What comes next: how GenAI is reshaping the legal market

Christine Horton

In association with

The legal industry is entering what could be its most significant period of transformation in decades.

As generative AI (gen AI) moves from experimentation into everyday workflows, both law firms and in-house legal teams are being forced to rethink how legal work is delivered, how value is measured and where human expertise fits into increasingly AI-enabled operations.

According to Thomson Reuters Institute’s 2026 AI in Professional Services Report, AI adoption across the legal sector has doubled over the past year, while half of organisations expect agentic AI to become central to legal workflows within two years.

For many organisations, the challenge isn’t whether AI will shape the future of legal services, but how quickly they can adapt to it.

Speaking at the company’s recent Legal Innovation Summit, Lizzy Duffy, senior director at the Thomson Reuters Institute, said the pace of change is already accelerating across the legal ecosystem.

“We know there’s a transformation taking place across the legal ecosystem as the pace of AI evolution accelerates. Legal professionals who support, protect and enable business must change too,” she said.

Moving beyond experimentation

According to Duffy, the legal market has already moved beyond the early phase of AI pilots and experimentation into real deployment.

Yet despite growing adoption, uncertainty remains around how AI is being used in practice. Duffy pointed to research showing that many corporate legal teams are still unclear about how their external firms are deploying AI within client work.

At the same time, clients themselves are increasingly driving the pace of change.

“We’re seeing that it is the client side that’s setting the pace. Our latest report into AI adoption in professional services shows that two-thirds of clients are optimistic about AI, compared with just around a half of law firms,” said Duffy.

That shift is putting pressure on firms to modernise both their technology strategies and their operating models. The Thomson Reuters Institute’s research indicates that legal expertise alone is no longer enough, as clients increasingly expect firms to combine technical capability with AI-enabled service delivery and greater efficiency.

Why collaboration matters

As AI reshapes legal workflows and client expectations, the interdependence between law firms and in-house legal teams is becoming increasingly important. Despite that, Duffy warned that many organisations are still approaching transformation separately rather than collaboratively.

“At this moment, both sides – law firms and the legal departments – are retreating into their own silos to build the future separately at just the moment when they really should be coming together,” she said.

A major focus for Thomson Reuters itself is understanding what the future legal department could look like by 2030. Through an internal initiative known as GCO 2030, the company’s legal team, in partnership with the Thomson Reuters Institute, is exploring how AI, automation and new workflows could reshape legal operations over the next five years.

Duffy outlined five emerging “archetypes” that she believes will define the modern legal department, ranging from large-scale automation of repetitive work through to deeper collaboration between legal teams and functions such as HR, finance and sales.

At the centre of all of them, she said, is a “tech-forward mindset” where legal professionals consider the right balance between human expertise and technology to achieve the best business outcome.

One of the biggest changes could come in how legal departments engage external firms. Duffy said AI is pushing organisations to become far more strategic about the work they outsource.

“Our goal is not to eliminate the need for law firms, but it is to work with them more strategically and more efficiently. We don’t want to pay for the same legal advice twice,” she said.

Redefining the legal market

The changes underway are expected to reduce demand for some forms of routine legal work, while increasing demand for high-value advisory services, specialist expertise and complex disputes.

Duffy outlined several possible futures for law firms, including “tech-led disruptors” built around AI-driven delivery models, “elite boutiques” focused on premium specialist expertise, and “integrated powerhouses” combining scale, standardisation and AI-enabled client services.

Crucially, Felix Steffek, professor of law at the University of Cambridge and principal legal AI advisor at Thomson Reuters, argued that AI’s ability to reduce legal transaction costs could fundamentally expand the market for legal services rather than shrink it.

“Legal AI reduces transaction costs and creates agency to shape the future,” he said.

Steffek also argued that AI systems are beginning to capture value traditionally created through routine legal work, particularly tasks previously handled by junior lawyers.

For legal leaders, the challenge now is determining where their organisations fit into this changing value chain. Duffy believes collaboration will ultimately determine which organisations thrive.

“None of these questions can be solved by one group alone,” she said. “By coming together to answer these questions, law firms and legal departments can help to shape a future for the legal market that is resilient, transparent and sustainable.”

