Key takeaways:

• • • Agentic AI poised for adoption uptick 鈥� Agentic AI is following GenAI’s rapid adoption in the legal industry, with less than 20% of firms currently implementing agentic systems but half planning or considering adoption in the near future, according to a new report.

    • Adoption depends on human oversight answers 鈥� Legal professionals are generally optimistic about agentic AI’s potential, but successful adoption depends on explicit guidance about human oversight and the lawyer’s role in maintaining ethical standards.

    • Time to retool AI education? 鈥� Agentic AI’s increased autonomy introduces new oversight and ethical challenges for law firms, making targeted education and clear guidance essential to understanding the differences from GenAI.

Over the past several years, law firms and corporate legal departments have turned towards generative AI en masse. At the beginning of 2024, just 14% of all law firms and legal departments featured an enterprise-wide GenAI tool. Just two years later, that number had already risen to 43% of all firms and departments, according to the 2026 AI in Professional Services Report, from the 成人VR视频 Institute (TRI). For large law firms or legal departments, those percentages 鈥� not surprisingly 鈥� are beginning to approach 100%.

With GenAI adoption now this widespread, legal industry leaders are now turning their attention to two primary initiatives. One, of course, is how to get the most out of the AI tools they already have 鈥� a task that is proving a bit elusive. Currently, less than 20% of lawyers say their organizations measure AI鈥檚 return-on-investment, and most corporate lawyers say they have no idea how their outside law firms are approaching AI. Thus, instituting not just AI tools, but also an AI strategy is the second top priority for law firms and corporate legal departments in 2026 and beyond.

However, even as the legal industry reaches a tipping point in adopting GenAI tools, technology innovation still continues unabated. Agentic AI has emerged as the next wave of innovation that could change how lawyers work on a daily basis, offering a way to autonomously complete multi-step tasks. For example, agentic AI systems are already being built for the legal industry that independently researches a regulation or law, drafts a document based on the finding, identifies pitfalls, and revises the document, with stops for human guidance only instituted as desired.

According to the AI in Professional Services Report, the legal industry is already making headway towards implementing agentic AI systems. For agentic AI to truly take hold in legal, however, lawyers still require more education around not only how it differs from the GenAI systems they already have in place, but also when and where human intervention needs to occur within an agentic system.

The early stages of agentic AI

Examining current agentic AI adoption for the legal industry almost takes one back in time 鈥� two years, to be exact. Following the public release of GenAI in late-2022, many legal industry organizations spent 2023 evaluating and experimenting with AI systems, usually with a small working group of interested guinea pigs. As a result, only 14% of survey respondents said their law firms or corporate legal departments were engaged in organization-wide GenAI rollouts at the start of 2024. However, more than half of respondents said their organizations expected to be rolling out large-scale GenAI systems over the next 1 to 3 years. The intervening two years since then have proved that prediction to be largely true.

Agentic AI usage in the first half of 2026 looks largely similar to GenAI in 2024. The legal industry started to experiment with agentic AI at the beginning of 2025, with an eye towards actual implementation in 2026 and beyond (particularly as legal software providers began to integrate agentic systems into their own products). As such, less than 20% of recent survey respondents say their organization is engaged in widespread agentic AI adoption, but with about half of respondents said their organization is either planning to use or considering whether to use agentic AI in the near future.

By and large, lawyers feel positive about the agentic AI movement. When asked about their sentiment towards agentic AI, 51% of legal industry respondents said they felt excited or hopeful, while just 19% said they felt concerned or fearful. Further, about half (47%) said they actively believe agentic AI should be used for legal work, while 22% felt it should not, with the remainder saying they were unsure. These figures largely track with the sentiments expressed about GenAI in 2024, which have only grown over time from about 50% positive two years ago to two-thirds of all legal professionals feeling positive currently.

This all lends further credence to a rise in agentic AI usage similar to what law firms and corporate legal departments experienced with GenAI over the course of 2024 and 2025. Indeed, when asked when they expect agentic AI to be a central part of their workflow, few have baked agentic systems into their daily work currently, but a majority of legal industry respondents expect it to be central within the next 3 to 5 years.

