Professional Services Caught in AI’s Crossfire: Disrupted from Inside and Out

([1])The advisory industry is grappling with twin “AI nightmares”: first, that generative AI’s tendency to produce confident errors could undermine the hard-won trust at the core of consulting and legal work, and second, that if AI works as well as advertised, the tech companies behind it – armed with firms’ own client data – might "cut the middleman out" entirely and render traditional advisors less necessary ([2]). In response, established firms are making unprecedented moves to harness AI rather than be displaced by it.

One prime example is KPMG’s recent alliance with Anthropic, announced in late May. The Big Four giant will integrate Anthropic’s Claude model deeply into its systems, effectively giving all 276,000 of its professionals across 138 countries access to a "Claude-powered" advisory platform ([3]). This sweeping commitment – the broadest AI rollout by any Big Four firm to date ([4]) – aims to both supercharge the efficiency of KPMG’s consulting, tax, and audit services and safeguard its relevance as clients adopt AI of their own. (PwC struck a similar deal with Anthropic that same week ([5]).) By partnering with an AI frontier provider, KPMG is betting it can mitigate AI’s trust issues through a controlled, firm-wide toolset, and simultaneously ensure it remains embedded in clients’ AI transformations rather than being leapfrogged by them.

Other major consultancies are likewise retooling their operations with AI. McKinsey, for instance, has developed a proprietary AI assistant called Lilli that acts as a "virtual team member" for consultants ([6]). This internal tool can rapidly generate slide decks, conduct research, and synthesize data, taking over many tasks once handled by junior analysts ([7]). Since its launch in 2023, Lilli has been enthusiastically embraced by staff – three-quarters of McKinsey’s employees now use it, collectively submitting over 500,000 prompts per month for help with their work ([8]). McKinsey says these AI systems are already saving consultants ~30% of the time they used to spend searching for information and drafting presentations, amounting to more than a million work hours saved so far ([9]). In other words, the traditional pyramid model of armies of junior researchers is giving way to a leaner structure, as AI shoulders the grunt work.

Crucially, firms recognize that embracing AI at scale requires a cultural shift and new guardrails to preserve quality. KPMG has instituted a firmwide "Think, Prompt, Check" training program to instill responsible AI usage, teaching its professionals how to craft better prompts and rigorously interrogate AI outputs ([10]). Deloitte, rolling out a ChatGPT-powered assistant called "PairD," likewise mandates that staff complete training and perform their own due diligence on the AI’s outputs to ensure accuracy and compliance ([11]). By upskilling their people and embedding AI into everyday workflows, big advisory firms hope to capture AI’s upsides (speed, scale, and cost-efficiency) while containing its risks – and demonstrate to clients that they can deliver tech-enabled insights, not just slide decks.

Even as firms race to reinvent themselves, their clients are rapidly gaining AI capabilities – and that upends the old advisor-client dynamic. Nowhere is this more evident than in the legal field, where in-house counsel have been quick to seize on generative AI tools. Corporate legal departments more than doubled their use of gen AI in the past year (from 23% to 52%), and 64% of in-house teams now expect to depend less on outside law firms thanks to the AI they’re building internally ([1]). General counsel are starting to demand transparency about whether their external lawyers are using AI on their matters ([2]). Law firms that can’t demonstrate strong AI capabilities – and seamlessly integrate with clients’ tech-enabled processes – risk seeing their work dry up.

The same pattern is emerging beyond legal. CFOs surveyed in early 2026 identified "building AI talent" within their finance teams as their top challenge for the next six months – ranking it even above technology or budget issues ([3]). Many CFOs are investing heavily in AI tools and upskilling internal staff so they can perform complex analysis, financial modeling, and reporting in-house – tasks they might previously have hired consultants or accountants to do. Even governments are moving toward AI self-sufficiency; Canada’s federal budget for 2025, for example, explicitly aimed to cut the use of external consultants by rolling out a homegrown AI platform across departments ([4]).

