Key insights:

• • • AI adoption is now a talent retention and recruitment issue — Law firms that lack professional-grade AI tools risk losing both current and prospective talent.

    • Client relationships are increasingly tied to AI-driven value — Corporate legal departments expect their outside counsel to use AI to improve productivity, quality, and innovation; however, few believe most of their law firms are meeting those expectations.

    • Law firms must rethink their business and pricing models — Although many firms feel financial pressure to accelerate AI adoption, most have not adjusted their pricing structures to reflect AI-driven efficiencies.

Law firms are experiencing unprecedented pressure from the rapid advancement of AI, which is affecting their talent recruitment, client relationships, and business models, according to deeper analysis of the recent ¶¶ŇőłÉÄęĚý2026 Future of Professionals Report.

To help law firms navigate this AI-driven disruption, ¶¶ŇőłÉÄę has published a new action paper, Future of Professionals Report 2026: Actionable insights for law firm leaders, drawing on insights from 736 law firm professionals and 203 corporate legal professionals.

Indeed, the new paper highlights that almost one-quarter of law firm professionals will refuse a job offer if the prospective firm lacks professional-grade AI tools. Further, any perceived misalignment between a professional’s AI preferences and the firm’s strategy increase the risk of attrition, especially among those professionals who value mentorship and skill development.

You can download your copy of theĚý2026 Future of Professionals ReportĚýłó±đ°ů±đ

In addition, almost one-third of corporate legal professionals say they are reconsidering relationships with outside law firms that do not demonstrate how they’ll offer clear AI-enabled value within the next 12 months, the paper notes. And clients increasingly expect their outside counsel to deliver efficiency, quality, and innovation through AI; however, only between 3% and 6% say they believe most of their outside firms are meeting each of these expectations.

Finally, almost 4-in-10 law firm professionals say they are feeling financial pressure to act faster on AI, yet almost two-thirds say their firm’s pricing structure remains unchanged despite clients’ demand for new models that reflect AI-driven efficiencies and increased value.

Dealing with AI-driven challenges

The paper notes that firms with approved AI tools are more attractive to talent, while the use of unauthorized “shadow AI” by more than one-third of professionals creates security and compliance risks. To address this, firms should provide transparent AI solutions and invest in training. While AI may reduce demand for some junior roles, it may increase the need for others, especially hybrid tech-legal roles.

On the client relationship front, many corporate legal departments are facing internal pressure to adopt AI and expect their outside law firms to keep pace. In-house legal teams increasingly expect AI-enabled productivity, quality, and innovation, yet many see a significant gap between expectations and delivery. For example, 70% say they expect productivity gains, while only 6% say they believe most of the firms they work with are delivering them.

Clients, for their part, also expect pricing models that reflect AI-driven efficiencies through greater cost certainty and transparency. Outside law firms that fail to adapt may risk fee pressure, ultimately losing business to more agile competitors.

Only half of professionals see their firm’s AI strategy reflected in their daily work, and this potential misalignment could cause talent and AI adoption problems.

Fortunately, amid all these challenges for law firm leaders, the paper identifies three strategic paths law firms can take, including:

• • • Using AI to elevate by automating routine tasks that would then allow professionals to handle complex, high-value work.
    • Using AI to scale by prioritizing productivity and efficiency and handling high volumes of routine work with AI and human oversight.
    • Using AI to reimagine by rebuilding the firm around AI and offering new models like outcome-based pricing and embedded partnerships.

Unfortunately, some firms are choosing to defer this crucial decision, which increases their risk of client and talent attrition as the market evolves.

Whichever path law firms take, however, the paper makes clear that firm leadership must clearly communicate their AI strategy.ĚýThe paper notes that only half of professionals see their firm’s AI strategy reflected in their daily work, and this potential misalignment could cause talent and AI adoption problems.

The paper encourages firms to move quickly to close the gap between client expectations, talent needs, and operational realities by defining a clear AI strategy, investing in training and tools, and adapting pricing models for an AI-driven market.

Using the guidance from this action paper, firm leadership can navigate these challenges and move their law firm into a more responsive, profitable, and sustainable AI-enabled future.

You can read a full copy of theĚýFuture of Professionals Report 2026: Actionable insights for law firm leadersĚýpaper here

Key insights:

• • • AI is now a talent and client expectation, not a differentiator — A large majority of tax & audit professionals regularly use AI, and many employees and clients now expect their firms to have strong AI capabilities.

    • Firms need to choose a deliberate AI strategy — There are three primary paths for AI adoption, and no matter which a firm chooses, the key message is that firms should actively define their AI direction rather than delay decisions.

    • Successful AI adoption requires governance and people-focused leadership — Beyond implementing technology, tax & audit firm leaders must establish AI governance, clearly communicate strategy, and align their AI with employee needs.

As AI adoption within the tax & audit profession accelerates — 81% of professionals say they are now using AI tools regularly — firm leaders are experiencing unprecedented pressure from talent, clients, and their firm’s own financial performance, according to the recent ¶¶ŇőłÉÄęĚý2026 Future of Professionals Report.

For example, retaining and recruiting top tax talent remains a critical concern in the profession, and AI has just ratcheted up the pressure even more. More than one-quarter of professionals say they would not accept a job at a firm lacking professional-grade AI, and almost 1-in-3 say they would consider leaving if their expectations for AI are not met within the next two years.

To help tax & audit firm leaders better navigate this fraught environment, ¶¶ŇőłÉÄę has published a new action paper, Future of Professionals Report 2026: Actionable insights for tax & audit leaders, that provides practical guidance for navigating talent shortages, rising client expectations, and financial pressures, all within the context of the rapidly evolving technological environment.

You can download your copy of theĚý2026 Future of Professionals ReportĚýhere

Many tax & audit professionals surveyed say client expectations are rising, with AI-enabled quality becoming an important criterion for retaining outside tax & audit firms. At the same time, nearly half of respondents say they feel pressure to generate financial gains from AI, while one-third say their firms have yet to adapt commercial models accordingly. If left unaddressed, these pressures can compound, the paper points out, ultimately threatening a firm’s ability to attract and retain both clients and talent.

Finding your strategic path for AI adoption

Fortunately for those tax & audit professionals who feel overwhelmed by the strictures of advanced technology, the paper identifies three primary strategic paths for AI integration that could fit your firm, including:

• • • Using AI to elevate by leveraging AI to handle routine tasks, freeing professionals to focus on complex, high-value advisory work. Firms adopting this path aim to deepen client relationships and command premium fees that are based on expertise rather than volume.
    • Using AI to scale by focusing on productivity and using AI to increase capacity and consistency without increasing headcount. This path is particularly attractive for managing busy tax seasons and reducing recruitment strain.
    • Using AI to reimagine by rethinking the firm’s entire business model. Instead of periodic compliance, firms provide clients with continuous, proactive support and real-time insights, shifting from a service provider to a strategic partner.