The unique barriers of agentic AI adoption

Agentic AI does differ from GenAI in one crucial area that may limit its growth potential within the legal industry, however 鈥� autonomy. By and large, GenAI systems operate on a back-and-forth basis: Users provide the tool a prompt, receive its output, and then iterate back-and-forth from there. Agentic AI is intended to be more automated by design, only requiring human input at pre-determined points in the process. And that makes some lawyers understandably nervous.

When asked why they might feel hesitant about using agentic AI for legal tasks, the most common answer was a general fear of the unknown, but the second most common answer dealt with the need for careful monitoring and oversight. In fact, some respondents said they were excited about GenAI, but more cautious about agentic AI鈥檚 potential.

鈥淎gentic AI, while exciting, to me removes oversight a step too far,鈥� said one such lawyer from a US law firm. 鈥淚 like the idea of prompting and reviewing a result. It is something else to have a machine have so much autonomy in the actual doing of a thing and potentially acting on my behalf without that very concrete review.鈥�

Please add your voice to 成人VR视频鈥� flagship , a global study exploring how the professional landscape continues to change.听

An assistant GC at a US company also pointed to potential privacy and security concerns, adding: 鈥淭he fact that agentic AI operates in a much more autonomous way, with a lack of control from the user, means there are many unknowns that are hidden beneath the process.鈥�

For law firm and corporate legal department leaders looking to potentially implement agentic AI systems into their practice, this means re-thinking what AI education and training will mean moving forward. Beyond that, however, legal AI educators also will need to make sure to pinpoint and perhaps over-explain those specific instances in which human oversight needs to occur in agentic systems. More autonomous does not mean fully autonomous, and particularly for lawyers with ethical duties to their work product, lawyer oversight will in fact be a necessary part of any agentic system.

For law firm or legal department leaders, that means that finding the right balance between efficient workflows and human intervention will be key to agentic AI adoption. And those organizations that can best communicate human-in-the-loop to their professionals up-front will be rewarded with more increased and reliable adoption.

Clearly, lawyers feel positively about the agentic AI future, after all. They just need it spelled out explicitly as to what the lawyer鈥檚 role will be in this new paradigm.

鈥淎gentic AI is powerful, but its moral compass must come from humans,鈥� one UK law firm barrister noted aptly. 鈥淟awyers are trained to safeguard fairness, rights, and the rule of law 鈥� principles that should guide how AI is designed, governed, and deployed. Hope lies in our ability to shape AI through these values for fairer values for society as a whole.鈥�

You can download a full copy of the 成人VR视频 Institute鈥檚听2026 AI in Professional Services Report听here

Key takeaways:

• • • Employees face contradictory messages or none at all 鈥� Nearly 40% of professionals surveyed report receiving conflicting directives about AI usage from clients and leadership, while half report no client conversations about AI have occurred at all.

    • Workers lack feedback on whether their AI efforts matter 鈥� Professionals who are experimenting with AI tools without knowing if their efforts are valued are left uncertain about whether investing time in developing AI skills is worth it.

    • Job displacement fears are rising 鈥� While employees remain cautiously optimistic about AI usage in their workplace, concerns about job displacement have doubled over the past year.

As generative AI (GenAI) tools flood into legal and accounting workplaces, organizations are deploying powerful technology without giving their employees clear directions on how to use it. Worse, some have received no guidance.

New research that underpinned the recent 2026 AI in Professional Services Report听from the 成人VR视频 Institute (TRI), reveals a disconnect between AI availability and organizational guidance, which is creating confusion that may undermine both employee experience and the technology鈥檚 potential value. (The report鈥檚 data was gathered from surveys of more than 1,500 legal, tax, accounting, and compliance professionals across 26 countries.)

