.
In an AI-augmented consulting world, new hires must demonstrate not only technical aptitude but also the ability to think creatively and strategically. Firms should prioritize candidates who can:
Collaborate with AI tools: New hires need to be adept at using generative AI platforms, understanding their capabilities, and integrating AI-generated insights into broader consulting strategies.
Interpret and contextualize AI outputs: AI delivers raw insights, but it takes a human to contextualize those insights within the nuances of a client’s specific challenges. Candidates with strong critical thinking skills and a knack for storytelling will be essential.
Bridge the technical and the human: As AI drives many of the technical aspects of consulting, firms need individuals who can navigate the human side of the equation—communicating effectively with clients, building trust, and managing change within organizations.
The traditional consulting talent pipeline, which heavily favored MBAs and graduates from a handful of prestigious schools, is no longer sufficient. Firms must broaden their hiring scope to include individuals with diverse backgrounds and skill sets, particularly in technology, data science, and specialized industries.
For example, candidates with experience in AI development, machine learning, and data engineering are increasingly valuable, as are those with deep expertise in niche domains such as cybersecurity, supply chain optimization, or healthcare analytics. These individuals bring specialized knowledge that complements AI-driven consulting and adds value beyond what traditional hires can offer. And beyond what AI alone can offer.
At the same time, consulting firms should actively seek candidates with strong interpersonal and creative skills—traits that are difficult for AI to replicate. As consulting shifts from delivering information to driving transformation, the ability to inspire and lead change within client organizations will become a critical differentiator.
Attracting top talent in an AI-augmented industry also means rethinking the employer value proposition. Consulting firms must differentiate themselves not just by offering high salaries or prestigious career paths but by creating environments that foster continuous learning, innovation, and meaningful impact.
For example, firms that provide opportunities to work with cutting-edge AI tools, tackle complex global challenges, or drive transformative change within industries will be more appealing to prospective hires. Similarly, offering clear pathways for advancement, even in a world without grinders, will be essential for retaining ambitious professionals.
The Big 4 consulting firms, my current stomping ground, have long been icons of stability, prestige, and expertise. With deep roots in the professional services industry, these firms have built vast networks, amassed unrivaled client rosters, and leveraged their global presence to dominate the market. But their greatest strength—their traditional, partner-led structure—may also be their Achilles’ heel as the AI revolution accelerates.
At the heart of the Big 4 model is a leadership structure dominated by partners. These individuals often climbed the ranks over decades, excelling at client relationships, business development, and navigating internal politics. Their success has been built on a system that rewards consistency, risk aversion, and incremental change—qualities that now risk leaving these firms unprepared for the seismic shifts AI is bringing.
As a current Big 4 partner, I’ve experienced firsthand the overwhelming feedback to stay patient, avoid disruption, “fit in the culture”, and conform to the status quo—a culture of risk aversion and playing it safe that often stifles meaningful change. It’s this direct encounter with the inertia within Big 4 firms that fuels my deep concern for their ability to adapt in an AI-driven world. This article, in many ways, serves as a personal call to action: a plea for Big 4 firms to embrace transformation boldly and urgently, rather than risk being left behind by the accelerating pace of technological change.
For many partners, the traditional consulting playbook has always worked. They’ve seen the firm grow year over year, with steady revenues and an established pipeline of talent feeding into the pyramid. Why fix something that isn’t broken?
This mindset breeds resistance to change. AI is viewed less as a transformative opportunity and more as a tool to enhance existing processes. While these leaders might approve pilot projects or adopt AI for internal efficiency, they’re often slow to recognize the existential threat AI poses to their core business model.
The problem is compounded by the pace of AI’s development. Inertia is no longer an option. Firms that wait too long to adapt risk falling behind nimbler competitors—tech-savvy systems integrators and forward-looking MBB firms—that are already embracing AI-driven transformation.
In the traditional model, partners bring immense value through their networks and ability to sell. But as AI reshapes the consulting landscape, this value proposition is under pressure. Clients are increasingly demanding more than just access to a firm’s junior talent and methodologies; they want deep, hands-on expertise from the senior leaders themselves.
For partners accustomed to spending most of their time building relationships and overseeing projects from a distance, this is a challenging adjustment. AI’s automation of grind work and its ability to generate insights independently means clients no longer need intermediaries—they want direct access to the people who can deliver the most impact.
