When AI Becomes the Consultant: What This Means for Traditional Firms

If an industry runs on human knowledge and labor, AI won’t just disrupt it, but rather “dismantle” it. This is the age where decades of hard-won expertise, once the cornerstone of long-term success, are suddenly at risk of becoming obsolete.

Consultancy is a typical example. For decades, consulting firms thrived because they had deep pools of expertise, specialized frameworks, and teams of smart people who could analyze problems and recommend strategies. That human expertise used to be the foundation of long-term success, clients had no way to replicate it internally.

But now, with AI being able to analyze massive datasets, generate insights, and even draft strategies, much of the work that once required armies of consultants can be automated. This makes consulting a prime case study of how industries built on knowledge, judgment, and analysis are being disrupted.

To begin with, it’s worth examining how the consulting industry became so large and influential.

How Consulting Built an Empire on Expertise

Historically, the roots of consulting go back centuries, with advisors helping leaders make critical decisions. However, the modern consulting industry began during the Second Industrial Revolution, when businesses needed help optimizing complex operations. Early pioneers like Arthur D. Little applied scientific principles to management, laying the foundation for consulting as a profession.

As the 20th century progressed, consulting expanded. Companies needed more than workflow optimization—they needed help navigating strategy, governance, and finance. Consulting moved from the factory floor to the executive suite.

Firms like Booz Allen Hamilton began advising not just corporations but also governments, while McKinsey emerged in the 1930s as a trusted partner for organizational restructuring and strategy after the Great Depression.

This shift established consulting as a professionalized discipline, offering objective, structured advice that could withstand scrutiny from boards and regulators.

The post-war era ushered in consulting’s “golden age of strategy,” with firms like BCG and Bain introducing frameworks that turned strategy into a science. By the 1980s and 1990s, technology drove a new wave—ERP systems, global integration, and the rise of the Big Four in IT consulting transformed the industry into a global business.

The late 1990s shifted the focus to operational excellence, with firms rolling out standardized methodologies and branded programs, though this risked commoditization.

By the 2000s, consulting fragmented further as clients sought specialized expertise, fueling the growth of boutiques, hybrid models, freelance platforms, and in-house teams. What was once elite and uniform had become a diverse ecosystem of choices.

In short, consulting was essential because it solved problems companies couldn’t solve on their own—knowledge was scarce, data was hard to access, and only firms like McKinsey, BCG, or Bain had the frameworks, benchmarks, and global insights to guide leaders’ decisions.

Consultants brought intellectual firepower, structured problem-solving, and credibility in executing large transformations, making them indispensable partners in strategy and operations.

However, that was the story before the rise of AI. The model once seen as a silver bullet—where firms like McKinsey, BCG, and Bain thrived by packaging scarce knowledge, proprietary frameworks, and global benchmarks—no longer holds the same power.

The Moment Everything Changed: When AI Entered the Boardroom

According to David Linthicum, a globally recognized thought leader in cloud computing, artificial intelligence (AI), and cybersecurity, traditional consulting firms are facing major disruption because AI can now handle much of the work they used to charge clients for. For decades, these firms thrived by offering proprietary frameworks, expertise, and analysis, but AI-powered tools are giving clients the ability to generate those same insights internally—faster, cheaper, and often more consistently.

“As clients adopt powerful AI tools, they are increasingly able to generate insights internally, eroding the need for traditional consulting services,” he stated.

This shift is especially pronounced in areas like auditing, business analytics, legal and accounting services, and IT automation, where much of the work involves processing enormous amounts of information. Since AI excels at this kind of task, clients no longer need to pay consultants for routine analysis that can now be automated. AI also removes the inconsistency problem: with consulting, sometimes clients get top experts, but other times they end up paying premium rates for inexperienced staff.

Big consulting clients are becoming more self-sufficient by using AI for analytics, automation, and even strategy, which reduces their reliance on consultants for routine work. As a result, consultants will be forced to focus on delivering higher-level, specialized insights instead of the low-level tasks that used to be their main source of revenue.

“So the big consulting clients out there are becoming what we call self-service innovators. So these clients can access AI powered analytics, process automation, and even strategic planning systems without relying on consultants, and so this self-service capability means clients expect consultants will deliver more specialized high impact solutions rather than routine analysis,” he explained.

