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History is full of moments when a transformative technology reshapes an entire sector. Steam power remade manufacturing. Electricity remade industry. The internet remade commerce. Artificial intelligence (AI) is remaking everything. And within that vast transformation, few sectors are more exposed than the legal industry.
I spent more than 30 years in corporate law, working across major law firms and multinational corporations, including as General Counsel (GC) of two large public companies. My career stretched across Europe, Asia, the United States, and the Middle East, in executive roles spanning multiple industries. In that time, I have watched the legal profession evolve from the tentative adoption of email and document management systems to the rise of sophisticated legal operations teams and the growth of alternative legal service providers (ALSPs). Yet, nothing in those decades compares with the scale, speed and impact of the transformation now underway.
The disruption will not come from government regulators. Nor will it primarily come from ALSPs, though they will play their part. It will come from the client.
Over the next several years, corporate legal departments will undergo a profound transformation as the corporations they serve reorganise themselves around AI.
As multinational corporations (MNCs) redesign their entire operating models around AI, their legal departments will transform in step. The result will be a client base that is faster, smarter, more technologically capable, and far less dependent on outside counsel than at any prior point in the profession's history. Law firms, leveraging a 19th-century operating model that depends on leveraging the hourly input costs of a large base of relatively junior lawyers, will struggle to adapt.
The Client Is Transforming - Faster Than Firms Realise
To understand why general counsel GCs are becoming the agents of disruption, it helps to understand what is happening inside the companies they serve.
AI is what economists call a general-purpose technology: a breakthrough with pervasive reach, rapid improvement, and the capacity to catalyse cascading complementary innovations. Like electricity or the combustion engine before it, AI does not merely optimize existing processes; it reconfigures entire industries, redefining how companies are structured, how they compete, and how they create value.
MNCs are responding by undergoing their most profound structural transformation in decades. They are building integrated digital platforms - what Harvard Business School professors Marco Iansiti and Karim Lakhani call "AI factories" - that remove human and organisational bottlenecks from critical workflows, enabling decisions to be made at machine speed, at near-zero marginal cost, and with ever-improving accuracy.1 These digital operating models scale, scope, and learn in ways that analogue organisations simply cannot match.
Legal departments, historically the caboose on this train, are now being pulled into the locomotive. A GC relying solely on traditional human resources to serve a business that can generate dozens of contract variations in the time it once took to produce two, and expects legal review in days rather than weeks, faces an impossible task without technological transformation. The “more-for-less” pressure that has long plagued legal departments - to do more work, more quickly and at a lower cost - is now being met not with resignation but with new capability. AI is allowing even lean teams to punch well above their weight.
By 2024, 95% of GCs reported their departments were engaging with generative AI.2 Nearly three-quarters of legal operations professionals believed it would become essential to the profession.3 The transformation from the lean, multidisciplinary department of the 2010s to the platform-driven legal function of the AI era is already underway.
What an AI Factory Looks Like
At the heart of this corporate transformation is the AI factory, a company-wide operating model built around an integrated platform of data pipelines, algorithms, and software infrastructure. The logic is self-reinforcing: data is continuously collected and fed into algorithms that identify patterns and generate predictions; those predictions are tested, refined, and fed back into the system; and the system learns, improves, and scales, largely without human intervention in the critical path.
For MNCs undergoing digital transformation, the journey toward an AI factory typically moves through several stages, from fragmented data silos, through pilot analytics projects and enterprise data hubs, to a fully integrated, AI-powered operating model. It is this final stage that removes traditional constraints on scale, scope, and learning, and enables companies to grow faster, adapt more rapidly, and capture more value than analogue competitors can match.
Why are so many companies investing in AI? It has to do with the structural models these systems enable. Unlike traditional operating models, which hit ceilings of complexity and cost as they grow, AI factory models improve with scale. The more users, transactions, and data they absorb, the faster and more accurate they become. Amazon's recommendation engine, Tesla's Full Self-Driving system, and Walmart's omnichannel retail platform all operate on this logic: data generates insight, insight drives action, action generates more data, and the flywheel accelerates. That flywheel creates increasing returns that shift markets toward “winner-takes-most” dynamics. The first mover captures most or all of the value in the market, making it hard for followers to catch up.