This shift requires partners to evolve. They must offer more than just their network; they need to bring specialized knowledge, strategic foresight, and the ability to solve complex problems that AI cannot.
The Big 4 are cultural powerhouses, steeped in tradition and guided by governance models designed to preserve stability. But this culture, while valuable in times of incremental change, becomes a liability in moments of disruption.
Resistance to transformation often stems from a fear of losing control. Senior leaders worry that adopting radical AI-driven strategies could destabilize the firm’s established hierarchy, disrupt billing models, disrupt the “culture”, or dilute the role of partners. These concerns, while understandable, create a dangerous hesitation.
Meanwhile, competitors—particularly large systems integrators with a stronger technology focus—are moving swiftly. They’re integrating AI into their service delivery models, aligning offerings with emerging client expectations, and winning ground that the Big 4 might struggle to reclaim.
The history of disrupted industries offers a cautionary tale. From Kodak’s resistance to digital photography to Blockbuster’s dismissal of streaming, legacy leaders often fail to adapt not because they lack the resources or talent, but because they cling too tightly to what worked in the past.
For the Big 4, the warning signs are already here. Clients are exploring AI tools independently, questioning the value of traditional consulting deliverables, and looking for partners who can drive transformation, not just advise on it.
If Big 4 partners don’t adapt quickly—by embracing AI, rethinking their roles, and prioritizing expertise over leverage—they risk following the same path as those disrupted before them.
For years, the Big 4 relied on their extensive networks as a key differentiator. Senior partners cultivated long-term relationships with decision-makers, leveraging trust and familiarity to secure engagements. However, as AI starts transforming consulting, this advantage is eroding.
Clients today are already less impressed by relationships and more focused on measurable outcomes. They no longer need to rely solely on their Big 4 partner’s Rolodex to access expertise or resources; AI tools, combined with open marketplaces and gig-based ecosystems, are leveling the playing field. The value of a personal network diminishes when clients can tap into cutting-edge insights and capabilities independently.
To remain relevant, Big 4 partners will have to demonstrate expertise and value that go beyond who they know. The ability to guide clients through complex AI-driven transformations and deliver results that AI alone cannot achieve will become the new benchmark for success.
The Big 4 have long thrived on the combination of prestige, brand recognition, and information asymmetry. Clients often accepted glossy PowerPoint deliverables at face value, trusting that the weight of the firm’s name guaranteed quality and rigor. But AI is poised to deliver a double blow to this comfortable model.
First, it will erode the Big 4’s brand value by leveling the playing field. When AI tools can generate detailed analyses and polished presentations in minutes, the mystique surrounding the Big 4’s output will begin to fade. Second, AI will make it painfully clear to clients that much of what they’ve been paying premium fees for—those same PowerPoint strategies and frameworks—isn’t delivering meaningful value. As clients become more sophisticated and self-sufficient with AI, they will demand substance and outcomes, not slides and status. Simply put, the easy life that many Big 4 practices have enjoyed, where prestige and process mattered more than true impact, is coming to an end—and fast.
AI is forcing a redefinition of expertise. It’s no longer enough to understand frameworks and methodologies or oversee a team of junior consultants. Clients will expect their advisors to be deeply knowledgeable in specific areas—whether it’s navigating AI implementation, managing data privacy risks, or driving cultural change in an AI-augmented organization.
This shift is particularly challenging for Big 4 partners, many of whom have risen through the ranks based on their ability to sell and manage relationships, rather than their technical expertise. In the AI era, clients will demand more than polished presentations and generic recommendations—they’ll expect senior leaders to bring actionable, domain-specific insights to the table.
The Big 4 firms that succeed will be those that double down on upskilling their leaders, investing in continuous learning, and fostering a culture where deep expertise is valued as much as—if not more than—salesmanship.
The traditional Big 4 model is built on leveraging time. But in a world where AI can accomplish much of that work in seconds, this model will become increasingly unsustainable.
Clients will very quickly start questioning the value of paying premium fees for outputs that AI can replicate. The focus will shift to outcomes—measurable business improvements that justify the investment in consulting services. For the Big 4, this means moving away from billing hours and toward selling value.
This shift will require not just a change in pricing models but also a cultural transformation. Firms must embed outcome-driven thinking into their DNA, aligning their services with client goals and ensuring that every engagement delivers tangible impact.
