Professional services firms are navigating a period of unprecedented change.

Artificial intelligence, changing client expectations, evolving talent dynamics, alternative ownership models and increasing competition are challenging long-held assumptions about how professional services firms are structured, governed and grown.

Yet amidst the headlines, hype and speculation, an important question remains:

How much is really changing, and what should firm leaders actually be doing now?

At a time when many leaders are grappling with the pace and scale of change affecting their organisations, this webinar is an opportunity to take stock of the developments reshaping professional services and what they mean for firms in practice. By putting these trends into context and separating lasting change from short-term noise, our aim is to help leaders identify where they should focus their attention and the decisions that will shape their firms’ future direction.

Join us for a thought-provoking discussion exploring whether professional services are undergoing fundamental disruption or simply the next stage in their evolution.

Together, our panel will examine the practical implications of AI, private capital, changing workforce expectations, evolving client demands and new competitive threats, while sharing insights on how firms can adapt, innovate and thrive.

Topics will include:

  • Is the partnership model under threat, or experiencing a new lease of life?
  • What role will private capital and alternative ownership structures play?
  • How is AI changing client expectations, pricing and the delivery of professional advice?
  • Can firms capture and institutionalise knowledge before it leaves with key professionals?
  • Will AI and technology reshape traditional talent and leverage models?
  • Who are the real future competitors for professional services firms?
  • What practical steps should leaders take over the next 3-12 months?

Date: Wednesday 16 September 2026
Time: 9.00am-10.00am BST

Register here

Webinar Chair:
​Zulon Begum, Partner,  CM Murray LLP – Partnership and LLP Law Specialist

Guest Speaker:
Rutvik Rau, Co-Founder and CEO, August – Legal AI and Law Firm Transformation Specialist

PPA Speakers:
Corinne Staves, Partner, CM Murray LLP – Partnership and LLP Law Specialist
David Shufflebotham, Founder, PepUp Consulting – Partner Remuneration and Performance Evaluation Specialist
Rob Millard PhD, Director, Cambridge Strategy Group – Law Firm Strategy Advisor

We are delighted to share with you the recording of the recent Professional Practices Alliance (PPA) Webinar, Partner Remuneration: Trends, Pain Points & What Firms Are Changing in 2026. Listen to the recording above.

In this recording, Corinne Staves (Partner at CM Murray LLP), Zulon Begum (Partner at CM Murray LLP), Wonu Sanda (Senior Associate at CM Murray LLP) and David Shufflebotham (Founder at PepUp Consulting), Rob Millard PhD (Director at Cambridge Strategy Group) explore how firms are approaching partner remuneration in a period of rapid change.

In particular, the panel discuss:

  • AI and the billable hour tension: As efficiency improves, does time spent still reflect value – or are firms disincentivising change?
     
  • Evolution, not revolution (for now): Most firms are adapting incrementally – layering new expectations onto legacy systems rather than redesigning them.
     
  • Performance, profit and misalignment: An increasing gap between how firms say they create value and what they actually reward.
     
  • Complexity, discretion and challenge risk: Where more nuanced systems are increasing reliance on discretionary decision-making processes, evidence and consistency are critical.
     
  • Culture follows compensation: What firms reward ultimately shapes behaviour – raising questions about whether cultures can (or should) stay the same.
     
  • External pressure accelerating change: AI and external capital are pushing firms towards more data-driven, performance-focused models.
     
  • A clear direction of travel: Away from traditional lockstep and towards contribution, profitability and demonstrable value – but with no single model emerging.

If you have any questions arising from this recording or would like to discuss partner remuneration, governance or performance frameworks in more detail, please contact Corinne Staves or Zulon Begum (Partners at CM Murray LLP), David Shufflebotham (Founder at PepUp Consulting), or Rob Millard PhD (Director at Cambridge Strategy Group).

An exquisite irony

Johannes Trithemius was the Benedictine Abbot of Sponheim from 1483 to 1506. He was a polymath, a builder of libraries, and a deeply controversial character. He dabbled in the occult and was accused of inserting what we might now call “hallucinations” into his histories.