David Linthicum added, “So they’re making the consultants actually move up the stack a bit, so instead of doing the low-level business work which is their bread and butter—that’s how they’re getting paid, that’s where they start, that’s where they start booking the hundreds and hundreds of hours that they do to get audits or help you with management consulting problems or IT automation problems, things like that—they’re going to be abstracted up to allowing them to make more higher-level decisions.”

Even consulting firms themselves will have to rely heavily on AI. But this brings another challenge: if they are using AI tools to generate insights, they can no longer justify billing clients hundreds of hours for routine tasks. Instead, clients will expect smaller teams, faster delivery, and much lower costs—potentially only 10% of traditional fees.

However, David cited that consulting won’t disappear altogether, but firms will shrink significantly in size and scope. Far fewer people will be needed, and the role of consultants will shift toward guiding higher-level decisions rather than performing the bulk of the analytical work.

“So I’m not saying we’re going to eliminate people altogether out of these consulting organizations, I think they’re going to be organizations of people at the end of the day, I just think we’re getting way fewer people to do what they’ve done in the past,” he said.

How Smart Consulting Firms Are Fighting Back

Consulting firms are under immense pressure to upskill their workforce and redefine value in the age of AI. To stay relevant, they must pivot toward becoming trusted guides in AI adoption and implementation, which has sparked a race to rapidly build AI competencies—from architecture to utilization across industries like healthcare, retail, and finance.

This is why the world’s top strategy consulting firms are undergoing a transformation, integrating artificial intelligence (AI) into their core operations and client services.

McKinsey’s AI strategy centers around QuantumBlack, a data analytics firm it acquired in 2015. This unit powers McKinsey’s machine learning and digital transformation efforts. The firm uses AI to analyze large datasets, identify strategic opportunities, and support decision-making.

Tools like CausalNex and the internal AI assistant “Lilli” help consultants deliver faster, more data-driven insights while maintaining strategic depth. McKinsey also deploys hybrid teams of consultants and AI engineers to provide end-to-end solutions.

BCG’s AI efforts are led by BCG X, a tech-focused unit that combines data scientists, engineers, and designers with strategy consultants. The firm has partnered with companies like DataRobot and Anthropic to expand its AI offerings.

BCG emphasizes Explainable AI (XAI), ensuring that business leaders understand how AI models generate insights. Tools like Lighthouse and FACET support forecasting and visualization, while internal experiments show strong productivity gains from generative AI—especially for junior analysts.

Bain has taken a bold step by partnering with OpenAI to roll out generative AI tools like GPT-4 and DALL·E to its 18,000 consultants. These tools automate research, idea generation, and presentation creation.

A standout example is Bain’s collaboration with Coca-Cola on the “Create Real Magic” campaign, which used generative AI to enhance marketing strategy and creative production. Bain’s Vector team, with over 1,500 tech experts, supports AI-driven transformation across industries, blending strategy and implementation.

Accenture leads in AI scale, with over 40,000 professionals and deep integration across industries. Its Applied Intelligence unit delivers solutions in data engineering, predictive analytics, and cloud-based AI.

Deloitte’s AI Institute drives innovation and ethical AI deployment, while PwC and EY embed AI into financial modeling, compliance, and strategic planning. Kearney focuses on practical AI applications in supply chain and pricing, offering user-friendly tools that deliver measurable impact.

The Rise and Fall of Knowledge Monopolies

While consulting firms are actively embedding AI into their workflows, the reality is that they still face major challenges in making it truly effective. These firms are built around human expertise, strategic insight, and deep client relationships, not AI development. Their core strength lies in consulting, not in building or mastering AI technologies. That is why when a tech-native company with AI at its core enters the consulting space, it creates a wave of concern across the industry.

OpenAI, the company behind ChatGPT, is no longer just licensing models—it is entering the consulting space directly. By embedding elite engineers into client teams, OpenAI is building custom GPT-4o models, domain-specific copilots, and AI agents that automate complex workflows.

With pricing starting at $10 million per engagement and clients like Grab and the U.S. Department of Defense already onboard, OpenAI is positioning itself as a serious contender in enterprise AI consulting.