Big 4 firms are already exploring how to use GenAI to supplement their own effort. The conversation, however, is focused on the promise of significant labor savings. And only on that. By automating much of the grind work, firms can reduce their reliance on junior consultants, thereby lowering operational costs. The conversation risks remaining short-sighted. The focus only on immediate labor savings may create blind spots for firms in preparing for the next wave of AI-driven disruption.
At first glance, the logic of labor savings is irresistible. Firms can maintain—or even increase—their project capacity while reducing the overhead associated with hiring, training, and managing junior talent. The promise of such efficiency gains can also make AI a compelling selling point for clients, as firms present themselves as tech-savvy partners who deliver faster and more cost-effectively than ever before.
However, this efficiency-driven approach is inherently shortsighted. While consulting firms are busy optimizing their internal operations, their clients will also be embracing AI—often just a few steps behind. Clients will be using the same tools to analyze data, draft reports, and model scenarios, rapidly closing the gap between what they can achieve independently and what consulting firms offer. The same technology that firms are using to streamline operations is simultaneously eroding the exclusivity of their services.
This creates a troubling paradox. By focusing narrowly on labor savings, firms may unwittingly accelerate their own commoditization. Deliverables that were once central to a firm’s value proposition—detailed reports, frameworks, and strategies—are now viewed by clients as baseline outputs, easily replicable using AI.
The real danger lies in underestimating how quickly clients will evolve their use of AI. While consulting firms may see AI as a competitive edge today, the reality is that clients are often only a few months to two years behind in their adoption curve. Once clients become proficient in leveraging AI, they will demand more from their consulting partners—more insights, more value, and more measurable outcomes. Those firms focused on immediate gains, may find themselves unprepared to meet these heightened expectations.
The next wave of AI-driven disruption won’t be about automation alone; it will be about transformation. Clients will want consulting partners who can go beyond delivering AI-generated insights to help them navigate the broader implications of AI adoption—reshaping business models, driving cultural change, and implementing AI-driven innovations at scale. Consulting firms that have optimized around labor savings may lack the expertise, infrastructure, and strategic foresight needed to thrive in this new environment.
The lesson is clear: labor savings are not a strategy; they are a tactic. To succeed in the age of AI, consulting firms must look beyond the immediate benefits of AI and invest in building capabilities that position them for long-term relevance. This means rethinking how they deliver value, focusing on transformation rather than transaction, and staying ahead of the curve as clients close the gap in their own AI maturity. Or to be blunt and risk upsetting my peers—partners at Big 4, any AI efficiencies and savings achieved in the first phase of AI adoption (first 2-3 year) should be fully re-invested in future phases of AI-driven transformation, and not distributed to equity partners.
The challenge for the Big 4 is that this transformation won’t be easy—or cheap. Upskilling partners, overhauling pricing models, and rethinking service delivery will require significant investment and, perhaps more importantly, a willingness to disrupt their own established ways of working.
The cost of inertia, however, will be far greater. Competitors like large systems integrators and MBB firms are already adapting, leveraging their tech-savvy reputations and future-focused strategies to win clients who might otherwise turn to the Big 4.
The pressure to evolve isn’t just external; it’s also internal. Younger consultants are increasingly drawn to firms that embrace innovation and offer opportunities to work on cutting-edge AI-driven projects. Without a clear path forward, the Big 4 risk losing not just clients but also the talent that drives their business.
While the Big 4 will grapple with adapting their traditional models, competitors such as large systems integrators and MBB (McKinsey, BCG, Bain) firms will likely do a much better job at positioning themselves to thrive in the AI-driven consulting landscape. These firms have distinct advantages that make them more agile and better prepared to meet the demands of the AI era.
Large systems integrators like Accenture, IBM, Capgemini, Deloitte’s tech-focused arms, and others have long had a reputation for their technological expertise and implementation capabilities. Unlike the Big 4, which traditionally leaned on frameworks and strategies, systems integrators are already comfortable working at the intersection of technology and business.
AI is a natural extension of their capabilities. These firms are leveraging their tech-savvy cultures to:
Integrate AI into service delivery: Systems integrators excel at end-to-end delivery, from strategy to implementation. They will be able to deploy AI tools not just for insights but also to operationalize those insights in client environments.