Watch the key talks from Thomson Reuters’ ‘Legal Innovation Summit’ on-demand below

• Economics of legal AI
• What does the legal market look like in 2030?
• CoCounsel Legal product reveal
• The secrets to scaling AI in legal panel discussion

In association with

For more information please visit legalsolutions.thomsonreuters.co.uk

For many legal organisations, the biggest challenge with AI is no longer getting started – it’s scaling successfully.

Across both law firms and in-house legal teams, experimentation with gen AI has accelerated rapidly over the past two years. But moving from isolated pilots to enterprise-wide adoption remains significantly harder, particularly in highly regulated environments where governance, risk management and client expectations all need to evolve alongside the technology.

So what does it actually take to scale AI beyond experimentation and turn it into sustained business value?

For Agustin Sanchez, director of customer success at Thomson Reuters, successful AI transformation starts long before technology is deployed.

“It starts with mindset,” he explained.

According to Sanchez, organisations that scale AI successfully combine curiosity and experimentation with leadership sponsorship, accountability and structured change management.

“If that mindset is the right one, then accountability comes into shape, then the right processes and structures are in place,” he said.

Beyond the pilot phase

Nevertheless, many organisations remain stuck between early experimentation and true operational transformation. While many businesses have introduced AI tools into parts of their legal operations, far fewer have embedded them deeply enough into workflows to create measurable enterprise-wide impact.

For Sanchez, the difference between being successful and being at a standstill often comes down to whether organisations treat AI as a standalone tech project or as a broader operational transformation programme. That involves identifying practical use cases early, establishing leadership buy-in and ensuring teams understand why AI is being introduced in the first place.

“What are the areas where we think AI has the largest potential for change and for return on investment?” Sanchez said.

He argued that well-defined use cases create momentum internally and help organisations build confidence in AI deployment before scaling further.

Embedding AI into legal workflows

Within the legal industry workflow-integrated AI tools that can operate within existing legal processes rather than forcing teams to work separately from them are gaining prominence.

Sean Edwards, head of legal, corporate finance and asset lending at Sumitomo Mitsui Banking Corporation, said his organisation had recently implemented CoCounsel as part of a wider AI strategy across the bank. He believes one of the major opportunities AI creates is the ability to work more effectively with large volumes of legal and operational data across the organisation.

“Lawyers are very good at marshalling data,” he said.

But he also stressed that scaling AI in regulated industries requires strong governance structures from the outset, particularly around security, confidentiality and internal approvals.

“It’s irritating to have to go through these approval processes,” he said. “But having that infrastructure is really important.”

Of course, trusted AI systems must be able to operate safely within highly regulated environments while maintaining explainability and governance controls. That becomes particularly important as organisations look to connect AI across broader enterprise workflows rather than limiting it to isolated legal use cases.

Why adoption matters as much as technology

Scaling AI successfully depends as much on adoption and enablement as it does on the technology itself.

Here, Tina Lepomme, Senior Legal Technologist at Addleshaw Goddard, argued that organisations need to give employees space to experiment with AI directly rather than simply mandating adoption from leadership teams.

“If the leadership gives the space and incentivises the use of AI, combined with giving everyone within the organisation the time and access to the tools to see what they can do, then you get those lightbulb moments,” she said.

When it comes to scaling AI, the experts advocate for a staged process rather than a single deployment event.

According to Sanchez, the first month is typically focused on broad adoption and familiarisation, while later stages focus on embedding AI into everyday workflows and eventually redesigning operating models entirely.

“At the six-month milestone, that’s when the magic happens. That’s when things have changed,” he said.

By the 12-month stage, he argued, organisations begin to see structural changes around staffing models, workflows and how work itself is delivered.

Turning experimentation into enterprise value

Organisations cannot afford to treat AI as a temporary innovation project. Scaling AI requires long-term operational commitment, clear governance and continuous iteration as both technology and user expectations evolve.

Edwards warned that organisations also need realistic expectations around ROI, particularly during the early stages of deployment.

“There’s a bit of real education there,” he said.

While some cost reductions may eventually emerge through lower external legal spend or improved efficiency, the legal and tech leaders argued that many of the most valuable gains initially come through improved capacity, faster workflows, better access to information and stronger collaboration across teams.

For Sanchez, the key is ensuring organisations remain ambitious while continuing to scale responsibly.

“Be ambitious, be bold,” he said.

As legal teams continue moving beyond experimentation, the organisations that succeed are likely to be the ones that combine AI innovation with operational discipline – embedding trusted, workflow-driven AI directly into how legal work gets done.