OpenAI’s approach, inspired by Palantir, focuses on execution rather than advice. Their pitch is simple: “No slide decks. Just working AI inside your systems.” This model—AI-as-a-Service—delivers results in weeks, not quarters, and bypasses traditional consulting firms. As a result, clients are rethinking their vendor choices, asking why they should pay millions for strategy documents when OpenAI can build and deploy the solution directly

The impact is profound. Big consulting firms are being pushed down the value chain, taking on roles like AI auditing, compliance reviewing, and integration support. While still relevant, they are no longer seen as the primary drivers of AI transformation.

OpenAI’s FDE program is designed to overcome enterprise bottlenecks, offering hands-on engineering, rapid deployment, and measurable business outcomes. Engineers map business processes, design bespoke AI architectures, and transition systems from proof-of-concept to production—all within a few months.

OpenAI is also building a global FDE team headquartered in major tech hubs like New York, London, Singapore, and Tokyo. With compensation packages ranging from $220,000 to $280,000 plus equity, the firm is attracting top talent and reshaping the consulting talent market.

By 2026, OpenAI expects up to 40% of its enterprise revenue to come from FDE-led engagements, with each dollar spent on services generating up to five dollars in infrastructure and API usage

What AI Can Do That Consultants Used to Own

While AI seems to be a major reason why traditional consulting is losing relevance, there’s a deeper, hidden problem that has gradually unfolded in the public eye. The consulting industry—once revered in the 1980s and 1990s for its role in corporate restructuring, mergers, and strategic planning—has increasingly been criticized for being bloated, profit-driven, and sometimes disconnected from real business outcomes.

Many firms have shifted focus from solving core problems to selling frameworks, roadmaps, and long-term engagements that prioritize revenue over impact. As clients become more tech-savvy and results-oriented, they’re questioning the value of expensive slide decks and slow delivery cycles.

Consulting industry also faces a crack down from the government. Under the Trump administration, Elon Musk and his allies at the Department of Government Efficiency took a chainsaw to federal contracts, arguing that no client had been exploited more than the U.S. taxpayer. A GSA inspector general’s report had already found McKinsey overcharging by 10 percent, costing $65 million. That set the tone.

Within weeks of Trump taking office, DOGE canceled more than 1,000 contracts—including Deloitte’s $1.9 billion IRS tech deal—many because they contained language on diversity or climate change. Booz Allen Hamilton, which makes nearly all its money from federal work, saw part of its contract terminated for those reasons.

Soon after, Josh Gruenbaum, the new procurement chief, sent letters to the ten biggest contractors demanding they justify their work and identify waste in plain language. Anything less, he warned, would be deemed “not credible.”

The firms scrambled. By May, they pledged $33 billion in savings, $9 billion of it immediate. By June, the GSA had canceled 2,800 contracts and was reviewing 20,000 more. The financial toll was heavy: Deloitte prepared layoffs, Accenture reported shrinking sales, and Booz Allen cut 2,500 jobs. Stocks across the sector tumbled.

Still, Booz Allen’s CEO Horacio Rozanski framed the cuts as a chance to prove value, insisting the government would ultimately need the firm’s technology and expertise. But Gruenbaum made clear the administration’s stance: if services weren’t essential—or could be handled internally—they would be cut.

What This Means for Your Career and Business

In The Economist article titled “The Consulting Crash Is Coming,” Joe Nocera draws a compelling parallel between the future of consulting and the disruption of legacy media industries.

“To get a sense of what consulting is likely to look like a decade from now, look at what streaming has done to the television business, or how the internet has disrupted the newspaper industry. Television and newspapers still exist, but they are a diminished force, with declining revenue, lower profits, and less cultural clout. That is what is about to happen to consultants,” he noted.

Looking ahead, consulting may resemble the media industries it’s being compared to: still present, but fundamentally changed. Firms will need to pivot toward specialized services, integrate AI into their core offerings, and rethink how they deliver value.

The prestige and influence that once defined the consulting world are under pressure, and as Nocera suggests, the industry isn’t dying, it’s being reshaped. The question is no longer whether consulting will survive, but how it will evolve in a world where expertise is increasingly democratized and commodified.