Offer AI-enhanced solutions: Whether it’s predictive analytics, AI-driven automation, or bespoke machine learning models, these firms will be able to provide clients with tools and platforms that deliver immediate, measurable value.
Attract technical talent: Their focus on cutting-edge technology makes them a magnet for AI specialists, data scientists, and engineers, ensuring they have the expertise to lead in the AI space.
This combination of technological know-how and practical implementation positions systems integrators as go-to partners for clients looking to leverage AI, often bypassing the Big 4 altogether.
The MBB firms—McKinsey, BCG, and Bain—may not have the same technological depth as systems integrators, but they excel in their ability to anticipate and shape market trends. Known for their rigorous research and data-driven insights, these firms are often the first to identify emerging opportunities and risks, including those posed by AI.
Here’s what sets them apart:
Thought leadership: MBB firms have been producing reports, whitepapers, and frameworks on AI for years, positioning themselves as experts in navigating its impact. Clients see them as strategic partners who understand not just today’s challenges but also tomorrow’s opportunities.
Agility: With their smaller, more elite structures, MBB firms can pivot faster than the Big 4. They’re quicker to adopt AI tools internally and to redesign their services around emerging client needs.
Focus on outcomes: MBB firms have always emphasized delivering results over process, a mindset that aligns naturally with the shift from outputs to outcomes. Their ability to tie strategy to measurable business impact makes them particularly attractive in an AI-driven world.
Both systems integrators and MBB firms benefit from cultures that are more aligned with the demands of the AI era:
Innovation-first mindsets: These firms are less bound by tradition and more willing to experiment with new technologies and service models.
Specialized expertise: They have long emphasized hiring and retaining top-tier talent with deep domain knowledge, rather than those that “fit the culture”, making it easier to adapt to a world where expertise trumps leverage.
Client-centric approaches: Both groups are adept at tailoring their offerings to client needs, whether through customizable AI solutions or bespoke strategic advice.
All these predictions should offer some lessons for the Big 4:
Invest in technology and expertise: Building AI capabilities isn’t optional—it’s a requirement. The Big 4 need to develop or acquire the technical expertise to compete with systems integrators.
Focus on measurable outcomes: Adopting an outcomes-first mindset can help the Big 4 remain relevant as clients demand more than just frameworks and recommendations.
Embrace cultural change: Innovation needs to move from buzzword to business practice. The Big 4 must foster a culture that rewards experimentation and adaptation, even if it challenges long-standing traditions.
Transitioning to AI-driven, tech-supported, end-to-end delivery isn’t optional; it’s essential for consulting firms that want to remain competitive in an AI-augmented industry. This shift requires more than just adopting new tools—it demands a cultural transformation. Firms must move away from seeing themselves as advisors and embrace their role as enablers of change.
The consulting industry is entering a period of profound transformation. While firms have weathered technological disruptions in the past, the rise of AI is different in its scope, speed, and implications. As consulting adapts to this new reality, the trajectories firms choose will define not only their success but also their survival. Yet, alongside the opportunities lie significant risks, particularly for firms that underestimate the pace of change or cling to outdated models.
In the near term, most consulting firms are likely to focus on integrating AI to enhance efficiency. The immediate appeal of generative AI and automation lies in their ability to streamline processes, reduce costs, and accelerate deliverables. Firms are already using AI to automate labor-intensive tasks like data analysis, benchmarking, and report generation, which were traditionally handled by junior consultants. This trajectory allows firms to maintain competitiveness in the short term, offering faster and more cost-effective services to clients.
However, this efficiency-driven approach carries risks. By prioritizing cost savings, firms may fall into the trap of treating AI as a tactical tool rather than a transformative force. As discussed above. This perspective limits innovation and overlooks the deeper, structural changes required to meet evolving client expectations. Firms that focus solely on operational improvements risk being outpaced by competitors that embrace AI as a driver of strategic reinvention.
As AI tools become more sophisticated, consulting firms will likely expand their use beyond back-end efficiency into front-end engagement. This involves deploying AI not just to support deliverables but to actively enhance client interactions and outcomes. For example, firms may integrate AI into collaborative workshops, use predictive analytics to inform real-time decision-making, or offer dynamic, AI-driven dashboards that clients can interact with directly.