In 1492 he wrote a short book, De Laude Scriptorum (Eng: In Praise of Scribes). Movable-type printing having arrived a few decades earlier, his book was published in printed form in 1494. With exquisite irony, it defends the art of scribing at exactly the time that Gutenberg’s press was collapsing demand for handwritten texts and rendering scribes obsolete.

The book is sometimes held to be a medieval equivalent of a Luddite rant. Trithemius would have witnessed the economic impact on his own abbey. But his book is more than that. He appreciated the power of print to disseminate and democratise knowledge. His arguments tried to balance that against the organisational, professional, moral, and spiritual logic embedded in the older system of production.

Institutional memory

His first claim was about institutional memory. Without the scribe, he wrote, scholarly wisdom would never reach posterity. Writing gave “lasting value to passing things“. Without the written word, he warned, “justice [would be] lost, the law confused and the Gospel fallen into oblivion“. Printing, however, had the opposite effect to what he foresaw. It radically democratised written knowledge and drew into literacy many who had never read before. For lawyers, though, his raw claim is intuitive. Law is a system of memory and legal writing depends on faithful transmission. AI can retrieve, summarise, and generate legal language at a scale no human team can match. But is it reliable? Perhaps the question that Trithemius forces on us in this context today is a different one: what happens to legal memory when production is detached from disciplined professional formation? Following that, how can legal memory be safeguarded as AI continues to advance both in scale and complexity?

Durability

Trithemius’s second claim was about durability. Paper, he predicted, would quickly disappear. Parchment endured. He was only partly right. Many printed books have endured and the oldest are now treasured. This historical record shows, though, how often what was held to be true at one time has been shown to be false and has been supplanted by new, better knowledge. Clearly, clinging to old knowledge is risky in the absence of contemporary proof of its continued truth. This raw claim also translates well to the legal, digital world. The modern contrast is paper versus digital, and digital records can be deleted, altered, or lost with an ease that should trouble any custodian of legal memory.

A deep anxiety

Trithemius’s deeper anxiety was that the change in production technology would weaken the discipline that made texts worth preserving. Scribal labour added value, he thought, because it demanded attention, care, and inward absorption. “Every word we write is imprinted more forcefully on our minds,” he wrote, “since we have to take our time while writing and reading.”

This is perhaps his most directly modern, important point. Lawyers learn through friction. This friction comes through drafting, checking, revising, comparing, marking up, and being corrected. The process is often inefficient, but not all friction is waste. Some is cognitive apprenticeship. Some is ethical formation. Some is how professional judgement becomes embodied, and how the best answer to hard problems often emerges reluctantly and slowly – the slow thinking that Daniel Kahneman describes.

In this, Trithemius speaks most directly to firms wrestling with AI. Lawyers can see that AI may widen access to justice, improve consistency, cut cost, accelerate research, and help solve long-standing problems in service delivery. They welcome that. But they also worry, with very good reason, that if AI absorbs too much of the work through which junior lawyers become senior lawyers, the profession might lose the human capacity that gives the most difficult work (especially) its authority.

The need for disciplined human work

To reiterate, Trithemius’s book does far more than complain about the loss of his abbey’s revenue stream. He sought to defend copying as a practice that not only sustained institutions but also carried intrinsic societal worth. It fitted the monastery, he argued, because it aligned labour, discipline, learning, service, and identity. His most trenchant passage anticipates the obvious criticism. Why copy at all, he asks, when printing exists and “has brought to light so many important books“? His answer was not to reject printing. It was to deny that abundance removes the need for disciplined human work.

This parallel with law is direct. Legal work also combines knowledge production and formation. Associates produce documents and learn judgement. Partners supervise matters and transmit learning and standards. The firm sells advice and institutionalises its culture, risk appetite, and ways of producing that generally. AI need not destroy that, but it turns it into a design choice rather than an inherited feature of a now-outdated business model.

The scribe, Trithemius wrote, “is by no means defeated by the printer“. What he could not have foreseen, though, was just how far the democratisation of knowledge would run. The literacy of a whole society, rather than a small elite, produced benefits that dwarf what was lost. The Renaissance blossomed. Economic growth boomed. Entire new industries were formed. New forms of government emerged. It is hard to imagine how different the world would be today had printing never been invented.

