AI disruption from inside and out: professional services at a crossroads.

([1])Kirkland & Ellis – the world’s highest-grossing law firm – is making a stunning $500 million investment to build a proprietary AI platform, with an explicit goal of killing the billable hour. The firm’s chair, Jon Ballis, says this enormous bet isn’t about shaving a few hours off legal tasks, but about fundamentally changing how they price and deliver work. Kirkland’s new in-house AI will capture the firm’s collective expertise and automate data-heavy tasks, enabling its lawyers to become high-value "intelligence lawyers" delivering insight at scale rather than selling time ([2]). As Ballis bluntly put it, widely available AI tools are “raising the floor for everyone” – in other words, baseline work is becoming a commodity, and "we don’t get hired for the floor" ([3]). In this new reality, simply billing more hours is not a viable strategy.

([4]) ([5])It’s not just law firms feeling the pressure. The most elite strategy consultancies – McKinsey, BCG, Bain – have quietly begun rewriting their fee models as AI slashes the time and effort required for analysis. McKinsey revealed that roughly one-quarter of its global fees are now tied to outcomes rather than hours ([6]), meaning clients pay for results delivered instead of time spent. BCG has told investors it expects around 40% of its revenue to be driven by AI-related work by the end of 2026 ([7]). The math is unavoidable: when internal AI tools like McKinsey’s “Lilli” chatbot are handling up to 30% of consultants’ analytical work ([8]), the traditional pyramid model – built on armies of junior staff churning through data for billable hours – starts to crack. Time-based billing is beginning to look like a tax on inefficiency in a world where machines accelerate the work ([9]). To maintain profits, firms are experimenting with performance-based contracts, value pricing and other models that share the efficiency gains with clients ([10]).

([11])Meanwhile, the Big Four are confronting a similar imperative under even more direct client pressure. This week’s news that KPMG is axing around 400 U.S. advisory roles – about 4% of its consulting arm – lays bare the changing demand landscape ([12]). For years, corporations poured money into digital transformation and compliance projects, but now that spend is softening as some clients deploy in-house AI solutions and pause discretionary projects ([13]). KPMG’s cuts target slower-growth service lines, and notably spare its deal advisory and strategy groups ([14]) – the very areas it expects to drive future growth. The firm is simultaneously hiring for “AI transformation” roles ([15]), reflecting a pivot: doubling down on technology and engineering expertise to deliver the faster, outcome-focused projects clients want. The takeaway is stark – the era of easy money from conventional advisory work is ending, and efficiency and results are trumping headcount as the basis for revenue.

([1]) ([2])As incumbents scramble to adapt, they face a pincer movement from technology giants and AI-born competitors. OpenAI – the very company whose ChatGPT sparked the current AI gold rush – has itself entered the consulting arena, working directly with enterprises on high-end AI projects ([3]). OpenAI’s strategy of embedding its own engineers within client organizations promises “AI-as-a-Service” with no middleman – “no slide decks, just working AI inside your systems,” as the company reportedly pitches ([4]). This week brought renewed attention to that approach as details emerged of OpenAI landing deals like a $200 million contract with the U.S. Department of Defense ([5]). For Big Four and global consultancies that have long profited from acting as interpreters between tech providers and corporate clients, the message is unnerving: the tech providers are coming for their turf.

([6]) ([7])Even when technology firms aren’t going solo, they’re finding powerful partners. IBM’s announcement of a broad alliance with OpenAI on August 13 exemplified how lines are blurring ([8]). IBM Consulting will integrate OpenAI’s latest models like GPT‑5.6 into its delivery platform and retrain tens of thousands of consultants on OpenAI tech ([9]). The goal is to offer ready-made generative AI solutions for industries from finance to government, using OpenAI’s most advanced capabilities under IBM’s trusted brand. It’s a shot across the bow for other IT and advisory firms – if they can’t offer clients the caliber of AI available from the top model makers, someone else will. No wonder many consultancies are rushing to ink their own AI partnerships or build proprietary platforms.