This trajectory represents a shift from static consulting models to more dynamic, data-driven engagements. However, it also introduces challenges. As clients become more adept at leveraging AI themselves, the line between consultant and client capabilities begins to blur. Firms that fail to differentiate their services risk being seen as redundant, particularly if their offerings do not go beyond what clients can achieve independently with similar tools.
There is also the risk of over-reliance on AI. While AI can enhance insights and efficiency, it cannot replace the human elements of consulting—creativity, judgment, and the ability to navigate complex organizational dynamics. Firms that neglect these aspects may find themselves delivering technically impressive but strategically hollow solutions.
The most successful consulting firms will likely pursue a trajectory that positions them not as advisors but as transformation partners. This involves a fundamental reinvention of the consulting model, with firms taking greater accountability for implementation, outcomes, and capability building. Rather than delivering plans and frameworks, these firms will co-create solutions with clients, embed AI tools into their operations, and drive sustained, measurable impact.
This trajectory demands significant investment—not just in technology but also in talent, culture, and client relationships. Firms must upskill their workforce to complement AI, foster a culture of continuous learning, and build trust through transparency and shared success.
Yet, the risks are equally significant. Transitioning to this model requires a departure from traditional revenue structures, such as billing by the hour or deliverable, which may unsettle long-standing business models. It also demands agility, as firms must continuously adapt to advancements in AI and shifts in client needs. Firms that cannot navigate these complexities risk losing relevance, particularly as newer, more agile competitors enter the market.
Perhaps the greatest risk for the consulting industry is inaction. The pace of AI-driven change is unrelenting, and firms that fail to evolve will be left behind. This includes firms that resist change due to cultural inertia, underinvest in AI capabilities, or cling to models that no longer resonate with clients. In other words, the Big 4 most likely. In a landscape where differentiation is increasingly tied to innovation, stagnation is a death sentence.
At the same time, there is a risk of moving too quickly without a clear strategy. Firms that rush to adopt AI without aligning it to their broader vision risk implementing tools that create more confusion than value. The balance lies in thoughtful, deliberate transformation—embracing AI not as a quick fix but as a cornerstone of a reimagined consulting model.
As the consulting industry navigates these trajectories, the firms that succeed will be those that strike a balance between short-term efficiency and long-term reinvention. By embracing AI as both a tool and a driver of transformation, firms can position themselves as indispensable partners in a world where the rules of business are constantly being rewritten.
Generative AI (GenAI) is the headline act in consulting’s adoption of AI. From automating grind work to enhancing client insights, GenAI will mark a first phase of AI’s integration into the consulting industry. But the story will not end here. AI is evolving rapidly, and the second phase—driven by advancements in areas like autonomous decision-making, domain-specific AI, and integrated AI ecosystems—promises even greater disruption and opportunity.
Consulting firms that focus solely on GenAI risk falling behind as AI’s capabilities expand. To thrive in the long term, they must prepare for this second phase, anticipating its challenges and positioning themselves to leverage its transformative potential.
The next phase of AI will move beyond text generation and predictive analytics to encompass more autonomous, adaptive, and specialized capabilities. Future AI systems will not just suggest strategies but execute them, continuously learn from their environments, and refine their actions in real time. Domain-specific AI—tools tailored to industries like healthcare, finance, or logistics—will provide highly specialized insights and solutions that generic platforms like ChatGPT cannot replicate.
In addition, integrated AI ecosystems will emerge, where multiple AI tools work together seamlessly to address complex, multi-faceted problems. For consulting firms, this means engagements will no longer be about deploying individual AI solutions but designing and managing entire AI ecosystems for their clients.
These advancements will raise the bar for consulting firms. Clients will expect their advisors to go beyond leveraging AI for efficiency and deliver expertise in integrating, governing, and scaling these advanced systems.
As AI’s capabilities grow, so too will client expectations. In the second phase of AI adoption, clients will demand partners who can help them navigate the complexities of AI integration, from addressing ethical considerations to ensuring compliance with evolving regulations. They will expect firms to provide not just tools but frameworks for managing AI risk, aligning AI strategies with business goals, and fostering cultural adoption within their organizations.
Importantly, clients will also expect consulting firms to stay ahead of them. While clients may lag slightly in their adoption of AI during the GenAI phase, many will close this gap in the coming years. Firms that fail to maintain a clear edge in AI capabilities risk losing their relevance as clients become increasingly self-sufficient.