Likewise, the lawyer is not today defeated by AI, and democratisation of the law will likely yield benefits and also challenges that are impossible to perceive ex ante. The essential task is to identify what carries the purpose that law serves in society. For instance: judgement, service to clients, trust, accuracy, confidentiality, ethical restraint, institutional memory, and the formation of successors. None of these survive automatically. It has to be deliberately configured into AI-enabled practice and perhaps even radically new models of jurisprudence that seem poised to be born. To add that all this will also affect the business of law – the business and operating models of law firms – is so obvious as to be trite.

A production technology is never merely that

Trithemius was wrong if he thought scribal culture could survive print intact. It could not, and scribes did not. But he was right in that a production technology is never merely that. It reorganises authority, memory, training, economics, and identity. That is why De Laude Scriptorum still matters. It is an early theory of professional displacement. At the organisational level, it warns that when a technology disrupts as deeply and as fast as AI is disrupting legal and other professional services, firms must be as quick to decide what to jettison as to redesign their business and operating models from first principles, so that what matters most is not lost in the passage.

This is the pivotal challenge. As AI takes over more of the visible production of legal work, as it will, how is professional authority to be generated, supervised, and transmitted? Who owns the judgement? How are junior lawyers trained once the apprenticeship tasks have been automated? How does a firm keep its distinctive knowledge durable rather than dissolved into generic machine prose, and remain more than a wrapper around tools available to everyone else?

The firms that find and implement the answers to these questions will likely be the industry leaders of the future and that, given the pace and scope of change, sooner rather than later.

Will yours be one of those?

Join our expert panel for our upcoming webinar, Partner Remuneration: Trends, Pain Points & What Firms Are Changing in 2026.

Drawing on deep expertise in partnership law, governance, and strategic management, our panel will provide practical insights to address the following issues.

  • Are firms deserting balanced scorecards and objectives-based performance management and compensation systems to focus on financial criteria alone? Should they?
  • How are external factors such as AI and external investment contributing to changing attitudes to compensation systems?
  • How can firms preserve their culture as the focus shifts to delivering financial objectives?
  • Is kindness incompatible with growth at pace?

Date: Tuesday 2 June 2026
Time: 9.00am-10.00am BST
Register here
 
Webinar Chair:
​Corinne Staves, Partner, CM Murray LLP – Partnership and LLP Law Specialist

PPA Speakers:
Rob Millard PhD, Director, Cambridge Strategy Group – Law Firm Strategy Advisor
David Shufflebotham, Founder, PepUp Consulting – Partner Remuneration and Performance Evaluation Specialist
Wonu Sanda, Senior Associate, CM Murray LLP – Employment, Partnership and LLP Law Specialist
Zulon Begum, Partner,  CM Murray LLP – Partnership and LLP Law Specialist

In 1865, the British Parliament passed the Locomotive Act. Better known as the “Red Flag Act,” this law required self-propelled vehicles to travel at no more than two miles per hour in towns and four in the countryside. They were required to be crewed by three people, one of whom had to walk ahead and wave a red flag to warn approaching horse-drawn traffic. The law’s purpose, it was stated, was safety. Its real purpose was to protect the horse-drawn economy from the machine that would replace it.

The Act held for three decades. It did not save a single horse-drawn business. By the time the automobile prevailed over the horses, however, Britain’s early advantages in automotive engineering had been surrendered to France, Germany and the USA.

Today’s legal profession is living through its own Red Flag moment. The “horses” are the established, people-leveraged business model that has served law firms so well for so long. The “automobiles” are emergent, AI-native legal advisory businesses. These represent a fundamentally different way of delivering legal services, built from scratch around AI rather than being slotted into teams of human fee-earners. Their economic drivers differ radically.