([10]) ([11])Perhaps even more disruptive is the rise of AI-native professional services firms. In the legal arena, Blackstone-backed startup Norm Law just opened a Washington, D.C. office to get closer to federal clients ([12]). Billed as an “AI-native law firm,” Norm Law runs on a custom AI platform (Norm Ai) that handles tasks like document review and drafting, allowing a single attorney to do the work of a whole junior team ([13]). The firm’s senior lawyers oversee and refine AI agents, blending technology with traditional counsel to ensure quality. Significantly, Norm Law prices many services based on outcomes instead of billable hours – delivering what it calls "the speed and efficiency of AI while preserving the judgment and accountability clients require" ([14]). In other words, it’s directly attacking the inefficiencies of Big Law with a leaner, tech-powered model. The implication for established firms is clear: tomorrow’s competition may have a fraction of the headcount and overhead, yet still handle complex work faster and cheaper by leaning on AI.

([15])Clients are also embracing tools that reduce their reliance on outside advisors. For example, a new AI platform called Datagnome launched this month to help corporate legal departments automate contract review, claiming it can cut review times by up to 40% ([16]). In practice, that means in-house teams might no longer need to farm out time-consuming document work to law firms or LPOs – or at least they can drive tougher bargains on price and turnaround. Likewise, CFOs and CIOs are adopting generative AI for data analysis, coding, and strategy support, chipping away at bread-and-butter work that consulting and advisory firms once assumed was theirs. As one industry survey starkly concluded, "consulting as we've known it is over" if firms can’t deliver outcomes at AI’s pace ([17]) ([18]).

([1])Even as software automates an increasing share of research, modeling, and documentation, these advances are highlighting a new premium on human judgment. Bloomberg’s latest AI-powered legal research tools can surface relevant information and draft answers in seconds ([2]) – but lawyers still must decide which insights truly matter and what to do next. That point wasn’t lost on Bloomberg Law, which emphasized at this week’s ILTACON conference that faster analysis alone isn’t enough if legal teams can’t determine how to act on AI findings ([3]). Similarly, E-discovery company Relativity is piloting a chatbot interface called “claiR” to help lawyers query documents more naturally, yet it remains a guided tool for skilled attorneys rather than a replacement for them ([4]).

([5])The reality is that harnessing AI’s potential requires more than simply provisioning the latest tools – it demands new skills and metrics. A KPMG analysis of 1.4 million interactions with AI found that only 5% resulted in “meaningful outcomes” ([6]), echoing a Fortune report that 95% of corporate generative AI pilots failed to show significant results ([7]). In many cases, early adopters fell victim to the hype, deploying AI without clear objectives or organizational readiness. Firms are learning that achieving real ROI from AI means focusing on the right use cases, upskilling staff to become "sophisticated AI users" ([8]) and establishing new processes to monitor value. Notably, only 18% of professionals say their organizations even track ROI on AI initiatives today ([9]) – a worrying blind spot as expensive AI investments ramp up.

([10]) ([11])All of this raises the question: what will “expertise” mean when clients have AI at their fingertips? The answer lies in what machines cannot do. Leading firms suggest the future of professional services will hinge on combining technology with human insight, not substituting one for the other. KPMG’s US CEO put it plainly: clients come to firms “where accuracy, judgment and knowledge matter most” ([12]). It’s the nuanced understanding, strategic creativity, ethical guidance, and industry wisdom – the true “collective intelligence” of an experienced firm – that remain inimitable. According to a new Thomson Reuters report, the winners will be those who leverage AI to elevate the kind of strategic and analytical thinking that sets top professionals apart ([13]). In practice, that means refocusing talent development on higher-order advisory skills and domain expertise, while letting AI handle repetitive analytical tasks.

In an era when clients can get a quick answer from a chatbot or a pre-trained model, professional services leaders must ask themselves: how will we add value now? The likely outcome is a redefinition of roles and offerings. Instead of serving as mere providers of information or process, tomorrow’s consultants, lawyers, and accountants will be curators of insight, validators of AI outputs, and partners in navigating complex, high-stakes decisions. As one ILTACON session title aptly put it, “AI Can Do the Work. Now What?” ([14]) The firms that thrive will be those that can answer that question – by proving their human experts plus AI deliver better decisions and outcomes than either alone.