A minority of respondents say their firms are deferring strategic decisions on AI, but the paper warns that any delay carries significant risks, especially as clients and talent expectations increase.

Universal priorities for firm leaders

Regardless of their chosen path, however, the paper outlines four priorities that every firm leader needs to address in order to succeed, including:

1. 1. 1. Govern the tools being used — More than one-third of professionals admit to using unauthorized AI tools, which greatly increases firms’ liability risks. Establishing clear governance, approving secure tools, and providing usage guidance are essential to mitigate these risks.
      2. Clarify the firm’s strategic direction — Firms must articulate their AI ambitions, internally and to clients, even if the path is not yet finalized. Understanding whether the goal is efficiency, expertise, or transformation can help guide decisions on tools, pricing, and hiring.
      3. Align AI with your professionals’ needs — Nearly half of professionals say they value work fulfillment as the primary benefit of AI, and a significant portion say they would consider leaving if their expectations go unmet. Engaging with teams to ensure AI deployment aligns with what they want is critical, whether they want more time, more complex work, or both.
      4. Define the role of early-career professionals — As AI automates more tasks, tax & audit firms must ensure that junior staff still receive the structured development needed to build professional judgment. Ensuring supervision before automation erodes these opportunities is vital for talent success.

As the paper clearly outlines, those tax & audit firm leaders that govern AI effectively, articulate a clear strategy, and invest in their people will be the ones best positioned to succeed in an increasingly AI-driven market.

You can download a full copy of theĚýFuture of Professionals Report 2026: Actionable insights for tax & audit firm leadersĚýpaper here

Key insights:

• • • AI adoption has become an urgent business imperative — Enabling corporate functions are under pressure from leadership, business stakeholders, and employees to demonstrate tangible AI-driven value.

    • Slow AI adoption creates risk — Many professionals are frustrated by limited access to high-quality AI tools, which contributes to increased employee turnover and growing use of unauthorized shadow AI

    • Success depends on coordinated transformation — Organizations need a deliberate AI strategy rather than scattered experimentation to help guide responsible AI adoption across the organization.

Today, internal corporate enabling functions — such as legal, tax, global trade, compliance, and risk — find themselves at a crossroads as they face mounting pressures from three critical fronts: i) internal stakeholders that are demanding faster, more informed decisions; ii) finance departments that are expecting AI-driven efficiency and cost control; and iii) a professional workforce eager for tools that enhance the value of the work they do.

The message from the C-Suite is clear: AI must deliver tangible results now, according to the recent ¶¶ŇőłÉÄęĚý2026 Future of Professionals Report.

To help internal corporate function leaders manage this pressure and move forward with confidence into an AI-enabled future, ¶¶ŇőłÉÄę has published a new action paper, Future of Professionals Report 2026: Actionable insights for corporate leaders, drawing on insights from hundreds of internal corporate professionals.

Facing down the triple pressures

The urgency that corporate function leaders are facing is underscored by those three areas of pressure. For example, almost half of professionals surveyed in enabling functions say they are either already experiencing the financial consequences of lagging AI adoption or are expecting to within a year. Many enabling functions have long been expected to absorb growing workloads without proportional increases in resources. Now, AI is increasingly viewed as a way to expand capacity and improve efficiency, making delaying its adoption a potential source of budgetary and competitive risk.

You can download your copy of theĚý2026 Future of Professionals ReportĚýhere

Stakeholder pressure is equally intense. As many business units accelerate their own AI deployments, they expect the organization’s other enabling functions to keep pace. If these functions become bottlenecks, they risk being sidelined or being perceived as obstacles rather than strategic partners. Indeed, more than half of corporate professionals say they are facing significant pressure from stakeholders to act faster on AI, with in-house legal teams feeling this most acutely.

Yet the pressure coming from the workforce may be the most alarming. The action paper shows that fully 30% of professionals say they are considering leaving their organizations within two years if the gap between the AI-driven value they expect and what is made available to them isn’t addressed. Access to professional-grade AI tools has become a key factor in job decisions, yet nearly 6-in-10 professionals say they lack access. This gap contributes to both retention challenges and the rise of unauthorized AI use, increasing compliance and governance risks.

Choosing the right path

Faced with the reality of these pressures, corporate function leaders must choose a strategic path for AI adoption. The action paper outlines three primary trajectories:

• • • Using AI to elevate by shifting human effort to high-value, judgment-based work.
    • Using AI to scale by leveraging AI to handle increased workloads without increasing headcount while optimizing for efficiency.
    • Using AI to reimagine by rebuilding workflows around AI’s capabilities, such as implementing shared data infrastructure and real-time dashboards.

However, knowing the path is not the same as walking it. The action paper also highlights a potential execution gap, in which a lack of coordination and shared accountability across functions derails any real progress. This is a particular problem for enabling corporate functions because many departments often operate in silos, using different AI tools and standards, which leads to fragmentation and operational bottlenecks.

The solution, as the paper outlines, lies in building a shared framework for AI governance and accountability, with fiduciary functions like legal, tax, and compliance taking the lead. Some critical recommendations outlined in the paper include advocating for professional-grade AI tools, planning for an evolutionary journey through AI adoption, and leading an organization-wide conversation about AI governance and standards.

Finally, the paper encourages corporate leadership teams to step back from daily pressures and engage in structured exercises to define a shared vision for AI within the organization. By developing a long-term roadmap that considers processes, data, technology, people, and risk, corporate leaders can ensure AI adoption delivers both immediate value and sustainable competitive advantage for the future.

You can read a full copy of theĚýFuture of Professionals Report 2026: Actionable insights for corporate leaders paper here

Key insights:

• • • GCs place increased importance on commerciality — Business enablement is becoming the fastest-growing priority for corporate legal general counsel, creating an opportunity for UK law firms to not only provide legal advice, but to help GCs demonstrate business value to their C-Suite.

    • Business savviness serves as a differentiator — When asked why they would select one law firm over another, the proportion of UK GCs mentioning business-savvy saw a marked increase in our latest report, as did the concepts of commerciality, knowledge of the client’s business, and knowledge of the client’s sector.

    • Understanding the business is critical in an AI world — Clients are largely ahead of their outside firms on AI usage and sentiment. As AI automates more routine legal work, successful UK law firms can provide additional value above AI output by translating legal advice into practical business guidance and better commercial outcomes.