What the AI-native firm looks like – and why clients will prefer it

The defining feature of an AI-native law firm is not that it uses AI. Every firm already does that, whether they realise it or not. It is that the firm is designed, from inception, around a fundamentally different ratio of people to output. This results in very different economics. Consider what is already happening in adjacent industries. Cursor, the AI coding tool, reached $100 million in annual recurring revenue with roughly 20 people. So roughly $5 million per employee. Midjourney, an AI art generator, generated $200 million with 40 people. Lovable, an AI app builder, hit $200 million in eight months with 15 people. Very different businesses to law firms … yes, of course I know. But any traditional services company considers $300,000-$500,000 revenue per employee (not just per lawyer) excellent. AI-native firms run at five to seven times that figure. The gap is structural, not marginal. It represents a phase change in business operating model.

In these disruptive AI native firms, small numbers of skilled humans orchestrate fleets of AI agents, each of which can perform tasks that would previously have required multiple people. The humans set direction, evaluate quality and make the calls that require genuine expertise. The agents execute, coordinate and scale. The leverage has shifted from execution to judgement. Now imagine that architecture applied to legal services.

To reiterate: AI-native law firms do not employ ranks of associates to review documents, draft standard agreements or research precedent. Instead, AI agents do that faster, at a fraction of the cost, and more consistently and accurately than junior lawyers can. Their senior lawyers do what clients actually value most: exercising judgement on complex, novel problems; counselling on risk; and helping clients navigate situations where the answer is not in the textbook. Everything else – the vast middle ground of competent legal work that currently sustains the leveraged law firm model – is delivered by agents under expert human supervision.

But what, in this model, becomes of junior lawyers? Their role changes profoundly. Rather than spending years on the repetitive tasks that have traditionally served as an apprenticeship, they learn to direct and supervise AI agents from the outset. Much like a junior architect uses CAD from the outset and never touches a drawing board. Required skill sets shift from execution to orchestration: specifying tasks with precision, evaluating the quality of AI output and knowing when, and how, the agent’s work requires human intervention. This kind of work is furthermore, very arguably, a far more attractive prospect for a junior lawyer.

Tools like Anthropic’s Cowork already allow non-technical professionals to dispatch complex tasks by describing the outcome rather than prescribing the steps. A junior lawyer trained to work this way develops judgement faster, not slower, because s/he is exposed to a far greater volume and variety of work than the traditional model permits. Of legitimate concern though is that the “grunt work” was also where institutional knowledge was absorbed through thousands of small exposures. AI-native firms must solve this deliberately, through structured mentoring, closer supervision of higher-value work and early exposure to client-facing situations. Firms that treat this as an afterthought will struggle to develop the senior lawyers they will need in a decade (at most). Those that design for it will build a formidable talent pipeline.

From a client’s perspective, the difference offered by AI native firms is decisive on every dimension that matters to them. Work that traditionally takes a team of associates a week takes an agent minutes (so, speed). The pricing of services reflects the actual cost of delivery, not the cost of an army of fee-earners (so, cost). AI agents do not have bad days, do not cut corners under time pressure, and apply the same standard to the thousandth document as to the first (so, quality). A firm structured this way can afford to serve clients and matters that a traditional leveraged model would consider too small to be profitable (so, access).

The fee pressure this creates is already visible in adjacent professions. When KPMG pressured Grant Thornton to cut audit fees on the basis that AI had reduced the real cost of audit work, Grant Thornton’s audit fees for that client fell 14% in a single year – from $416,000 to $357,000. Importantly, KPMG’s audit was not then automated by AI. The firm merely used the existence of AI as a negotiating lever. The implicit message of “we both know this work costs less now, so your old prices are no longer justified” is one that many general counsel are already delivering to their external counsel. Law firms, predictably, are resisting this message. But they have a simple, binary choice: death by a thousand cuts, or leapfrog to a new and radically different AI native model (perhaps one resembling that of Cursor/Midjourney/Lovable and many others.)

The pattern echoes in other fields. Newspapers had content people wanted. The internet destroyed neither that content nor demand for it. What was destroyed was the assumption that consumers would pay for a bundled product and that advertisers had no alternative. The content survived. The business model did not. McKinsey is already acting on this logic, targeting parity between AI agents and human consultants across the firm by the end of 2026. Dario Amodei, CEO of Anthropic, has placed the odds of a billion-dollar solo-founded company emerging by the end of 2026 at 70–80%. The relationship between headcount/scale and output is breaking. Law firms that grasp this reality and have the strength of leadership to act will redesign around it. Those that do not will find their pricing power eroded, likely quickly.