This self-service trend is putting acute pressure on professional firms’ revenues and pricing. If AI can compress work that once took weeks into hours, clients are asking why they should continue paying by the hour for it. Analysts observe that companies are increasingly pushing for outcome-based or fixed-fee engagements, insisting they pay for results delivered rather than hours logged ([5]). Nearly one-third of law firm leaders predicted that AI would force changes to billing models, yet so far none have actually made such changes ([6]). In short, as clients gain the ability to do more with AI and data on their own, they are less willing to fund the old leverage model of massive hourly bills – unless external advisors can offer clear value beyond what AI provides.

A third source of disruption comes from new entrants born with AI at their core. This month, startup Superlegal launched what it calls the first AI-powered law firm in the US, focused on serving the $2.1 trillion construction industry ([1]). Superlegal’s platform uses a custom-trained AI to review and redline contracts with a human lawyer providing final oversight. Critically, its business model is built on fixed, transparent pricing: reviews start at about $117 per contract ([2]), versus the roughly $500 per hour typically charged by traditional law firms ([3]). By delivering faster turnaround (often under 24 hours) at a dramatically lower price point, this AI-native firm aims to win business that might otherwise go to high-cost outside counsel.

Meanwhile, the big technology players themselves are eyeing the professional services domain. Industry watchers note that at least three tech giants – OpenAI, Anthropic, and Microsoft – have all set their sights on the legal market ([4]). In a telling move, OpenAI recently hired the founder of a major contract management startup to lead its new initiative for AI legal products ([5]). When the creators of advanced AI begin delivering solutions directly to end clients, they effectively become competitors to the consultants and lawyers who used to implement those solutions. As one expert put it, it’s “weird” to see AI companies building their own consulting arms – a move that appears to contradict the very premise of user-friendly generative AI tools ([6]). Still, it underscores the reality that both startups and tech titans are converging on professional advice markets, bringing a product-like, tech-driven approach that challenges incumbents.

Together, these AI-native challengers are putting a pinch on the legacy firms by targeting profitable niches and offering scalable, software-driven alternatives. They are often more nimble and capitalized by eager investors (Superlegal itself raised a seed round backed by the former CEO of Thomson Reuters and Google’s AI fund) ([7]). The implication for traditional firms is clear: no segment of the consulting, legal, or accounting value chain is safe from reinvention. Firms must decide where they can truly excel and add irreplaceable value, and where they should partner with or even white-label emerging AI solutions before someone else steps in.

All of these developments lead to a fundamental question: What will "expert human judgment" mean in an AI-driven professional world? With intelligent systems increasingly handling research, analysis, and even first-draft writing, the human advisor’s role is shifting to higher-order skills. Top firms claim human expertise remains indispensable – indeed, a recent study found that none of the largest law firms plan to reduce their lawyer headcount despite achieving 100-fold productivity gains on some tasks with AI ([1]). And McKinsey’s CEO Bob Sternfels has emphasized that “we don’t see tech as replacing consultants… far from it. We see it augmenting us” ([2]) – reflecting a widespread belief that AI will complement, not substitute, human advisors.

Realizing this vision, however, will require tangible changes. KPMG executives argue that the most successful professionals will be those who use AI as a "reasoning partner," effectively becoming supercharged "cyborgs" who seamlessly integrate AI into their problem-solving process ([3]). In this paradigm, AI assumes the grunt work as a tireless team of "helpers," enabling human experts to focus on nuanced judgment, creativity, ethical decision-making, and interpersonal advice that machines cannot replicate ([4]). Achieving that balance means rethinking recruitment, training, and career paths so that human judgment is continually elevated by AI, not sidestepped by it.

For C-level leaders, the takeaway is that the traditional leverage and billing models of professional services are on the brink of a profound transformation. AI demands that firms deliver more tangible value and efficiency to clients – or those clients will either build the capability themselves or turn to tech-enabled competitors. The next era of consulting and advisory won’t hinge on who has the most bodies to bill, but who best combines smart algorithms with truly expert human judgment. The firms that survive and thrive will be the ones that embrace AI as an ally and prove that their counsel, enhanced by technology, is worth every penny.