Employees navigate inconsistent AI policies or none at all

Approximately 40% of the professionals surveyed said they received contradictory guidance from clients and leadership about AI tool usage, with directives both encouraging and discouraging their use on projects and in RFPs. This ambivalence is slowing down decision-making at the front lines 鈥� a place in which AI could deliver the most value.

Equally concerning is the fact that half of professionals indicated that no conversations with clients about AI tool usage have taken place yet. And when discussions do occur, concerns about data protection and accuracy are the main topics.

This confusion extends to external relationships as well. More than two-thirds of corporate and government clients remain unaware of whether their outside professional service providers are even utilizing GenAI. And the majority of clients have provided no direction whatsoever to their outside law firms concerning AI use, respondents said.

Organizations often ignore what employees need to know

Perhaps most revealing is how organizations are measuring 鈥� or failing to measure 鈥� whether their AI investments are paying off. Almost half of respondents said their organizations are not measuring return on investment (ROI) at all. Among the minority (18%) of respondents that said their organizations do track ROI, the metrics they use tell a story about organizational priorities. That fact that internal cost savings and employee usage rates lead the list suggests a focus on efficiency over innovation or quality improvements.

This measurement vacuum has consequences for employee experience. Without clear success metrics, employees lack feedback on whether their AI experimentation is valued, discouraged, or even noticed. The absence of ROI frameworks also makes it hard to justify training investments or dedicated time that allows employees to develop AI fluency.

AI usage doubles while support systems fall behind

AI usage among professional service organizations has nearly doubled over the past year, and professionals are increasingly integrating these tools into their workflows, the report shows. Yet organizational infrastructure that could support this adoption surge lags badly. Most professionals said they expect GenAI to become central to their work within the next two years 鈥� but that may be happening without roadmaps from their employers.

In addition, notable barriers in employees鈥� usage of AI remain. When asked what barriers could prevent their organization from more widely adopting GenAI and agentic AI, almost 80% of professionals cited concerns over inaccurate responses. Other concerns included worries over data security, privacy, and ethical use. Most of these suggest an ongoing lack of trust in GenAI.

The tool landscape adds another layer of complexity. Publicly available tools dominate current usage, with more than half of respondents (57%) citing their use, while proprietary or industry-specific solutions remain largely in the consideration phase. This suggests employees are often self-provisioning AI tools rather than working within enterprise-supported ecosystems. This potentially opens organizations to increased risk exposure because of security gaps, compliance risks, and inconsistent quality.

Employees鈥� job displacement fears increasing

Despite these challenges, employee sentiment toward AI remains cautiously optimistic. More than half (57%) of respondents said they are either hopeful or excited about the future of GenAI in their industry. Clearly, employees see AI’s potential to enhance their efficiency, automate routine tasks, and free up their time for higher-value work.

At the same time, hesitation and concern among employees are rising, particularly around accuracy, job displacement fears, and the unknown implications of autonomous AI systems. Notably, concerns about job displacement have doubled over the past year, and this trend demands organizational attention and transparent communication about a workforce strategy to combat this concern.

What organizations need to do now

Organizational leaders who are serious about positive employee AI experiences need to step up their efforts to provide guidance to employees and gain the ROI that AI promises. Specific steps they can take include:

• • • Draft clear and consistent guidance 鈥� Create explicit policies for employees about in which instances AI use is encouraged, required, or prohibited. This includes client communication protocols, data-handling requirements, and escalation procedures in those situations in which AI outputs seem questionable.
    • Develop and implement meaningful ROI metrics 鈥� Organizations must move beyond usage rates and cost savings as key success measurements. Tracking data points that capture quality improvements, time redeployed to strategic work, and client feedback on AI-enhanced deliverables present a more comprehensive picture. Also, leaders need to share these metrics transparently in order to give employees an understanding about organizational priorities.
    • Invest in structured learning 鈥� The survey shows professionals are experimenting with dozens of different tools from ChatGPT to specialized legal tech platforms. Organizations should curate recommended toolsets, provide hands-on training, and create communities of practice in which employees can share effective prompts and use cases with other users.