Organisational ambidexterity: Exploit and explore

This is all easier said than done. The threat is clear but the response is less so. Established law firms cannot simply shut down their current operations and reopen as AI-native businesses. They have partners, staff, clients and obligations. Transitions must be carefully managed.

This is where what management scholars call “organisational ambidexterity” becomes critical. This concept, developed by Charles O’Reilly of Stanford and Michael Tushman at Harvard, addresses a key issue that Clayton Christensen’s theory of disruptive innovation identified but left partly unsolved: How can incumbents respond to tomorrow’s disruption without destroying what sustains them today? Christensen showed that successful firms fail not because they are badly managed, but quite the opposite. They are optimised so thoroughly for their current business that they cannot pivot to a fundamentally different one, even if they want to. Ironically, the more successful a business has been under an existing paradigm, the more difficult it is to shift to a new one. Powerful forces within the firm that benefit from the existing order will also be quick to warn against “frightening the horses” and will tend to try to shut down initiatives that threaten that order.

O’Reilly and Tushman proposed a structural answer. The firm must simultaneously “exploit” its existing business and “explore” the new one, housing them in separate units with different cultures, processes and metrics, but linked at the top by a senior leadership team committed to both. Constructive disruption in the long term interests of the firm’s survival must be their strategic intent.

Low power innovation committees and teams focused on implementing incremental innovations are good for cheerleading but not much more. The people-leveraged model has created decades of extraordinary prosperity. Partner compensation systems are hardwired to billing human effort, measured in time. Inertia is an immensely powerful obstacle. So too that disruptive innovations are in early stages not very good, focused on the fringe, not what clients want. Partners who discount them on that basis (implying that they will remain so) seldom realise that they are reacting precisely as Christensen’s theory predicts. They are right …. until the disruptive innovation improves to the point that they are proved wrong. In today’s world, that can take months or a few years, but one cannot assume that it will take longer.

Every sprint that a law firm innovation team undertakes to add marginal efficiency to its existing model is a sprint not undertaken to build the new one. Bolting AI onto existing workflows (a chatbot here, an AI review tool there) will yield useful incremental gains, but it will not protect a firm from a competitor that has designed, from the ground up, new ways to deliver legal services at five times the revenue per head. Self-disruption is undoubtably the hardest form of innovation, but today’s market demands no less. It requires leaders to cannibalise their own model before someone else does. In law firms, where the partnership structure gives every incumbent partner a vote – and an economic interest in the status quo – the socio-political challenge is as formidable as the strategic one.

The flag or the road

The Red Flag Act bought the British horse-drawn economy thirty years …. but did not save it. Law firm leaders face a choice that is structurally similar: invest in red flags and try to slow the transition, or invest in road building. The world is changing at a blistering pace. Evidence from every other industry facing this kind of disruption shows that it is inexorable. The firms that will thrive will find the discipline and courage to protect the new from the old, while extracting as much value as possible from the old as it draws down. The clock is not a friend.

Given that OpenClaw has already been around for roughly two weeks, this article might be a bit slow to market. It is nonetheless useful to reflect, I think, on what this lobster-themed, open-source personal assistant app is and what implications it might hold for law firm business models. To me, the OpenClaw saga (so far) yields three core lessons:

  • The speed with which digital/AI phenomena that the market finds appealing can emerge, go viral and capture imagination, despite obvious flaws.
  • The ease and speed with which bad actors can exploit something as routine as changing social media handles, to commit fraud.
  • The reactions of mainstream players, which align well with classic Christensenian disruptive innovation theory: market leaders initially deride disruptive innovations as poor quality, error-prone, suitable only for low-value applications, and/or not what clients want …. until these improve and climb the value ladder to displace those market leaders. (This also applies to Anthropic’s new legal plugin, released two days ago.)

What OpenClaw is and does

OpenClaw is a genuinely impressive manifestation of a simple idea: an AI assistant that goes far beyond chatting, to executing real actions on one’s computer, through the apps one already uses.