This is why global AI spending is accelerating at an unprecedented rate. According to Gartner, worldwide AI spending is expected to reach nearly $2.6 trillion in 2026, up nearly 48% from 2025. By 2027, spending is projected to approach $3.5 trillion, representing almost a doubling in just two years and a compound annual growth rate of more than 40%.4 Indeed, Microsoft, Amazon, Alphabet and Meta are alone expected to spend approximately $725 billion on technology capital expenditure in 2026.5 To put that in perspective, that is more than the combined defence budgets of all European NATO members ($559bn) and nearly four times Russia’s annual defence budget ($190bn).6
These are extraordinary numbers because the stakes for companies are extraordinary. They understand that, given the “winner takes most” dynamics exhibited by first movers, AI is increasingly becoming a source of competitive survival.
The race is no longer simply to adopt AI but to redesign the enterprise around it. That is why companies are investing in the infrastructure, data architectures, models, agents, workflows, and operating systems required to build AI factories.
Legal departments, embedded within these enterprises, are being pulled into that same transformation.
The Architecture of the GC 4.0 Legal Department
What does this transformation look like in practice? The AI-era legal department will be organised around a layered architecture with technology at its core.
At the base sits an expanded legal operations team, no longer confined to vendor management and e-billing, but now serving as the strategic engine responsible for technology selection, data governance, AI adoption, and integration across enterprise systems. Above that foundation lies an integrated technology platform: an intelligent system that handles intake and triage, manages knowledge and data, deploys AI-powered applications, and provides governance and oversight. Agentic AI systems (autonomous, goal-driven agents capable of executing multi-step workflows with minimal human supervision) are increasingly embedded across this platform, further reducing the need for routine human intervention.
Built on this foundation are human specialists and generalists: lawyers who draw on the platform's capabilities to operate with greater speed, reach, and precision than was previously possible. Workday’s legal department offers one model of this. It is in the process of building toward an AI-first ecosystem with persona-based AI agents, a unified data layer, and an agentic "front door" that routes matters autonomously before they ever reach a human lawyer.
The operational gains of AI-enabled departments will be significant. JP Morgan's COIN contract intelligence system provides a harbinger of things to come. It reduced contract review time from 360,000 lawyer-hours per year to mere seconds in its first year of operation.7 Workday's Evisort contract tool is saving the department over 45,000 hours per quarter. AI-powered intake systems can route and manage work at scale with near-zero marginal cost.8
These are not incremental improvements. They are structural transformations that fundamentally alter what in-house teams will need - and expect - from outside counsel.
What Transformed Clients Will Expect
The implications for law firms, which will be significant, are often underappreciated. Three dimensions in particular stand out.
First, work that was once automatically sent outside is increasingly being done in-house. AI enables legal departments to handle growing volumes of more complex work, including increasingly sophisticated document review, contract drafting, compliance analysis, and regulatory monitoring, at dramatically lower costs and with significantly greater consistency. One study estimates that up to 20% of legal services could become commoditized as AI improves, potentially resulting in 80% fewer billable hours on such work and price reductions of as much as 50%.9
Second, for work that remains externally sourced, the expectations are shifting fundamentally. AI-era clients will not want a law firm that delivers advice as if it were operating independently of the client's own systems and workflows. They will want partners who can integrate seamlessly into their digital platforms, share data, align with their processes, and deliver at the speed that technology enables. Competitive advantage, for both legal departments and their outside counsel, will increasingly lie in the integration of people, processes, data, and technology, not merely in the quality of individual legal minds.
Third, clients will have unprecedented visibility into what they are buying. Real-time dashboards, predictive analytics, and AI-powered procurement platforms are already enabling GCs to compare law firm bids across panels, benchmark performance across providers, and apply data-driven scrutiny to every invoice. The information asymmetry that long underpinned law firm pricing power is eroding.