Many consulting firms will approach the second phase of AI with a reactive mindset, adapting to changes as they occur. While this approach may preserve short-term stability, it carries significant risks. Firms that are slow to adopt new AI capabilities or fail to anticipate shifts in client demands will struggle to compete with more proactive competitors.
A reactive strategy also increases the risk of falling into the same trap as the GenAI phase: focusing on operational efficiency at the expense of strategic reinvention. While efficiency gains may keep firms afloat, they will not differentiate them in a marketplace increasingly defined by innovation and outcomes.
To prepare for AI’s second phase, consulting firms will have to adopt a proactive, forward-looking approach. This begins with investing in the capabilities and infrastructure needed to support advanced AI applications. Firms should prioritize building expertise in areas such as:
Autonomous AI systems and their governance.
Industry-specific AI applications that offer tailored value to clients.
AI ethics, compliance, and risk management frameworks.
Additionally, firms will have to cultivate a culture of continuous innovation. This means encouraging teams to experiment with emerging AI tools, fostering collaboration across disciplines, and embedding AI literacy at every level of the organization. Senior leaders, in particular, must take an active role in championing AI-driven transformation, ensuring that their firms remain agile and adaptive in the face of rapid change.
The consulting industry has long prided itself on its ability to guide clients through change, but now it finds itself at a critical juncture. The rapid evolution of AI represents a strategic inflection point—a moment where the rules of the game shift, and decisions made today will determine which firms thrive and which fall behind. For consulting firms, adapting to this new reality isn’t just important—it’s existential.
Strategic inflection points are rarely obvious when they first emerge. They often feel like incremental changes rather than the seismic shifts they truly are. Many firms may see AI as an enhancement to their existing models rather than a force that demands a complete rethink of their business. But history has shown that industries failing to recognize and act on these moments are often left scrambling to catch up—or worse, rendered obsolete.
Adapting to an inflection point requires more than incremental adjustments; it demands bold, forward-thinking decisions. Consulting firms must shift from seeing AI as a tool to improve existing services to embracing it as a catalyst for reinvention. This means:
Reimagining their value proposition to focus on outcomes rather than outputs.
Investing in new capabilities, such as AI integration, ethical governance, and implementation expertise.
Redefining the consulting career path to prioritize expertise and innovation over hierarchy and tenure.
Adaptation also requires a mindset shift. Firms must foster a culture of agility, where experimentation is encouraged, and failure is seen as a stepping stone to learning and growth. Senior leaders must take an active role in driving this cultural transformation, setting the tone for the organization and ensuring alignment with long-term strategic goals.
As we reflect on the seismic shifts that AI, exemplified by tools like ChatGPT, is beginning to bring to the consulting industry, one truth remains steadfast: human expertise is, and will continue to be, irreplaceable. While AI has shown remarkable ability to automate processes, generate insights, and even draft strategies, its capabilities are inherently limited by its nature. Human consultants bring qualities that AI cannot replicate—qualities that are crucial for navigating the complexities of modern business challenges.
AI excels in environments with clear rules and abundant data. It can analyze historical patterns, predict trends, and suggest optimized solutions. However, many of the challenges clients face exist in ambiguous, uncertain contexts where no amount of data can provide definitive answers.
In these situations, human judgment becomes critical. Experienced consultants draw on intuition, domain expertise, and a deep understanding of organizational dynamics to make decisions where AI falls short. For example, an AI might recommend a cost-cutting strategy based on efficiency metrics, but it takes a human to evaluate the cultural and political implications of that strategy within the client’s organization.
Business transformation is as much about people as it is about processes. Clients don’t just need technical solutions; they need partners who can build trust, understand their unique challenges, and guide them through periods of change.
AI, for all its power, lacks the ability to connect on a human level. It cannot empathize with a stressed leadership team, mediate conflicts within an organization, or rally employees around a shared vision. Human consultants bring these interpersonal skills to the table, creating the relationships that make successful transformation possible.
AI generates insights based on existing patterns, but it cannot think creatively or innovate in the way humans can. True innovation often involves challenging assumptions, breaking established norms, and imagining possibilities that have never been explored before.