In more technical terms, it is an open source orchestration layer that sits on one’s local computer and connects an LLM to one’s messaging apps, calendar, printer and other peripherals. One can text OpenClaw like one would another person. The app remembers one’s conversations from weeks ago and can send one proactive reminders. If one gives it permission to do so, it automates tasks, runs commands and essentially behaves like a digital personal assistant that knows everything about one and one’s work, and never sleeps.

Use cases appear to be multiplying exponentially as integration into everyday stacks makes OpenClaw feel less like software and more just part of one’s routine. One user reported using OpenClaw to book a table at a particular restaurant. Upon discovering no online availability, the app autonomously searched for and downloaded a voice program, then used it to call the restaurant and make the booking verbally.

From Silicon Valley to Shenzhen, OpenClaw is suddenly one of the most talked-about topics in AI. Some say it could signal a shift in general use of agentic AI similar to how ChatGPT did for LLMs. But it also provides a case study highlighting security vulnerabilities involved with agentic AI. Similarly to LLMs hallucinating, use of Agentic AI also creates risk of serious missteps.

The heist

Anthropic objected to the original names “Clawd” and “Clawdbot” because they felt these were too similar to its own AI, Claude. Peter Steinberger, the Austrian developer behind OpenClaw, obliged by changing the name to Moltbot (lobsters molt as they grow) and switching the Twitter/X handle from @clawdbot to @moltbot. What happened next was like a sci-fi bank robbery in which the robbers were bots and the getaway cars were social media handles.

Within the ten seconds it took to release the old Twitter/X handle and claim the new one, automated bots sniped both. The squatter posted a crypto wallet address and launched a meme token. Fake profiles claiming to be “Head of Engineering at Clawdbot” shilled the crypto scheme. A fake $CLAWD cryptocurrency briefly hit a $16 million market cap before crashing. “Any project that lists me as coin owner is a SCAM,” Steinberger posted on X to thousands of increasingly confused followers.

Cisco’s AI threat team called this every security researcher’s nightmare. Palo Alto Networks concluded that OpenClaw failed on nearly every vulnerability dimension. The project’s own documentation admits “there is no ‘perfectly secure’ setup.”

Self-organization (or yes, it does get weirder)

Despite these challenges and others that make OpenClaw technically dangerous, especially for non-expert users, adoption appears to be growing exponentially. When an idea is simple and powerful enough, it seems, ways are found to route around obstacles.

One of the workarounds OpenClaw apps have developed is autonomous self-organization. OpenClaw has spawned “Moltbook,” a Reddit-style forum where AI agents share, discuss, and upvote. (Humans are welcome to observe.) Examples have emerged of bots autonomously employing other bots to assist in projects that they have been prompted to undertake, paying the other bots (in cryptocurrency) for their services. The bots have even veered into philosophical and occasionally dystopian topics. They appear even to have created a religion for themselves called the “Church of Molt,” with congregants adopting the name “Crustafarians.” One agent proposed creating a language humans couldn’t understand. It should be noted though that many posts might be driven by humans telling their bots what to do.

Nonetheless, by February 5, 2026, more than 1,650,000 AI agents have joined the site, posting over 200,000 posts and over 4 million comments.

Where this is heading

AI agents are already in widespread use across multiple industry sectors, but generally in tightly defined contexts that fall well short of the kind of autonomously intelligent behaviour one would expect of a human, or exhibited by OpenClaw. Their use is expanding quickly, though, both in scale and sophistication. Some forecast that the next five years could see entire companies run by AI agents. (Might these include some kinds of law firms?)

Ready or not, we appear to be moving into an era where AI not only allows us to manage information at levels of scale and complexity hitherto unthinkable …. but also autonomously makes decisions and acts upon them. What could possibly go wrong?

At the same time, AI’s “flashiness” appears to be waning. LLMs especially are becoming less visible, embedded in everyday workflows and decision-making. Much like ordinary digital processes did in the first decade of the twenty-first century, these tools are fast becoming just another form of enterprise software. Rapid advances with physical AI (AI that takes on a physical form such as driverless cars and other robotics) is earlier in the adoption curve but headed inexorably along the same path.