The definition of what it means to be a successful law firm in the United Kingdom is expanding. No longer is it enough to simply provide subject matter expertise for clients, with good lawyering becoming table stakes to even be considered for a panel. Neither is it enough to provide this expertise in a cost-saving and time-efficient manner, as clients are increasingly expecting of all firms.

Today, clients are expecting their outside UK law firms to go further into truly understanding the client’s business proposition, according to the recent 2026 State of the UK Legal Market Report from the Thomson Reuters Institute (TRI). And while efficiency and expertise remain top priorities, more corporate general counsel than ever before are rating business savviness and commerciality as key areas of focus. Clearly, GCs don’t just want legal advice from their outside firms, they want positive business outcomes.

Rather than provide an additional imposition on firms, however, forward-thinking law firm leaders in the UK will view this as an opportunity to stand out. Particularly in an AI-driven age in which low-level work continues to be automated, leaning into commerciality can offer lawyers a way to showcase their value while providing the positive business outcomes that clients truly desire.

Increased focus on enabling business processes

Client needs for outside counsel have evolved in recent years, simply because the corporate legal department itself has evolved. Business pressure has demanded that GCs turn their departments into a business enabler, rather than a cost center. And now corporate executives are measuring legal department success on how well it supports the rest of the organization.

Amid this pressure, GCs have seen mixed results. They have instituted a number of changes to their departments in recent years, leading to the development of corporate legal operations teams and an increased focus on success metrics that tie back to the rest of the business. And while 86% of global GCs say they believe their legal department is a significant contributor to organizational objectives, according to TRI interviews, only 17% of C-Suite executives agree. GCs are doing the work, but corporate executives aren’t seeing their preferred results.

In order to close that expectation gap, it’s unsurprising that GCs are doubling down on business enablement at the top of their agenda. When asked about their strategic priorities over the coming year, efficiency remained the primary focus for most GCs. However, business enablement represented the fastest growing priority, doubling its share of mentions to 27% of GCs in our latest research.

The definition of what it means to enable the business varies depending on the GC, of course. Some mentioned the need to enable business initiatives, others mentioned support specifically for M&A activities, while still others pointed to the imperative to meet changing business needs such as business innovation.

As a result, GCs are now increasingly turning their attention towards how their outside law firms can help with business enablement, and in doing so they’re shifting their criteria for choosing outside firms in the UK. When asked what drives favorability when selecting one firm over another, the proportion of GCs mentioning business-savvy rose to 37% in our most recent survey, compared to 31% from the year prior. Diving deeper into more specific sub-themes, the concepts of commerciality, knowledge of the client’s business, and knowledge of the client’s sector all saw increases in the portion of respondents mentioning those factors.

As the report notes, under real pressure to demonstrate their strategic value upwards, GCs are looking for external advisors that can help them meet their commercial goals. Those UK lawyers who want to stand out can begin by not only providing legal advice, but much-desired business advice as well.

The impact of commercial focus

Law firm leadership and partners in the UK have long said that they’re happy as long as their clients are happy. However, what does it mean for clients to truly be happy? That definition has shifted over time, and even has different permutations based on clients’ industry and geographic location.

When measuring their own success, UK general counsel place less emphasis on compliance & risk compared with their global counterparts, and less emphasis on cost & financial outcomes than do GCs based in the United States. Instead, UK GCs are heavily focused on quality & effectiveness, getting to the best outcome possible regardless of what it takes to get there.

UK law firms should be measuring their own success similarly. As the report notes, the ability to understand a client’s industry, strategic priorities, and risk tolerance — and then to translate legal advice into practical guidance for decision-making — has become central to how today’s clients select their outside counsel. Although work is cost-sensitive to a degree, law firms will ultimately be judged on their ability to deliver on high-stakes, bet-the-company matters, in which superior outcomes will outweigh marginal cost savings.

This is particularly true in an AI-centric environment. Previously, law firms were more readily able to compete on price for some low-level, repeatable work. Now, however, that work is increasingly being automated away. Clients are largely ahead of their outside law firms in both AI usage and sentiment towards AI’s impact on the legal industry, the UK report shows.

As the report notes, the ability to understand a client’s industry, strategic priorities, and risk tolerance — and then to translate legal advice into practical guidance for decision-making — has become central to how today’s clients select their outside counsel.

What’s more, corporate legal departments are becoming unafraid to use AI in those situations in which it makes cost-efficient sense with little legal risk. This means that law firms need to stand out not only from one another, but from the output that internal AI tools can provide.

Understanding the client’s business context can help provide this additional value, the report notes. That does not mean every lawyer needs to become a business consultant; but it does mean that firms must embed commercial understanding into the way they advise clients, staff matters, manage relationships, and measure success. Lawyers who can connect legal risk to business consequence will be better positioned to earn client trust, strengthen panel relationships, and demonstrate value in ways that AI tools cannot easily replicate.

As corporate legal departments in the Uk and elsewhere continue on their own path to become business enablers, they will increasingly expect their outside counsel to evolve with them. Those firms that thrive will be those that understand not only the law, but the client’s market, pressures, priorities, and definition of success.

In the UK legal market of 2026 and beyond, commerciality is not simply an added benefit — it is becoming central to what clients believe good lawyering looks like.

You can download a full copy of the Thomson Reuters Institute’s recent 2026 State of the UK Legal Market Report here

Key findings:

• • • Workloads grow, while staffing stays flat — Many government legal department professionals say their work keeps increasing while staffing remains stagnant; and many are turning to AI tools to improve capacity.

    • AI adoption is surging — Over the past year, AI adoption among government legal departments has spread rapidly, with federal and state agencies leading the way.

    • Unfortunately, AI oversight hasn’t surged — Many legal departments report that their AI governance is lagging behind adoption, with 20% of agencies having no AI use policy in place at all.

Government legal departments are facing an all-too-familiar problem: more work, more complexity, and the same number of staff to do the job, according to the Thomson Reuters Institute’s 2026 Government Legal Department Report, which captures the insights from 200 government legal department professionals at varying levels.

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2026 Government Legal Department Report

Threaded through these insights, some clear trends emerged. For example, technology — especially AI and other advanced tools — is increasingly serving as an extension of staff, expanding agencies’ capacity to manage rising workflow demands.

Increasing pressures across all levels

More than one-third of respondents report that their workload increased by more than 10% in the past year, with many handling between 21 and 50 legal matters per week. At the same time, workloads are becoming more complex, with more than one-third of respondents saying that more than half of the legal issues they face are complex, which is particularly notable at the state and federal levels.

Staffing shortages, a top concern in recent years, continue to persist. Three-quarters of respondents say their agencies experienced staffing shortages over the past two years, and almost two-thirds say they anticipate shortages into 2027.

