AI’s Double Disruption: Consulting & Law Must Reinvent or Be Replaced

Consultancies and professional service firms are fundamentally shifting from traditional advice-driven models toward AI-powered execution platforms ([1]). Rather than selling slide decks and billable hours alone, leading firms are embedding 'agentic' AI tools, governed workflows, and reusable digital assets directly into their core offerings ([2]). AI is no longer treated as a standalone service, but is woven into how solutions are delivered day-to-day.

One example is the alliance announced this week between IBM and Google Cloud. The two giants launched a new practice with thousands of IBM consultants to help companies scale AI deployments and modernize core systems, melding IBM’s industry expertise with Google’s advanced Gemini AI models ([3]). Similarly, PwC recently expanded its strategic partnership with Anthropic to integrate the Claude AI across its global operations, establishing a joint 'AI center of excellence' and training 30,000 employees on Claude to reinvent everything from deal advisory to finance functions ([4]).

The Big Four accounting and advisory firms in particular have invested heavily to infuse AI into audit, tax, and consulting work. EY now has 150 specialized AI agents assisting 80,000 of its tax professionals, and KPMG committed $2 billion to AI initiatives aiming to generate $12 billion in new AI-driven revenue ([5]). Deloitte’s in-house AI platform 'Zora' automates invoice processing, while PwC’s 'GL.ai' system reviews journal entries in audits – part of a broader push to run autonomous analysis on client data ([6]). These aren’t lab experiments; the largest firms have moved to production scale, spending more on AI in 2025–26 than many mid-sized companies spend on their entire IT infrastructure ([7]).

This internal automation is already reshaping the talent model. Why hire an army of junior analysts to crunch data or review documents when AI co-pilots can do it in seconds? Indeed, new graduate recruitment at the Big Four fell by 44% in a single year as entry-level work is increasingly handled by AI ([8]). Consultants and lawyers are shifting into roles overseeing AI-driven processes – focusing on higher-value tasks while machines tackle the heavy lifting.

At the same time, clients are becoming more self-sufficient thanks to user-friendly AI tools. One recent survey shows overall AI use across professional service organizations nearly doubled to 40% in 2026 (from 22% in 2025), and for the first time a majority of professionals have tried generative AI like ChatGPT . In the legal sector, nearly 70% of lawyers now use AI for work – more than double the prior year’s rate ([1]). With AI at their fingertips, many business teams are handling tasks in-house – from research and drafting to data analysis – that they once paid external advisors to do. As one Big Four insider admitted, clients 'don’t want a traditional MBA grad coming in with a slide deck and telling you how to cut costs' anymore ([2]). They expect more efficient, tech-driven results instead of old-school advice.

For law firms especially, these trends threaten the foundations of the billable hour model ([3]). Corporate legal departments are using AI to automate routine work and are now pushing back on outside counsel’s fees for tasks that technology makes faster. One general counsel even quipped that with AI enabling so much efficiency in-house, he’s 'glad I’m not the managing partner of a law firm' – implying that much of AI’s benefit will accrue to clients at law firms’ expense ([4]).

Pressure is mounting for new pricing models and demonstrable value. Why should clients pay by the hour for work that AI accelerates? Some firms have tried to preserve revenue by charging flat fees for tasks that now take a fraction of the time, but savvy clients are asking why they should pay the same for less lawyer or analyst effort . In the legal community, the American Bar Association has even advised attorneys to charge 'reasonable fees' that account for time saved by using AI, urging a shift toward billing for value delivered instead of hours worked . In the consulting arena, industry reports likewise point to a shift away from open-ended advisory fees and toward outcome-based, performance-tied contracts ([5]). In short, clients increasingly expect the efficiency gains from AI to show up in their bills – and they are prepared to seek alternative solutions if incumbents don’t adapt.

The rise of generative AI is also inviting non-traditional competitors into the market. In recent weeks, both OpenAI and Anthropic – the creators of ChatGPT and Claude – launched ventures to offer AI-driven advisory services directly to enterprises ([1]). OpenAI even acquired an AI consultancy (Tomoro, ~150 experts) to jump-start its new division, embedding these 'forward deployed' engineers inside client organizations to accelerate AI transformations ([2]). These well-funded AI labs are effectively targeting the $1 trillion consulting and tech advisory market ([3]), threatening to siphon off work that used to go to traditional firms.

Meanwhile, specialized startups are attacking lucrative niches once dominated by established players. For example, DiligenceSquared recently raised $5 million to automate the commercial due diligence that private equity firms typically pay top consultancies $500K–$1 M per deal to conduct ([4]). The platform uses AI voice agents and automated research synthesis to evaluate acquisitions faster and at lower cost. Its founders – veterans of Blackstone and BCG – argue that this kind of work is so 'highly standardized ... and sold at a massive markup' that it’s an ideal target for AI disruption ([5]).

Even the legal arena has seen the debut of an AI-driven firm. This week, a startup called Superlegal unveiled what it bills as the first AI-powered law firm in the United States, operating under a special regulatory sandbox to serve construction-sector clients directly ([6]). Superlegal’s proprietary system can review and redline contracts in under 24 hours for about $117 each (with a licensed attorney verifying each AI-assisted review) – a fraction of traditional legal costs. Early customers report that this model cut their contract review expenses by 90% and reduced turnaround times by 70% . By drastically lowering cost and delay on high-volume tasks, such AI-native firms pose a serious challenge to incumbent law firms’ bread-and-butter services.

To withstand this twin assault, incumbent firms are doubling down on what machines cannot replace: seasoned human expertise. Leaders insist they’ll embrace AI where it helps, but won’t try to beat the tech giants at their own game of building AI. Instead, success in the AI era will hinge on deep domain experience, creativity, and judgment. As Tony Alvarez of Alvarez & Marsal put it, his firm won’t compete head-on with OpenAI, but it has a unique 'restructuring DNA' earned over 40 years of turnarounds ([1]). Likewise, KPMG’s Lisa Fernihough touts the value of 'combining cutting-edge technology with deep sector expertise,' and PwC’s Claire Reid says their advantage 'lies in understanding how industries work' ([2]) – human insight fused with tech know-how that outsiders can’t easily match.

Some firms are even encoding their experts’ knowledge into AI systems to amplify their reach. A prime example is Kirkland & Ellis’s new partnership with Palantir: the law firm built an AI platform to streamline private equity fund formation work ([3]). This proprietary system effectively centralizes and compounds Kirkland’s institutional knowledge and workflows, embedding the firm’s expertise across its operations and making it available at scale throughout its 1,000-lawyer funds practice ([4]). As Kirkland’s leaders explained, combining their deep fund experience with Palantir’s technology allows them to deliver better value by applying their 'most senior judgment' to every client transaction through an AI-driven system .

Ultimately, the role of the human adviser is being redefined – not replaced – by AI. As intelligent systems handle more routine analysis and drafting, professionals are shifting from performing processes to supervising and refining the AI’s output ([5]). The consensus is that high-stakes, complex decisions – the kind that can make or break a company – will still demand human insight that no algorithm can replicate ([6]). In fact, with mundane tasks offloaded to machines, top consultants and lawyers might become even more valuable: freed to focus only on critical matters, they could command higher fees for their expertise . For both buyers and providers of advice, the priority now is to harness AI’s efficiencies while elevating the uniquely human judgment and strategic creativity that truly add value.