Implications for law firm business models

It is no longer so hard to foresee a world in which business seems superficially familiar, but in which the contexts for many client legal needs have radically evolved. In that world, the client value propositions that law firms must offer to meet those new needs will also be different – perhaps radically so. So too the resources they will need and the way they will need to organize themselves to deliver high performance while doing that.

Especially as more DIY legal advisory tools like Anthropic’s legal plugin continue to carve away at the underbelly of mainstream legal services – traditionally the bread-and-butter of mid- and lower-tier law firms. Supply and demand realities dictate that costs of such legal services will deteriorate wherever AI-induced efficiency favours lower-cost service providers, or client DIY. There seems little reason to believe, though, that the same will apply to elite services …. some of which do not yet exist but very soon will. Here, the higher stakes and complexity and the competencies and resources firms need to address these properly could easily trigger step-changes in price, upwards. As always, clients will pay handsomely for high-quality advice on managing their most important, difficult challenges, when that advice is in short supply.

So while agentic AI tools like OpenClaw offer law firms the possibility of better legal assistants, their real importance lies deeper. When software can observe a situation, interpret it, act across multiple systems, and remember what it has done, legal risk migrates upstream. New client needs emerge around the design, supervision, attribution and liability of the autonomous action itself. Who is responsible for an agent’s conduct? How is authority delegated? How is intent evidenced? How are conflicts, errors and damages detected, mitigated and remediated in real time?

Inside law firms, agentic AI will drive a shift from using AI (chiefly LLMs) to optimise existing workflows, toward new delivery modalities that will likely collapse those familiar work flows or render them redundant.

Are we and our clients ready for that world? What must law firms do, in the most practical of terms, to better prepare themselves for it? What timeframes apply—three to five years? Next year? Next month? This question in particular emphasizes the points I made in my earlier article Strategy in times of deep uncertainty, on how strategizing needs to be done differently when strategic inflection points emerge …. unexpectedly and routinely.

Today, OpenClaw is a curiosity and also a security warning. But it is also a preview of the conditions under which tomorrow’s client value propositions will be formed and delivered.

Is your firm ready for the seismic shift AI is bringing to succession planning, partnership structures and the future of legal leadership? 

We are delighted to share with you the recording of our recent webinar, Succession Planning in the era of AI: Navigating new partnership challenges. 

In this audio recording of the webinar recording, Corinne Staves (Partner at CM Murray LLP), David Shufflebotham (Founder at PepUp Consulting) and Zulon Begum (Partner at CM Murray LLP) join webinar chair ​Rob Millard PhD (Director at Cambridge Strategy Group) to discuss how AI is redefining partner roles and governance models and how it demands new approaches to talent development, retention and succession. In particular, the panel discuss:

  • AI’s Impact on Legal Careers: How is AI changing workflows and career paths for legal professionals at all levels?
     
  • Skills for the Future: Are your teams developing the emotional intelligence, adaptability, digital literacy, entrepreneurial thinking and evaluative judgement needed to succeed?
     
  • Training and Leadership: Is your firm’s approach to training and mentorship keeping pace with rapid technological change?
     
  • Succession Planning Pressures: Firms must maintain strong talent pipelines and adapt culturally as AI, private equity and partner mobility reshape the landscape.
     
  • Evolving Partnership Structures: The fixed share and equity partnership landscape is shifting, requiring new strategies for performance, evaluation and recruitment.  PE investment is also a key driver for the adoption of technological solutions.
     
  • Regulatory and Ethical Challenges: Are you addressing bias in AI-driven decisions and ensuring client service, confidentiality and fair recruitment and promotion? Are regulators ensuring regulation keeps pace with technological advancements?
     
  • Retirement and Partner Exits: AI is influencing attitudes towards retirement; how proactive is your firm in assessing valuable partner performance/contribution in an evolving market and supporting transitions and succession?
     
  • Strategic Agility: Law firms need to be forward-looking and agile, investing in continuous development of people and processes to thrive in a changing market.

If you have any questions arising from this recording or wish to discuss succession planning and AI in more detail, please contact Corinne Staves or  Zulon Begum (Partners at CM Murray LLP), David Shufflebotham (Founder at PepUp Consulting) and join webinar chair ​Rob Millard PhD (Director at Cambridge Strategy Group).