Indeed, despite an increase in complexity and workload, attorney staffing levels have stayed the same for almost 40% of agencies, the report shows. And at the federal and state level, departments were more likely to have experienced a reduction of more than 10% of their staff.

AI adoption skyrockets, making governance more necessary than ever

More than one-quarter of respondents say their agency or department is now using AI tools, up from a meager 5% last year, with this increase taking hold at the federal and state level much more quickly. Among the different groups of respondents, one-third of federal and state government legal professionals report using AI tools compared to just 19% of those at county and city departments. Resistance to AI is diminishing, too; however, more than one-third of county and city legal departments still report having no plans to use AI.

Optimism toward AI is rising alongside implementation, the report shows. More individuals at the federal and state level feel optimistic than pessimistic about AI technology, which is an inversion of last year’s sentiment. Among county and city legal professionals, pessimism still remains more common. Among all respondents, confidential data exposure remains the top evaluation criterion when assessing these advanced tools.

The report underscores that this all points to a need for the establishment of strong governance models before adoption. Nearly two-thirds of government agencies and departments have an AI use policy in place or are developing one, respondents say. However, 1-in-5 departments and agencies are still without an AI use policy, risking unofficial use of prohibited AI tools.

Those agencies hesitant to implement AI technology are encouraged to view AI technology as a way to increase staff capacity amid flat staffing, rising workloads, and growing matter complexity. AI tools can help reduce strain on employees, contributing to better-managed workloads while reducing employee burnout. When appropriately vetted, however, AI technologies can reduce administrative burdens, increase legal research efficiency, and help those organizations facing trying to manage more work with the same staffing levels.

An actionable path forward

As the report makes clear, AI is no longer a future challenge; rather, it’s a present reality in a rising percentage of government legal departments. Indeed, the report outlines ways departments and agencies can move forward in this space, by beginning with lower-risk foundational tools like legal research and case management systems; and then investing time in developing thoughtful AI use policies and evaluation protocols. With responsible staff training and a thoughtful evaluation process, AI technologies can protect the valuable time and work-life balance of government legal professionals.

Increasing workloads are not optional for government legal departments, but how department leaders empower their staff to manage these workloads is becoming the differentiator.

You can download

a full copy of the Thomson Reuters Institute’s “2026 Government Legal Department Report” by filling out the form below:

Key highlights:

• • • The limits of the current system and good intentions — While the justice gap is not the fault of legal educators, their good intentions alone cannot close a systemic gap that requires new models of training and delivery designed for the long term.

    • A healthcare model for legal services is needed — Just as the healthcare industry relies on physicians, nurses, and physician assistants, the justice system needs a wider spectrum of trained and regulated legal providers; and American law schools are best positioned to educate, license, and oversee them.

    • States prove the model works — Alaska, Utah, and Arizona have already developed programs that train and certify non-lawyer legal service providers to help individuals navigate courts and address common legal issues, offering a replicable framework for those states willing to open regulatory doors.

Our nation’s healthcare system has wisely evolved past being one built on doctors alone. Yet in the legal industry, access to services remains largely tethered to a lawyer-only model that leaves millions of people unable to secure the help they need. Every day, tenants face eviction without representation, parents navigate custody disputes alone, and workers struggle to secure employment benefits or resolve workplace disputes because they cannot pay for legal counsel.

Legal professionals need to work together to create a broader, smarter, and more efficient legal workforce that can meet the public’s legal needs while maintaining the United States’ current legal standards of excellence. American law schools are best positioned to lead this effort; however, they will need to partner with regulators to educate, license, and oversee new categories of legal service providers who, like nurses and physicians’ assistants, can help expand the public’s access to critical support.

Preserving excellence while expanding access

American legal education has long been the global gold standard, producing leaders in law, politics, and business. Its rigorous curriculum, emphasis on critical thinking, and commitment to developing practical problem-solving skills have established a framework that many systems around the world aspire to emulate.

While meaningful innovations have taken place in legal education over the years, many are best characterized as refinements to the existing model rather than significant reforms. For example, curricular options today are more likely to include a wider variety of subject areas and teaching methods, however, most US legal education is still delivered through an in-person, full-time, three-year post-graduate Juris Doctor (JD) degree. While the overall quality of American legal education is exceptional, it is not filling our nation’s need for justice work.

The consequences are increasingly difficult to ignore. Low-income Americans receive no or insufficient legal help for 92% of their substantial civil legal problems, according to the Legal Services Corp.’s report. As a result, in many court systems, self-represented litigants have become the norm rather than the exception, whether the legal challenge involves housing, consumer debt, or family stability.

This is not the fault of legal educators, who often go above and beyond to help bridge the gap through the provision of free legal services and other efforts. Even so, it is the responsibility of legal educators to assist in designing and supporting new models of training and legal delivery to systemically narrow the gap for the long term.

Innovation beyond fine-tuning

Addressing this persistent and growing issue will require more than fine tuning. Instead, to meet the demands of a society increasingly characterized by inequality, social division, and complex interdisciplinary problems requires change that will better prepare our justice system for the future.

To get there, legal educators may have to sacrifice one part of what has long defined them: homogeneity. While a degree from a more elite law school is certainly rewarded in the entry-level employment market, the legal education provided at most of the accredited law schools in the US is more alike than different.

For law schools to help close the justice gap, increasing institutional pluralism is essential. Law schools can and should differentiate themselves by developing tailored solutions to address specific justice challenges within their reach. For example, Medical-Legal Partnership Clinics at and help low-income clients address legal issues that can impact their health outcomes. And students at the University of Arkansas School of Law provide assistance to small businesses, nonprofits, and rural municipalities that often cannot afford legal counsel though the university’s Community and Rural Enterprise Development Clinic.

To be sure, law schools cannot and should not do this alone. Law school deans have rightly encouraged legal education’s accreditation process to improve regulatory flexibility and promote responsible change. As a result, many schools are developing high-quality online programs that offer both access and excellence. These programs may expand the pool of lawyers over time, but they remain largely focused on JD education rather than the broader workforce that will be needed to improve the public’s legal health.

A framework for responsible expansion

To enhance access to justice, the legal profession needs to move beyond “educating lawyers” alone and expand into teaching law more broadly. The traditional JD degree will continue to be vital to our legal system; but just as healthcare relies on physicians, nurses, physician assistants and other licensed professionals, the justice system needs a wider spectrum of trained and regulated providers.

To get there, states must open their doors to a wider range of legal services providers. Unfortunately, many states — often for political reasons — continue to resist allowing limited-service legal providers to handle routine but still important legal needs.