Our data shows that the employee experience around AI adoption reveals a workforce that is hopeful but hungry for direction and concerned about job impacts. Leaders who implement these actions effectively are more likely to unlock the strategic value that AI promises while building the trust and competence needed for their organizations and its employees to thrive in an automated future.

You can download a full copy of the 成人VR视频 Institute鈥檚听2026 AI in Professional Services Report听here

Key findings:

• • • AI adoption accelerates across professional services听鈥� Organization-wide use of AI in professional services almost doubled to 40% in 2026, with most individual professionals now using GenAI tools, and many preparing for the next wave of tools such as agentic AI.

    • Strategic integration and measurement lag behind usage 鈥� While AI use is widespread, only 18% of respondents say their organization tracks ROI of AI tools, and even fewer measure AI’s impact on broader business goals such as client satisfaction or revenue generation.

    • Communication around AI use remains inconsistent听鈥� While most corporate departments want their outside firms to use AI on client matters, less than one-third are aware whether their firms are doing so. Meanwhile, firms report receiving conflicting instructions from clients about AI use, highlighting a need for clearer dialogue and shared strategy around AI adoption.

Over the past several years, AI usage within professional services industries has come into focus. As we enter 2026 in earnest, the early adoption phase of generative AI (GenAI) has come and gone. Today, most professionals have experimented with some form of GenAI, and many organizations integrated GenAI into their workflows 鈥� and now, a number are preparing for the next wave of technological innovation such as agentic AI.

Given this, the question for professionals and organizational leaders has now become: What will be AI鈥檚 long-term impact on my business?

Jump to 鈫�

2026 AI in Professional Services Report

To delve into this question further, the 成人VR视频 Institute has released its 2026 AI in Professional Services Report, which takes a broad view into the current usage and planning, sentiment towards, and business impact of AI for legal, tax & accounting, corporate functions, and government agencies. Taken from a survey of more than 1,500 respondents across 27 different countries, the report finds a professional services world that has embraced AI鈥檚 use but is continuing to evolve business strategy around its implementation.

For instance, the report shows that to 40% in 2026, compared to 22% in 2025 鈥� and for the first time, a majority of individual professionals reported using publicly-available tools such as ChatGPT. Additionally, a majority of respondents said they feel either excited or hopeful for GenAI鈥檚 prospects in their respective industries, and about two-thirds said they felt GenAI should be applied to their work in some manner.

At the same time, however, many are exploring GenAI tools without much guidance as to how that use will be quantified or measured. Only 18% of respondents said they knew their organization was tracking return-on-investment (ROI) of AI tools in some manner, roughly the same proportion as last year. And even among those tracking AI metrics, most are tracking mainly internally-focused, operational metrics; and only a small proportion analyzed AI鈥檚 impact on their organization鈥檚 larger business goals 鈥� such as client satisfaction, external revenue generation, and new business won.

This slow move to strategic thinking also impacts client-firm relationships. Although more than half of both corporate legal departments and corporate tax departments want their outside firms to use AI on client matters, less than one-third said they were aware whether their firms were doing so or not. From the firm standpoint, meanwhile, confusion reigns: 40% of firm respondents said they have received orders both to use AI on matters and not to use AI on matters from various clients.

Indeed, bout three-quarters of corporate respondents and firm respondents agreed that firms should be taking the lead in starting these conversations around proper AI use. Yet these discussions have not yet happened en masse. 鈥淔irms are reluctant 鈥� they claim it would compromise quality and fidelity,鈥� said one U.S.-based corporate chief legal officer. 鈥淚 think they are threatened by it.鈥�

All the while, technological innovation progresses ever quicker. This year鈥檚 version of the report measures agentic AI use for the first time, finding that already 15% of organizations have adopted some type of agentic AI tool. Perhaps more interesting, however, is that an additional 53% report their organizations are either actively planning for agentic AI tools or are considering whether to use them, indicating perhaps an even more rapid pace of adoption than we鈥檝e already seen with the speedy rise of GenAI.

