The Legal Operating System: In-House Legal in 2040
After three decades of adapting to digital change, in-house legal teams are now facing a shift that will go beyond productivity gains and fundamentally change how they work.
Between 1995 and 2010, the first wave of digital transformation reshaped how legal teams worked – from faxes to email, and from folder-based filing to keyword-based search. The next 15 years changed how legal work was delivered – automation reduced manual steps, and cloud platforms extended access and continuity.
But speed is not the same as transformation. While the infrastructure evolved, the function remained largely the same: legal teams advised, reviewed, approved and responded. The next wave – 2025 to 2040 – will be different. Legal will become less a department and more an operating layer: encoded into workflows, distributed across platforms and delivered through automation.
By 2040, a GC’s role may no longer revolve around leading teams – it may extend into the design and governance of the automated legal architecture the company as a whole relies upon. That future may feel distant, but the groundwork is already being laid.
From Today’s Tools to Tomorrow’s Trajectories
“Each of us has access to an enterprise-grade LLM, and we’re encouraged to explore how it can improve our legal output and productivity.”
Max Latchmore, Senior Legal Counsel, Octopus Energy
While most in-house legal teams are still experimenting with AI tools, some are already reframing their day-to-day workflows. It is a shift in mindset, where teams are learning both new applications and to share knowledge more fluidly across departments.
Legal as Infrastructure
“In-house legal teams won’t just adapt to AI, they’ll redefine how business decisions are made by embedding legal thinking into every workflow.”
Dan Wright, Partner, Director of OC Solutions, Osborne Clarke UK
Within the next 15 years, AI tools will become the delivery mechanism for legal, embedding rules and decisions into agentic workflows that touch every part of the business. Much of what legal teams currently manage – contract review, compliance checks, policy enforcement – will shift into automated systems, allowing routine decisions to happen faster and with fewer delays. Escalation protocols and clause logic will be built directly into tools so risks can be flagged and transactions paused before legal steps in. In many organisations, agentic AI will negotiate standardised terms and route only high-ambiguity or high-impact cases to human reviewers, freeing up legal teams to focus on complex decisions where human input in the moment makes a meaningful difference.
When legal becomes embedded into systems the entire company uses every day, its role begins to shift. Business teams will no longer think of legal as a checkpoint. Instead, legal becomes a background function: ever present but largely invisible. When legal logic is encoded directly into the systems that drive business outcomes, the function becomes inherently more proactive – shaping behaviour and data in advance rather than responding after the fact.
“When legal is embedded into business systems, its role changes. It is no longer there to catch the ball; it helps throw it further.”
Antti Seppala, General Counsel, Pigment
However, while legal logic becomes a seamless part of everyday business, the need for oversight and continuous refinement remains. AI’s decisions, while faster and potentially more consistent, will still require a human hand to ensure they align with a business’ legal standards and ethical expectations.
From Expertise to Probability
Today, AI systems can already perform some of the legal tasks traditionally handled by junior lawyers, including contract reviews. Their outputs are fast and often hard to distinguish from those of a human lawyer. But for most legal teams, the real challenge is not AI’s performance; it is understanding how those results are reached and whether they can stand behind them.
Currently, legal expertise is grounded in human context: experience, interpretation, business sense and ethical judgement. Most legal AI systems rely on large language models (LLMs) that generate outputs based on statistical inference – what sounds right according to prior patterns.
Although these systems can mimic judgement and often rival junior lawyers in performance, they do not understand the law. And because their output often appears cogent and well written, while their inner workings remain largely opaque – even to their own designers – their mistakes can be hard to spot and even harder to explain. To date, this appears to have made it challenging for insurers to price for risk.
This will change in time, however, with researchers enjoying early success in mapping how LLMs make planning decisions in narrow use cases. Their success offers hope that even more complex models may become more transparent. Once that transparency is established, AI models become better understood and easier to insure.
At some point in the coming years, parts of the AI stack will have matured to a point where certain legal outputs – under defined scopes and conditions – are insurable. This will be a milestone, one that marks the moment when legal accountability begins to shift from human authorship to system governance.
“We’re replacing judgement with probability. That’s not wrong, but it is different – and we must recognise and plan for that change.”
Anna Grafton-Green, Senior Director, Head of Legal (UK, Europe and Israel), PayPal
That shift reframes the GC’s role from interpreting risk to deciding when machine judgement is good enough and where it should be applied. While edge cases and high-value deals will be the last to be left entirely to machine judgement, by 2040 much of the legal function will focus less on interpreting the law and more on designing the systems that do.
Legal’s New Ecosystem
As in-house legal teams redesign how their work is delivered, their external legal support needs will evolve in kind. Internal systems will increasingly absorb tasks once routinely handed off, such as first-line contract review or policy drafting.
There will always be cases that GCs will require formal advice on, particularly where the stakes are high or the context ambiguous. While much of the routine scaffolding around a $200 million transaction will be handled internally, human judgement from outside counsel will still offer assurance when commercial or reputational risks are significant.
In other scenarios, GCs will need outside support in shaping and evolving the logic embedded in company systems. This may involve designing machine-readable policy frameworks, developing AI tools and AI-run playbooks tailored to the legal function, testing agent outputs to ensure compliance and ethical standards, and providing oversight of system updates to ensure regulatory and legal alignment.
Between these ends of the spectrum lies a demand for new forms of legal support. We may not yet have names for them, but they will be critical to facilitating the transformational shifts to the new legal operating system.
The last time we saw a shift of this scale was during the commercialisation of the internet. Entire industries were restructured, with some vanishing only to be replaced by their digital counterparts. Legal will follow a similar trajectory. Routine advisory work may decline, but demand will rise for system-level expertise. This is not just about replacing tasks, it is about building a new operational layer from the ground up.
“Legal expertise will no longer be confined to advice, it will also fuse legal and AI skills, to enable data-driven strategic decisions to be made across organisations, constantly supporting the business’ strategy.”
Ashleigh Hegarty, Chief Legal Officer, Charlotte Tilbury Beauty
The Legal Operating System
The AI revolution over the next decade and a half will reshape every sector, and legal will be no exception. By 2040, the in-house legal function will no longer be a faster version of its current reactive state. Instead, it will operate as a strategic, intelligent layer seamlessly integrated across the organisation.
Delivering on that mandate will require a broader range of skills within the legal function. Legal teams will increasingly depend on product designers, data scientists, governance engineers and behavioural strategists to shape intelligent systems. For those entering the profession today, technical fluency and design thinking might become as important as technical legal knowledge.
While the transition will be slow, in-house legal teams are already exploring the challenges of AI integration and risk management, often using existing enterprise tools to lay the groundwork for the changes ahead. They need to find the answers to these questions sooner rather than later, because the decisions they make today will shape the future of legal work and determine how well they are positioned by 2040.
Contributors
We would like to thank these individuals for having shared their insight and experience on this topic.