Models for this approach already exist. , , and each have developed programs that train and certify non-lawyer legal service providers to help individuals navigate courts, understand their rights, and address common legal issues involving housing, family law, public benefits, and debt.

If state courts and legislators are serious about closing the justice gap, they should begin by opening their regulatory doors to these alternative legal providers, while providing responsible licensing and oversight mechanisms in collaboration with law schools in their state. If those doors are open, law schools can and will step through. Many law schools already have innovative master’s degree programs that are aimed at law-adjacent fields such as government contracts, human resources, compliance, and more. These non-lawyer educational programs can easily be tailored for alternative legal providers.

Keeping legal education in the hands of American law schools will properly balance access and excellence, ensuring the public continues to be served by qualified practitioners. Law schools have the skilled faculty, ethical underpinnings, and institutional infrastructure that’s needed to train and oversee the next generation of justice workers.

A robust justice system needs a full spectrum of professionals to meet society’s legal needs, much as our healthcare system relies on a range of trained providers. Until we build such a structure, the justice gap will remain exactly where it sits today, to the detriment of many citizens.

You can find more about theĚýchallenges facing law schools and legal education here

Key highlights:

• • • How AI-native firms redefine the lawyer’s role — AI-native firms like Paralex are gravitating toward a “technician” archetype, which puts less emphasis on the trusted-advisor dynamic that has long defined the attorney-client relationship.

    • The profession may be heading toward a two-tier split — As AI-native firms grow and normalize this operating model for a new generation of attorneys, the legal profession may bifurcate into a smaller cohort of relationship-driven advisors who provide deep, context-rich counsel; and a larger pool of proficient, AI-assisted technicians working at high volume.

    • AI firms can highlight how future lawyers learn — AI-native law firms are elevating a long-standing mentorship gap that threatens to erode how the next generation of lawyers develop independent judgment; and addressing it will require both creative AI-assisted solutions and more deliberate frameworks for deciding which cognitive tasks should remain done by humans.

The opportunity of starting a native AI law firm to test an idea is intriguing to some lawyers, especially those with an entrepreneurial instinct and determination to see the idea through. When founded , he aspired to democratize legal services for small businesses and leveraged AI to do so. His 29 years of practicing law had shown him the inefficiency and costly downsides of the billable hour; and he hypothesized that if the workflow could be automated with an attorney in the loop and could charge one-tenth of what it normally cost, demand would follow.

The reality has been more complicated and more instructive for the future of legal practice, Candelmo explains, as he offered a candid accounting of what Paralex has learned in practice.

Building for underserved small business owners

Paralex was built around a tiered service model covering everything from verified legal Q&A to AI-assisted contract drafting. AI handles the intake and first drafts at every stage, and the attorney handles the judgment. The small business transactional law vertical was a deliberate bet because the practice area is most amenable to pattern recognition and workflow automation. In addition, small business represents one of the largest pools of underserved legal clients.

Candelmo has learned that affordability alone does not unlock demand. The long-cited statistic that “60% of small businesses never use a lawyer because of cost” overstates how much of that gap is price-driven. Indeed, a meaningful portion of business owners appear to not want legal counsel at any price. Free AI tools have compounded this learning because ChatGPT, Claude, and Gemini can produce a plausible contract or answer a legal question at zero cost. “People feel that maybe it’s just good enough,” Candelmo says.

How AI-native firms redefine concept of a lawyer

AI-native firms like Paralex are discovering they need to develop exclusively the “technician archetype” among its lawyers. The attorneys who thrive in Paralex’s workflow are those most comfortable operating at volume, untroubled by the absence of ongoing client relationships, and motivated by clean execution rather than the slower cultivation of client relationships. Candelmo describes them as comfortable with gig work because they want to be paid for what they produce rather than chasing invoices.

Young attorneys need to master the tools but not outsource their judgment to them. And they should seek out senior attorneys and cultivate human relationships that will make them more than a technician.

Candelmo shares that the trusted-advisor attorney who deeply knows a client’s business, anticipates problems before they arise, and provides counsel grounded in years of accumulated context is largely absent from the Paralex experience. He describes AI-native firms’ role as taking out the unnecessary back-and-forth that occurs in traditional law firms’ practices. At the same time, AI-native firms start out narrowly servicing a vertical by providing legal services that are optimizing for efficiency and relatively less complex.

The implication is significant for lawyers and their professional identity. As native AI firms grow and attract a generation of attorneys for whom this model is normal, the profession might be more likely to bifurcate between a smaller cohort of relationship-driven advisors on the one hand, and a larger pool of technically proficient, AI-assisted attorneys working at volume on another.

A generation of lawyers with no one to learn from

What Candelmo says he worries most about is who will teach the next generation of lawyers how to think. In AI-native environments, a junior attorney working at high throughput may review AI-generated output quickly, trust it, and move on. The output looks complete — but there is no obvious signal that something important was missing and no senior attorney to say why it matters.

Candelmo’s proposed solution is a second layer of AI tools, such as simulation tools, that can function like a senior lawyer. It reviews the initial output, flags gaps, and provides the kind of annotated feedback that would have come from a partner review in a traditional law firm.

His advice to young attorneys is to master the tools, but do not outsource your judgment to them. And they should seek out senior attorneys and cultivate human relationships that will make them more than a technician, Candelmo adds. “Ensure that your humanness, your human relationship skills make you stand apart.”

As native AI firms grow and attract a generation of attorneys for whom this model is normal, the profession might be more likely to bifurcate between a smaller cohort of relationship-driven advisors on the one hand, and a larger pool of technically proficient, AI-assisted attorneys working at volume on another.

In addition, , Partner at Foley and Gardner and adjunct professor at the teaches at the University of Wisconsin Law School, goes one step further and advocates for adding a conscious step before instinctively turning to AI tools. He suggests each lawyer first ask themselves, “What cognitive function is being delegated to GenAI at each step in the workflow?”

In the current state, the AI conversation within the legal ecosystem continues in a good-or-bad binary rather than simply asking when AI use is beneficial and when it is risky, which is increasingly what law students are asking for. For example, the announced a policy that bans students from using AI for class assignments and during exams, although students can still use AI for research to identify sources.

The experiences of Candelmo and Paralex, alongside the broader debate playing out across the legal ecosystem, make it clear that the legal profession is being forced to make deliberate choices about what lawyers are for, which cognitive tasks should remain human, and how professional judgment is developed and passed on.

The law firms and legal institutions that build thoughtful frameworks for when and how AI should be used will create a profession that is both more efficient and more capable of producing the kinds of lawyers that clients and society will continue to need.

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Key takeaways:

• • • The dulling effect is real, but the root cause is older than AI — Wherever gatekeeping institutions reward a narrow formula, their output converges long before any chatbot enters the picture. AI then accelerates optimization toward your already selected criteria.