The Structural Misalignment of the Traditional Model
Against this backdrop, the traditional law firm model faces a deepening structural mismatch.
That model rests on two pillars: leverage and the billable hour. If leverage (the ratio of salaried professionals to equity partners) is the engine of profitability, the billable hour is the fuel. Both incentivize firms to maintain large cohorts of lawyers working long hours, billing time to clients regardless of whether time spent reflects value delivered. As of 2025, at least 80% of legal matters still use hourly billing, with most purported alternatives quietly underpinned by the same hourly logic.10
This model has been extraordinarily successful. In 2025, revenue per lawyer among the Am Law 100 climbed to $1.39 million (+8.7%), while profits per equity partner (PEP) reached $3.59 million (+14.0%). These gains outpaced inflation by a factor of three to five. At the very top of the market, the most profitable firm generated more than $12 million in profits per equity partner, underscoring the extraordinary economics of the elite tier of the legal industry.11
But a closer look reveals an uncomfortable tension. In a 2024 Axiom survey, 96% of GCs reported legal budget cuts averaging 11%, with the deepest reductions at companies exceeding $1 billion in revenue. At the same time, 81% of GCs said they were critically understaffed, with 100% indicating that at least some of the work they outsourced could have been handled in-house if they had the right resources, signalling a desire to bring more of it in-house over time.12
This is not a temporary dissatisfaction. It is the early signal of an inflection point.
Clayton Christensen's model of the innovator's dilemma is instructive here. Dominant incumbents rarely fail because they are incompetent. They fail because they are too well-adapted to the world that is passing. Nokia was not a poor handset maker in 2007; it was the world's best. What it missed was that the game was shifting from hardware to software ecosystems, and by the time it tried to pivot, Apple and Google had already redefined the terms of competition.
Law firms risk a similar dynamic. Their structural features, including partnership models with short time horizons, limited access to external capital, siloed practice groups with misaligned incentives, and a billable hour model that penalises efficiency, make it genuinely difficult to transform at the pace and scale that the AI era requires. And record profitability, rather than providing a runway for transformation, can serve to mask the early warning signals.
The Catalyst, Not Just the Client
What makes this moment different from prior cycles of legal innovation is that clients are building and deploying that technology themselves, and their transformation will force the transformation of the entire legal ecosystem.
In prior eras, law firms could reasonably wait for clients to ask for something different. Now, the clients are not waiting. They are building AI factories, deploying agentic systems, and redesigning their legal operations around platforms that enable scale, scope, and continuous learning. As they do so, they will look at the law firm model - built as it is for a pre-digital age, with a pricing structure based on time rather than on value, and with humans organized in silos - and they will increasingly route their work elsewhere.
Competitors are waiting in the wings. The global ALSP market is growing at an 18% compound annual growth rate and is projected to reach $50 billion by 2033.13 Private equity is consolidating adjacent professional services sectors with speed and ambition. New platform models (technology-enabled marketplaces that orchestrate legal work across multiple providers) are beginning to embed themselves into corporate legal department workflows. Hybrid models, inspired by the Big Four auditing firms, are integrating legal advisory with risk analytics, compliance consulting, and legal technology solutions under one roof.
Against this backdrop, the legal services landscape is being fundamentally reorganised. The question for law firms is whether they will be among those who shape it or among those who get displaced.
What Comes Next
The legal profession is not facing the end of expertise. Complex, high-stakes, genuinely bespoke legal work will remain valuable, perhaps even more so, as the baseline of what technology can handle rises, making true judgment increasingly rare and therefore more prized.
But the volume of work that fits that description is smaller than most firms believe. And the expectations attached to the rest, including speed, integration, efficiency, and data-driven transparency, are about to change fundamentally.
Law firms that respond thoughtfully can find significant opportunity in this moment. Those that experiment with new models, invest in platforms and technology, adopt outcomes-based pricing, and position themselves as genuine partners in their clients' digital transformations, rather than independent advisors operating at arm's length, will be well placed for what comes next.