Consultants bring a level of creative problem-solving that goes beyond data-driven logic. They can conceptualize entirely new business models, identify unconventional opportunities, and craft narratives that inspire change. This ability to think outside the box is particularly valuable in industries undergoing rapid disruption, where the solutions of the past are no longer sufficient for the challenges of the future.
AI’s capabilities are only as good as the data it is trained on and the goals it is programmed to optimize. Without careful oversight, it can produce results that are technically correct but ethically questionable or strategically misaligned.
Human consultants play a vital role in providing this oversight. They ensure that AI-driven solutions align with a client’s values, comply with regulatory standards, and consider the broader societal implications of their implementation. For instance, deploying AI to optimize workforce efficiency might improve short-term productivity, but human consultants can weigh the long-term impact on employee morale and organizational resilience.
AI can identify opportunities for improvement and even suggest steps to achieve them, but it cannot lead a transformation. Organizational change involves managing complex stakeholder dynamics, aligning competing priorities, and navigating resistance—all tasks that require human leadership.
Consultants act as orchestrators of transformation, bringing together diverse teams, ensuring alignment across functions, and driving the execution of strategies. Their ability to manage the human side of change is a critical complement to the technical capabilities of AI.
The consulting firm of the future won’t be defined by a choice between human expertise and AI—it will thrive on the partnership between the two. AI will handle the heavy lifting, automating repetitive tasks, analyzing vast datasets, and generating foundational insights. Human consultants will focus on the higher-order challenges: interpreting those insights, crafting strategies that consider the full context, and driving the human-centered execution of those strategies.
By combining the strengths of AI with the irreplaceable qualities of human expertise, consulting firms can deliver value that neither could achieve alone. This synergy will be the cornerstone of consulting’s evolution in the age of AI.
As we enter a new chapter for the consulting industry, it’s clear that technology will continue to evolve at a breathtaking pace. But even in the face of rapid advancements, one thing remains constant: the need for human wisdom, empathy, and creativity. The consulting firms that recognize and embrace this truth will not only adapt to the future—they will define it.
As we stand on the brink of a new era, with the launch of tools like ChatGPT heralding a wave of AI advancements, it’s clear that the consulting industry is on the cusp of profound transformation. The trends outlined in this article—AI-enhanced insights, continuous transformation, the shift from outputs to outcomes, and the rise of long-term partnerships—are not merely possibilities; they are inevitabilities. The consulting firm of the future will look radically different from the models we have relied upon for decades.
The consulting firm of tomorrow will not be defined solely by human expertise or technological capabilities but by how seamlessly the two are integrated. AI will be at the core of every engagement, from scoping projects to delivering insights and tracking outcomes. Consultants will need to act as interpreters, bridging the gap between what AI can produce and what clients need to succeed.
The role of the consultant will shift from data analysis and report preparation to guiding strategic decision-making, managing AI systems, and helping clients navigate complex transformations. Human expertise will remain critical, but it will focus on areas where AI cannot yet tread—creativity, empathy, judgment, and the ability to manage human dynamics in the face of change.
The episodic engagements that once defined consulting will give way to ongoing relationships. Clients will expect their consulting partners to stay with them through the entire lifecycle of transformation, providing not just solutions but the tools, training, and collaboration needed to sustain those solutions over time.
This shift will demand a new operating model. Consulting firms will evolve into agile, adaptive entities that deliver value continuously rather than at discrete intervals. Pricing structures will align with client outcomes, with fees tied to measurable improvements rather than hours billed or deliverables produced.
As clients become more sophisticated in their use of AI, consulting firms will need to demonstrate their ability to deliver results that go beyond what AI alone can achieve. The consulting firm of the future will not just leverage AI tools to generate insights but will embed those tools into client operations, ensuring that every engagement drives measurable business impact.
This outcome-driven approach will redefine the value proposition of consulting. No longer will firms be able to justify their fees through effort or exclusivity of knowledge. Instead, their worth will be measured by the tangible improvements they deliver—cost savings, revenue growth, operational efficiencies, and more.
The traditional consulting career ladder—grinders, minders, and finders—will no longer suffice. As AI automates the repetitive grind work, firms will need to focus on hiring and developing talent capable of complementing AI, not competing with it. The career path will emphasize rapid upskilling, domain expertise, and the ability to lead complex, technology-driven transformations.