Overall, the report makes it clear that most professionals do understand that change, driven by AI in the workplace, is undoubtedly here. Even compared with 2025, a higher proportion of professionals said they believe that AI will have a major impact on jobs, billing and revenue, and even the need for legal or tax & accounting professionals as a whole. The percentage of lawyers calling AI a major threat to the unauthorized practice of law rose to 50% in 2026 from 36% in 2025.

Further, this report paints the picture of a professional services world that has embraced AI, begun to see its impact, and realized that it will have broader business and industry implications than previously imagined. As a result, the time for professionals and organizations to begin planning in earnest for an AI future has already arrived.

As a corporate general counsel from Sweden noted: 鈥淲e cannot keep up with the modern-day corporations鈥� demands unless we also develop and adapt our way of working.鈥�

You can download

a full copy of the 成人VR视频 Institute’s 2026 AI in Professional Services Report听here

Key takeaways:

• • • Human oversight & ethical standards are essential 鈥� Successful AI integration in professional services requires strong human oversight and clear ethical guidelines to ensure trust, accuracy, and responsible innovation.

    • Client-centric strategies drive value 鈥� Organizations should align AI adoption with specific business objectives and client needs, focusing on pragmatic data organization and workflow improvements rather than pursuing technology for its own sake.

    • Agentic AI & human-in-the-loop learning are transforming workflows 鈥� The rise of agentic AI systems and human-in-the-loop machine learning is enabling more adaptive, efficient, and innovative solutions, but these technologies must be carefully managed to balance automation with human expertise.

AUSTIN, Texas 鈥� As professional service organizations stand at an unprecedented inflection point, AI has evolved from a promising technology to a force fundamentally reshaping how they deliver value to clients.

The 成人VR视频 Institute鈥檚 (TRI鈥檚) recent听2025 Emerging Technology and Generative AI Forum delved deeper into this situation, bringing together industry leaders, technologists, academics, and visionaries to explore the transformative impact of AI on professional services.

The current state of AI in professional services

The Forum鈥檚 opening panel, Hello World! The State of Emerging Technology and Generative AI, set the stage by emphasizing that the most value in AI lies in data consistency, gradual digital transformation, and human oversight during implementation. A striking statistic that emerged from the discussion showed that in a recent survey 91% of service professionals say they believe AI should be held to higher accuracy standards than human work. This underscores a critical reality 鈥� trust and data protection remain paramount concerns across the board.

Panelists highlighted the importance of aligning AI strategies with specific business objectives to maximize value creation. Indeed, they explained, rather than pursuing AI adoption for its own sake, organizations must focus on prioritizing the critical factors that make implementation possible while harnessing AI’s potential to secure the positive change and innovation that the technology promises.

Exploring agentic AI systems

The second panel, AI on Autopilot: Exploring the Rise of Agentic AI and Its Potential within Professional Services, delved into one of the most exciting frontiers in AI development. Panelists discussed how professional service leaders need to adjust expectations surrounding AI’s capabilities chiefly by breaking down complex problems into manageable chunks and benchmarking AI’s impact with quantifiable data.

In fact, a recurring theme throughout the Forum was the critical importance of keeping humans in the loop. Panelists emphasized that AI agents do their best work with sufficient oversight, and organizational leaders must understand risk factors before deploying AI agents in production environments, especially those involving any client-facing matters.

The conversation also touched upon alternative fee arrangements, examining AI’s dual role as both assistants and autonomous agents and how professional service leaders need to harmonize technology with elevated workflow management.

Human-in-the-loop learning

Prof. Peter Stone, Truchard Foundation Chair in Computer Science at the University of Texas鈥揂ustin and Chief Scientist at Sony AI, delivered a compelling keynote at the Forum, titled Human-in-the-Loop: Machine Learning for Robot Navigation and Manipulation. Prof. Stone鈥檚 research explores how to create autonomous intelligent agents that adapt, interact, and embody complex, human-like behaviors. He also has demonstrated these capabilities through engaging videos of robots playing soccer and mastering Tetris.