    • Using AI for efficiency alone leaves the creative upside on the table — While most organizations deploy AI for simple drafting tasks, the bigger payoff comes from using it as a discussion engine — a sort of sparring partner that pressure-tests ideas and pushes thinking past the first plausible answer.

    • The highest-leverage intervention is reforming what you reward — The fix for this is upstream of the technology, and it comes from giving people time to make sure unconventional ideas actually survive your organization’s sorting mechanisms.

A tension sits at the center of nearly every serious conversation about AI and organizational strategy, and most leaders can feel it even if they haven’t named it yet.

On one side is the promise that AI can make teams more creative. That it can accelerate brainstorming, provide deeper research, identify hidden connections, and pressure-test ideas before they reach a client or a boardroom. When used well, AI is not a replacement for thinking but an amplifier of it.

On the other side, of course, is the fear that regular AI use is quietly dulling the creativity it’s supposed to enhance. That real fear is that the more people lean on these tools, the more their thinking converges toward the same polished, plausible, and fundamentally safe middle ground — and that the less people work their creative muscles, the more they atrophy without them realizing it. This trade-off, swapping originality for efficiency, is a losing exchange.

Both of these intuitions are reasonable and both are, to varying degrees, correct. However, they aren’t equally weighted. The purely cautious camp is taking the bigger gamble, because any competitor that cracks the problem by figuring out how to capture AI’s creative upside while managing the dulling effect gets both the innovation edge and the efficiency gains. The cautious organization doesn’t just miss the upside, it falls behind on both fronts.

The catch is that cracking the problem requires correctly diagnosing what’s actually killing your creativity — and a prominent recent essay on this exact topic gets it instructively wrong.

A good question, poorly tested

Rebecca Winthrop, a senior fellow at the Brookings Institution and director of its Center for Universal Education, recently published in The New York Times arguing that AI is constricting creative thinking. Her central claim is that while chatbots produce polished language, they’re masking a narrowing range of underlying ideas — and this is especially dangerous for students, whose creative development is still taking shape.

The piece is worth reading, and not just as a foil. Winthrop draws on from Georgetown neuroscientist Adam Green, whose team has been tracking the range of ideas in college application essays before and after ChatGPT’s release. Green’s findings related to the before/after tracking study (which have not yet been peer-reviewed) are striking, finding that while post-ChatGPT essays used more diverse and colorful vocabulary, the ideas beneath that language converged. Human judges rated the AI-era essays as more creative, even though the substance had narrowed. In a separate study by Green’s team, cited by Winthrop, human-written essays contributed up to eight-times more novel ideas than AI-generated ones.

The fear is that regular AI use is quietly dulling the creativity it’s supposed to enhance, and the real fear is that the more people lean on these tools, the more their thinking converges toward the same polished, plausible, and fundamentally safe middle ground — and the less people work their creative muscles.

And Winthrop flags serious concerns that deserve far more attention than they typically get. For example, AI’s homogenizing pressure falls hardest on those students who sit farthest from the mainstream, including neurodivergent students and those from racial and linguistic minorities. That finding alone should be shaping education policy conversations and acting as a warning for innovation-conscious reformers.

Here’s where Winthrop’s piece stumbles, however, and where it becomes a cautionary tale for organizations that may be thinking about their own AI and innovation strategies. The evidence Winthrop chooses to build her case on — the college admissions essay — is possibly the worst genre in American education for measuring whether AI is killing creativity. Because the creativity in college admissions essays was already dead.

I should know. I’m one of its murderers.

The most templated genre in America

The college admissions personal statement has been reverse-engineered for decades. Well before any large language model existed, applicants had cracked the code: Be damaged, but not too damaged; be resilient but make it look like you did it yourself; and be whole now, because the institution wants guaranteed successes, not risky projects. And all of this must be delivered in a tone that makes the committee feel good about their institution’s role in a meritocratic society. Deviate from this formula and you’re taking a risk, but hit every beat and you’re in the pile that moves forward.

I know this because I lived it recently enough to still remember the specific frustration of trying to fit my own experiences into that template at the age of 17, twisting and contorting experiences I’d actually lived through into the shape I knew admissions readers were looking for while sanding away the human beneath when it didn’t fit. The authentic version of my story wasn’t what they wanted, the version that hit the beats was.

And there’s a further detail conspicuously absent from Winthrop’s essay: The college admissions consulting industry. It’s enormous, it’s been around for decades, and its entire business model is teaching applicants to write to the template. Some of these consultants charge $5,000 or more, and their product isn’t creativity, it’s optimization. They teach students to identify what the admissions committee rewards and deliver exactly that, with the rough edges smoothed away and the personal experiences torqued into the right emotional shape.

My family took this seriously enough to invest in help, and I was fortunate enough they had the means to do so. I had one of those consultants. Mine cost $2,000, and my parents had to sell my mom’s pinball machine to pay for it. I think sometimes about what it says that the path to higher education ran through a professional who taught me, essentially, to write to a formula rather than to present myself in a way that would have given the committee a more honest, unique portrayal of just who they were letting into their institution. The consultant didn’t make me less creative; the system that made the consultant necessary did.

And this is the blind spot in Winthrop’s argument. She treats pre-ChatGPT essays as the baseline for authentic creative expression, but that baseline was already shaped by an industry dedicated to template optimization. So when Green’s research finds that post-ChatGPT essays use richer vocabulary but converge on familiar ideas, the question worth asking isn’t just whether AI caused a measurable shift (Green’s controlled experiments suggest it did) but whether the underlying ideas were already converged at a more fundamental level that the metrics don’t capture. In essence, all AI may have done is make that convergence more visible while democratizing the surface polish.

There’s an entirely different version of Winthrop’s essay waiting to be written — one in which the same data tells a democratization story rather than an erosion story. Where a free chatbot gives a first-generation college student the same surface-level advantage that a $5,000 consultant gave wealthier applicants for years. That’s not a comfortable reframe for institutions already invested in the idea that their selection processes brings forth authentic individuality — but it’s the reframe the data actually supports.

The template always comes first

This isn’t unique to college admissions. Wherever institution rewards a narrow formula, it gets gamed — and the gaming predates whatever technology that has made it easier.

The video essayist Sarah Z traced exactly this pattern in , which makes the gap in Winthrop’s argument clearer. When the publishing industry rewarded a specific shape of trauma narrative in the 1980s and ’90s — suffering resolved through individual resilience — the template grew so predictable that fabricators outcompeted honest writers. Laurel Rose Willson sold a satanic-ritual-abuse memoir and, years later, a Holocaust-survival story, citing the same self-inflicted wounds as evidence for both. Publishing houses weren’t fooled just because they were careless, they were fooled because they’d built a machine that searched for formula — and the system that rewards a narrow pattern is the same one that makes it exploitable.