Junior consultants will spend less time on spreadsheets and PowerPoint decks and more time learning how to integrate AI tools, interpret data, and manage client relationships. Senior leaders will need to provide more than just networks and salesmanship—they will need to deliver expertise that is irreplaceable and value that is demonstrable.
The consulting firm of the future will also play a critical role in addressing the ethical and societal implications of AI. Clients will look to their consulting partners not just for technical solutions but for guidance on navigating issues like data privacy, algorithmic bias, and the broader impact of AI on workforces and communities.
This will require consulting firms to develop expertise in AI governance, compliance, and risk management, positioning themselves as trusted advisors in an increasingly complex landscape.
As we close 2022, the consulting industry faces a stark choice: evolve or risk irrelevance. The appearance of tools like ChatGPT is not just a technological milestone—it’s a wake-up call for an industry that has long relied on traditional models of value creation.
The consulting firm of the future will not emerge by accident. It will be built by those willing to embrace change, experiment with new models, and invest in the capabilities needed to thrive in an AI-driven world. The firms that succeed will not just adapt to the future—they will help define it, setting the standard for what consulting can and should be in the decades to come.
To thrive in this flipped industry, consulting firms must embrace change as both a necessity and an opportunity. The disruption caused by AI is not a threat to the core purpose of consulting; it’s a chance to realign with what clients truly value: solutions that are fast, actionable, and transformative.
Adapting to this new reality requires more than just adopting AI tools or tweaking service offerings. It demands a fundamental rethinking of how consulting firms operate, deliver value, and engage with clients. This shift isn’t optional. Clients are already evolving, leveraging AI to become more self-sufficient and demanding more from their consulting partners. Firms that resist or delay will find themselves quickly outpaced by more agile competitors.
The flipped industry doesn’t mean the end of consulting—it means the end of consulting as we know it. Expertise remains critical, but it’s no longer about who can collect the most data or create the flashiest PowerPoint deck. The consulting firm of the future will be judged by its ability to:
Navigate complexity.
Interpret AI-driven insights in ways that resonate with clients’ unique challenges.
Build trust by delivering measurable results and ethical guidance.
Consultants who lean into these roles will find that their expertise is not diminished by AI but enhanced by it.
Thriving in a flipped industry requires consulting firms to go beyond adaptation and embrace reinvention. This means creating new models for delivering value—models that are collaborative, transparent, and built for long-term impact. It means redefining what it means to be a consultant, moving from a provider of solutions to an enabler of transformation.
The firms that seize this moment will emerge stronger, not just surviving the disruption but shaping the future of the industry. They will set the standard for what consulting can achieve in a world where AI amplifies human potential rather than replacing it.
Above all, the flipped industry underscores the enduring importance of the human element. AI is a powerful tool, but it is just that—a tool. The creativity, empathy, and judgment that define great consultants cannot be automated. These qualities are what make consulting meaningful, and they are what will continue to differentiate the best firms from the rest.
As the consulting industry flips, the firms that thrive will be those that embrace the possibilities of AI while staying true to the principles that have always defined consulting at its best: delivering real value, building trust, and helping clients achieve what they couldn’t achieve on their own.
The flipped industry is here, and it’s happening faster than anyone anticipated. For those willing to embrace it, the future of consulting is bright—not despite AI, but because of it.
The Final, Final Thought. Really
As a Big 4 partner who cares deeply about the future of Big 4, it pains me to say this final thought, but I must. For the Big 4, this moment represents not just a challenge but an existential risk. Their traditional models, deeply rooted in hierarchical structures and slow-moving and risk-averse processes, leave them especially vulnerable to the pace of AI-driven change. If these firms cannot embrace AI and adapt quickly enough to meet the demands of a flipped industry—redefining their value proposition, overhauling their delivery models, and rethinking their leadership structures—then perhaps their time has passed. In an era where agility and innovation are the ultimate currencies, the inability to transform may signal that their legacy approach was never meant to endure in the face of such profound technological evolution. The firms that fail to rise to this moment will not be undone by AI itself but by their own resistance to change. Perhaps, in the end, that’s the most fitting judgment on their relevance in this new age.
For over 30 years, Marin Ivezic has been protecting critical infrastructure and financial services against cyber, financial crime and regulatory risks posed by complex and emerging technologies.
He held multiple interim CISO and technology leadership roles in Global 2000 companies.