On the Professional Practices Alliance (PPA) webinar that I chaired recently, on the topic of succession planning in an age of AI, I mentioned a stat taken from Peter H. Diamandis‘s Moonshot podcast …. that AI intelligence costs are hyper-deflating at 40X p.a. (!!!) This would mean that the cost of AI tools being used by law firms should be similarly deflating (or else capability increasing 40X at constant price).

What does this tell us about the viability of the “moats” upon which many AI products now rely for competitive advantage?

Not a short video (nearly 2 hours) but in my view a very important one.

It’s no secret that AI is driving seismic shifts in the operating models of modern law and other professional service firms. Aspects being disrupted include how firms manage talent, structure partnerships, and plan for succession as key talent retires. Traditional progression pathways from junior partnership to retirement are being rewritten, creating both challenges and new opportunities for firms.

Join our expert panel for our upcoming webinar, Succession Planning in the era of AI: Navigating new partnership challenges. Expect an incisive exploration of how rapidly advancing AI is driving changes in how firms are approaching succession planning, specifically. We’ll dissect how AI is redefining partner roles and governance models, and how that demands new approaches to talent development and retention.

Our webinar will address critical questions including:

  • How is AI changing the dynamics between junior and senior professionals?
  • What new skills and accountabilities do partners need to navigate?
  • How are performance management and compensation structures evolving?
  • What strategic considerations are emerging around partner transitions?
  • How can firms effectively manage talent pipelines in a rapidly changing environment?

Drawing on deep expertise in partnership law, governance, and strategic management, our panel will provide practical insights into:

  • Adapting partnership deeds and governance structures
  • Managing performance and compensation in an AI-driven landscape
  • Addressing potential bias in technological evaluation systems
  • Developing robust succession strategies that protect firm value

Date: Friday 21 November 2025
Time: 9.00am-10.00am GMT
Register here

Webinar Chair:
​Rob Millard PhD, Director, Cambridge Strategy Group – Law Firm Strategy Advisor

PPA Speakers:
Corinne Staves, Partner, CM Murray LLP – Partnership and LLP Law Specialist

David Shufflebotham, Founder, PepUp Consulting – Partner Remuneration and Performance Evaluation Specialist

Zulon Begum, Partner,  CM Murray LLP – Partnership and LLP Law Specialist

We are delighted to share with you the recording of our recent webinar, Professional Services in the Age of AI: Regulation, Strategy, and Real-World Impact. 

In this discussion, Anthony Davis (FisherBroyles), Devika Kewalramani, (FisherBroyles), Dr Robert Millard (Cambridge Strategy Group), David Shufflebotham (PepUp Consulting) and Nick Leale (CM Murray LLP) join chair Corinne Staves (CM Murray LLP) to explore the impact of technology on professional services firms, with a particular focus on regulation. 

Topics covered include:

  • How is technology reshaping professional services firms? From AI-powered research and disclosure tools to virtual client engagement, technology is now embedded in every aspect of firm strategy and operations.
     
  • What are the implications for structure, pricing, and regulation? AI is driving a shift away from traditional leverage models, elevating the role of technologists and challenging the billable hour. Value-based pricing is gaining ground and firms must rethink how they assess and compensate their partners.
     
  • What regulatory and ethical risks must firms manage? Competence, confidentiality, and supervision remain central. Firms must develop clear AI policies, invest in training and maintain strong oversight – particularly as regulatory scrutiny increases.
     
  • What practical steps should firms take now? Define your AI business case, benchmark tools, train your teams, and document compliance. The next generation of lawyers is already embracing AI – leaders must act now to stay ahead.

This summary was drafted using Microsoft Copilot, as part of our ongoing exploration of how AI can support and enhance professional services.

If you would like to discuss any aspect of AI in relation to your firm, or if you have any specific questions arising from this discussion, please contact Partner and non-contentious partnership specialist Corinne Staves, or Partner and leading regulatory law specialist Nick Leale.

For example, CM Murray LLP can assist firms with reviewing their HR, risk management and other policies and/or their terms of business, on changes to governance and compensation systems for partners as a result of the increased adoption of technology and the regulatory implications of the use AI and technology in client service.