AI doesn’t create that convergence, it just accelerates the optimization toward whatever you’re already selecting for. Blaming AI for homogenized output in an already-homogenized system is like blaming your GPS for traffic on the BQE — the bottleneck was there long before the tool arrived.

If your organization has ever received a stack of pitch decks, strategy memos, or RFP responses that all hit the same beats in the same order, congratulations! You’ve built your own admissions committee, but don’t blame AI.

AI doesn’t create that convergence; it just accelerates the optimization toward whatever you’re already selecting for. Blaming AI for homogenized output in an already-homogenized system is like blaming your GPS for traffic on the BQE. The bottleneck was there long before the tool arrived.

Threading the needle

Of course, none of this means the concern about AI and creativity is unfounded. The dulling effect is real, and anyone who uses these tools regularly has probably felt its subtle gravitational pull toward the center. Or in the way a chatbot’s first suggestion can quietly foreclose any other directions you might have explored on your own, or how it may produce something that sounds polished but carries none of your voice

A different research team — Anil Doshi and Oliver Hauser, behind the , Winthrop herself points to — put a name to the mechanism, anchoring. Handed an AI-generated idea, writers locked onto it, narrowing the range of what they produced before they’d really begun.

However, the solution on an organizational level isn’t to restrict the tool; rather it’s to address the institutional and behavioral factors that determine whether the tool narrows thinking or expands it.

In this determination, three things matter most:

First, use AI as a discussion engine, not just an automation tool — There’s a meaningful difference between asking a chatbot to draft something for you and using it to create something with you. This article is a case in point. I didn’t read Winthrop’s essay and immediately decide to write a response. Instead, I spent almost half an hour talking to Claude about the article, debating the argument, testing my objections, diving into Green’s research more deeply, and connecting the piece to ideas I’d been thinking about from completely different contexts, such as the Sarah Z essay. This article emerged from that conversation unintentionally, and it would not have existed without it.

Further, the ideas emerged pressure-tested and sharpened through a process that felt more like sparring than delegation — and that’s exactly the kind of process organizations should be targeting. Most organizations deploying AI are using it for efficiency — drafting, summarizing, formatting — and that’s fine. However, if that’s all you’re doing, you’re leaving the creative upside untouched, and your people are feeling the dulling effect without the compensating benefit. It takes an intentional push from leadership to get teams using AI as a thinking partner rather than a shortcut.

Second, give people time — This sounds obvious, but it matters specifically because of how AI interacts with time pressure. When people are rushing, they take the first adequate output and move on. With traditional workflows, shortcuts save time at the cost of quality or risk. With AI-assisted workflows, however, shortcuts save time at the cost of originality, because the first output from a chatbot is almost always the most conventional one. It’s the statistically average response, and reaching the edges takes iteration, pushback, and follow-up prompts that challenge the initial direction. That takes time, and if your people don’t have it, they’ll use AI the way a stressed applicant uses a college essay consultant, producing the safest possible version of whatever the system rewards rather than the innovative one which could change the game.

Third, reform what you reward — This is the intervention that actually addresses the root cause, and it’s the one most organizations will resist because it requires examining their own sorting mechanisms. If your evaluation criteria, your promotion structures, your review processes, and your RFP scoring rubrics all select for the safe and conventional, then AI will only turbocharge that selection.

You’ll get the template faster and more polished than ever, much like the admissions committee that rewards a narrow emotional arc and gets 300,000 identical essays. Or, if your firm rewards the pitch deck that hits every expected beat and takes no risks, AI will produce that pitch deck beautifully — and you’ll wonder why innovation has stalled.

Again, the intervention is upstream of the tool. What does your organization actually do when someone brings in an unconventional idea? What happens to the proposal that doesn’t fit the template? If the answer is that it gets smoothed out in review or tossed altogether, that’s not an AI problem.

The old traps didn’t disappear

Winthrop is right that creative thinking is something to protect and nurture. She’s also right that AI introduces new pressures that deserve serious attention. And she’s right that the stakes are highest for the people whose perspectives are already farthest from the mainstream.

But the college admissions essay wasn’t homogenized by ChatGPT, it was homogenized by decades of institutional selection pressure that rewarded a single template and penalized everything that didn’t fit. AI didn’t create that problem, it just made the template accessible to everyone, including the families that couldn’t previously afford $2,000 and a pinball machine to get their kid across the threshold.

Similarly, your organization’s creative output won’t be determined simply by which AI tools you adopt. It will be determined by what your leadership rewards, what your processes select for, and whether your people have the time and incentive to push past the first plausible AI-supplied answer.

The technology is new, but the traps are very old. And if you want to use AI to make your organization more innovative, the place to start isn’t the tool — it’s the template.

You can find moreĚýĚýfrom the Thomson Reuters Institute here

Key takeaways:

• • • Productivity softened at an unexpected time — Productivity declined to -0.4% in Q1 2026, even as demand remained strong at 2.7% growth.

    • Value per lawyer provides the clearer signal — Fees worked per lawyer (or value per lawyer) continues to grow, reflecting the combined impact of hours and rates despite volatility in productivity.

    • Margin pressure is emerging unevenly — In the Midsize segment, value growth is trailing expense growth, creating early signs of compression.

The Q1 2026 results present an unusual combination. Demand grew by 2.7%, well above historical norms, and worked rate growth remained elevated, with Am Law 100 firms pushing toward double digits, according to the Thomson Reuters Institute’s recently releasedĚýQ1 2026 Law Firm Financial Index. These inputs would typically support strong overall performance.

Yet productivity declined slightly, falling to -0.4% after six months of positive growth. On its own, that change is modest. In context, however, it reflects a more interesting shift in how performance is being generated.

The key is understanding what productivity measures and what it does not. Law firms’ traditional measure of productivity is hours worked per lawyer, which tracks the average number of hours logged by a firm’s lawyers to give an estimate of efficiency. However, that traditionally has not incorporated pricing mostly because, historically, law firms have focused more on the hourly output of lawyers as the mark of success. This means firms were often not concerning themselves with whether the pattern is profitable, let alone taking into account factors like demand elasticity or automation’s impact on the equation.

This is changing, however. As more and more revenue growth is being driven by rate increases rather than increases in demand or hours per lawyer, the disconnect is being magnified. And this distinction helps explain why strong inputs are producing a more muted output and why understanding that relationship is vital for firm leaders to get an accurate picture of how large law firm economics are evolving.