Those that wait for the metrics to confirm the inflection point before acting may find, as Hemingway's character did, that change arrives in two ways: gradually, then suddenly.
Endnotes
1. Marco Iansiti and Karim R. Lakhani, Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World (Boston: Harvard Business Review Press, 2020).
2. Deloitte Legal, “How Generative AI Is Changing Legal Department Functions,” Deloitte, September 6, 2024, https://www.deloitte.com/global/en/services/legal/perspectives/how-generative-ai-is-changing-legal-department-functions.html.
3. Blickstein Group, “17th Annual Law Department Operations (LDO) Survey Report”, presented in collaboration with FTI Consulting, 2024, https://www.blicksteingroup.com/law-department-operations-survey, 5.
4. Matt LoDolce and Meghan Moran, “$2.59 Trillion in AI Spending Dominated by Vendors and Hyperscalers, with Enterprises Yet to Flex Spending Potential,” Gartner, May 19, 2026, https://www.gartner.com/en/newsroom/press-releases/2026-05-19-gartner-forecasts-worldwide-ai-spending-to-grow-47-percent-in-2026
5. Myles Udland, “‘Magnificent 7’ Earnings Rush Reveals AI Spending Surge, with Hyperscaler Capex Set to Reach $725 Billion in 2026,” Yahoo Finance, April 29, 2026, https://finance.yahoo.com/markets/article/magnificent-7-earnings-rush-reveals-ai-spending-surge-with-hyperscaler-capex-set-to-reach-725-billion-in-2026-224901707.html.
6. Stockholm International Peace Research Institute (SIPRI), “Global Military Spending Rise Continues as European and Asian Expenditures Surge,” press release, April 27, 2026, https://www.sipri.org/media/press-release/2026/global-military-spending-rise-continues-european-and-asian-expenditures-surge.
7. GoBeyond.ai Team, “How JP Morgan Uses COIN AI to Automate Contract Analysis and Revolutionize Legal Document Processing,” GoBeyond.ai, July 27, 2025, https://www.gobeyond.ai/ai-resources/case-studies/jpmorgan-coin-ai-contract-analysis-legal-docs.
8. Based on information provided by Workday, including written materials and conversations, with the author.
9. Thomson Reuters, 10, “The Future of the Law Firm – No Time for Bystanders Amid AI’s Increasing Influence”, Thomson Reuters, 2025, https://legal.thomsonreuters.com/en/insights/white-papers/future-of-law-firm-amid-ai-increasing-influence/form?gatedContent=%252Fcontent%252Fewp-marketing-websites%252Flegal%252Fgl%252Fen%252Finsights%252Fwhite-papers%252Ffuture-of-law-firm-amid-ai-increasing-influence, 10.
10. Robert J. Couture, “The Impact of Artificial Intelligence on Law Firms’ Business Models,” Harvard Law School Center on the Legal Profession, February 24, 2025, https://clp.law.harvard.edu/knowledge-hub/insights/the-impact-of-artificial-intelligence-on-law-law-firms-business-models/; and Steven J. Harper, The Lawyer Bubble: A Profession in Crisis (New York: Basic Books, 2013), 171.
11. LawFuel Staff, “$12 Million Paydays, a $10 Billion Firm, and Biglaw’s Best Run in Years,” LawFuel, April 2026, https://www.lawfuel.com/infographics/amlaw100-2026-enhanced.html.
12. Axiom Law, “View from the Top: GCs’ 2024 Outlook on Legal Budgets, Talent, and Innovation,” March 29, 2024.
13. Thomson Reuters Institute, “Alternative Legal Services Providers 2025,” January 2025, https://www.thomsonreuters.com/en-us/posts/wp-content/uploads/sites/20/2025/01/ALSP-Report-2025.pdf; and Grand View Research, “Alternative Legal Service Providers Market Size, Share & Trends Analysis Report, 2025–2033,” June 2025, https://www.grandviewresearch.com/industry-analysis/alternative-legal-services-providers-market-report.