The divergence between hours and value

To see that situation more clearly, it is necessary to move from activity-based metrics to value-based ones — and fees worked per lawyer (or what we’re calling value per lawyer) provides that view. Fees worked is a pre-realization revenue proxy, representing the total value a firm produces before billing and collections take over, then averaging it across lawyer headcount. This method accounts for scale, giving a cleaner read on efficiency than looking at just raw hours. Because fees worked per lawyer folds rates and hours into a single measure, it captures the value that the traditional productivity metrics leave out.

As shown in the chart below, the industry is experiencing a widening gap between the hours lawyers work and the value that their work generates even as demand has remained consistently positive and rate-driven growth has stayed strong across recent quarters. As a result, productivity has been more volatile and recently turned negative. At the same time, fees worked per lawyer (or full time equivalent) has continued to trend upward, indicating that value per lawyer is still increasing rapidly despite what the old metric might have historically implied.

That means that law firms are producing far more value per lawyer even though hours per lawyer have softened slightly. The factor magnifies once you consider what period firms are measuring against. The first quarter of 2025 was exceptionally strong, creating a high baseline that can subdue the current level of growth — against a “normal” year, law firm performance would be even greater.

While this is a historically recent phenomenon, it’s not one unique to 2026. Strong rate growth has often offset weaker productivity for the last couple of years. What makes the first quarter of this year more unique is that it no longer seems uniformly true across the market.

Where performance is beginning to diverge

The Q1 2026 data shows a clear separation in how firms of different sizes are translating demand and rates into value per lawyer. Among Am Law 100 firms, for example, strong rate growth remains the primary driver of revenue performance, which is being supported by disciplined headcount management that’s kept efficiency high. These firms have continued to push pricing while maintaining selectivity in hiring, allowing value per lawyer to remain resilient even as productivity softens.

The Am Law Second Hundred has embraced a different strategy. Firms in this segment are continuing to pursue growth through lateral hiring and increased capacity. This supports overall revenue but can dilute per-lawyer metrics as new lawyers ramp up. The result is softer value per lawyer despite the segment’s continued headcount expansion.

The most consequential shift is occurring in the Midsize law firm segment. Rate growth has slowed for Midsize firms, while those in other segments have maintained or exceeded prior pacing. At the same time, expenses are accelerating and are now outpacing overall fees worked growth. This creates a dynamic in which value per lawyer is still increasing, but it’s running closer to expenses.

What this all means for profitability

In the near term, there is no indication of a broad downturn. Value per lawyer continues to grow despite declines in hours per lawyer, and pricing remains strong, particularly at the top of the market. At the same time, however, the balance between value and cost is beginning to shift, most notably in the Midsize segment, where expenses are rising faster than revenue proxies.

Looking ahead, we will keep our eyes on value per lawyer, which is developing into a critical performance metric. If this metrics continues to strengthen as comparisons normalize, the softness in Q1 will likely prove temporary. If it remains constrained, particularly in segments already facing cost pressure, however, it may point to a more persistent challenge.

The broader takeaway reflected in the Q1 2026 LFFI data is that law firm performance is no longer defined primarily by the traditional measures such as hours per lawyer at the forefront without the context of rates. Indeed, this should no longer be given as much psychological weight as it was before the pandemic. In a market shaped increasingly by pricing power, the more important question for today’s law firm leaders is how much value each lawyer is generating and whether that value is keeping pace with the cost of delivering it.

You can download a full copy of the Thomson Reuters Institute’sĚýQ1 2026 Law Firm Financial Index here

Key insights:

• • • AI is now a common facet of the legal landscape — AI is increasingly a part of legal workflows across aspects of the practice, involving not only work matters, but also interactions with clients, opposing counsel, and the courts.

• • • Foundational understanding of AI in legal is crucial— The guide provides concise, practical information that lawyers and legal professionals can use to get a better grasp on AI use in legal practice

• • • Guidance needed in a fast-changing environment — AI technology and its uses, its limitations, and lawyers’ professional responsibilities in the practice of law are evolving rapidly — and this guide provides needed guidance and help in navigating today’s environment.

AI is influencing virtually every corner of the legal profession, impacting how legal research is conducted, documents are drafted, discovery is handled, client expectations are managed, and how courts are addressing questions of professional responsibility. Whether lawyers themselves are using AI or not, they are likely to at least be on the receiving end of AI-assisted work product from opposing counsel or clients.

To help bring clarity to this rapidly changing legal arena, the Thomson Reuters Institute and the have released the — a resource for lawyers and legal professionals who want to approach AI with clarity, confidence, and professional rigor. This “Foundational Overview” is the first installment of the “AI Guideline Series” being published by Thomson Reuters Institute and ILTA, with additional guides to be published within coming months.

You can also access the newly published

For AI-enabled lawyers to be the most effective, it’s important that they first understand the complex legal and technical terminology related to AI, as well as the different categories of AI, within which legal practice these technologies best fit, and the professional responsibilities that accompany their use.

Practical, concise overviews

The AI Guide is a resource for establishing a solid foundation by using the most current information in this fast-moving environment. Written with contributions from a variety of leading attorneys, legal scholars, and legal technologists, the Guide offers lawyers a practical orientation to today’s AI landscape and the issues that matter most for their legal practice.

The Guide contains concise overviews on:

• • • the current state of AI adoption across the legal profession
    • essential AI terminology
    • the major categories of AI technologies and platforms
    • the situations in which AI is often used to support legal work
    • the ethical and professional responsibility considerations that lawyers must understand, and
    • the emerging trends likely to shape AI use in legal in the years ahead.

The Guide also offers a collection of additional resources for more in-depth exploration.

As AI shows itself to be remarkably effective at assisting with many routine, time-consuming, and information-intensive legal tasks, it also continues to require careful human judgment, verification, and oversight to be most effective. That’s why understanding AI’s strengths and its limitations is becoming an essential professional skill.

A different way of interacting with information

Unlike previous technologies, AI is not simply another software application. It is a fundamentally different way of interacting with information — one that’s capable of generating analysis, drafting documents, identifying patterns, and assisting with increasingly sophisticated legal work.

AI’s application within the legal profession brings forward unique, specific considerations. It also raises questions — as well as answers that are still evolving around accuracy, trustworthiness, ethics, professional responsibility, and many other issues.

Today, these are no longer theoretical discussions; rather, they’re practical questions that lawyers are confronting every day, regardless of whether those lawyers are currently using AI in their workflows.

The “AI Guide for Legal Professionals: A Foundational Overview” can give lawyers a foundational understanding on how they and other legal professionals can integrate AI into their legal practice, better understand their responsibilities, and critically evaluate new AI technologies as they evolve.

You can access the newly published