Prof. Stone’s work has significant implications for various applications, including healthcare and manufacturing 鈥� fields in which intelligent robotic systems can transform operational efficiency and innovation. His emphasis on the importance of training with the human-in-the-loop has clearly shown that we remain in the nascent stages of agentic machine learning, despite such vast development over the past decade.

Client-centric technology strategy

The panel, Wired for Success: Creating a Forward Focused, Client Centric Technology Strategy, explored how professional services firms can develop technology strategies that both enhance client engagement and drive value creation. Panelists emphasized the need to ensure that AI’s work is thoroughly checked, treating the innovative technology like any other employee.

Panelists also acknowledged the challenge of organizing data prior to implementing the technology but determined that this particular technology doesn’t need to be perfect to accelerate workflows. Rather, organizational leaders only need to ensure their metrics reflect a realistic qualification of value. This pragmatic approach recognizes that organizing data to make it AI-compatible 鈥� particularly in the legal technology industry 鈥� are essential steps in the journey toward effective AI adoption.

Ethical considerations in AI development

The final panel, A Unified Field: Ethical Considerations amid AI Development and Deployment, tackled one of the most critical aspects of AI adoption: The need for a strong ethical foundation for AI use. Panelists underscored the need for organizations to establish clear guidelines and harness diverse perspectives for ethical AI practices.

As AI continues to evolve in highly personal applications like facial recognition technology, ethical decisions become less straightforward. The panel delved into questions about the next generation’s interaction with AI, including whether it is ethical to harness AI to teach children through new educational approaches

Panelists also emphasized that ethical AI is a collective responsibility that falls on all users’ shoulders, setting the stage for a future in which AI development is both responsible and visionary.

The AI-enabled path forward

TRI鈥檚 2025 Emerging Technology and Generative AI Forum firmly established that successful AI implementation requires more than technological sophistication 鈥� it demands a holistic approach that encompasses data strategy, talent development, client engagement, and unwavering commitment to ethical standards. The future of professional services will be defined not by whether firms adopt AI, but by how thoughtfully and strategically they integrate these transformative technologies into their core operations.

The insights shared throughout the Forum further underscore a fundamental truth: As professional services firms navigate this transformation, the frameworks and strategies discussed provide a roadmap for sustainable innovation that enhances rather than replaces human expertise. The ethical considerations discussed are not merely compliance requirements but rather fundamental principles that will determine whether AI serves as a force for positive transformation or something else entirely.

Forum attendees took away how important it is to harness AI’s potential while maintaining the trust, transparency, and human judgment that clients expect from their most critical business partnerships. Indeed, the path ahead requires continued collaboration, shared learning, and collective commitment to responsible innovation that truly serves humanity’s best interests.

To dive deeper into these insights and understand the strategic implications for your organization, we invite you to download here

Key takeaways:

• • • Strategic alignment drives ROI听鈥� Organizations that implement GenAI with a clear, formal strategy aligned to their broader business goals, such as revenue growth or client experience, are able to find stronger ROI measurements than those adopting AI informally.

    • Measuring GenAI requires more than basic metrics听鈥� While many firms currently track simple, internally-focused metrics like cost savings and user adoption, true value from GenAI comes from mapping its use to strategic outcomes such as revenue generation, operational efficiency, and client satisfaction.

    • AI strategy aids measurement capabilities听鈥� Despite increasing adoption of GenAI tools, less than one-quarter of professional services organizations have a visible AI strategy, according to our research, which decreases their ability to properly measure GenAI鈥檚 organizational impact.

At this point of the lifecycle of generative AI (GenAI), most individuals across the professional services world have a conception of what GenAI is and what it can do. Indeed, 96% of respondents had at least a basic understanding of AI principles, according to the 2025 Future of Professionals report, which surveyed corporate, legal, tax & accounting, and government professionals.

With that in mind, most organizations are prepared to take the next step: Making GenAI an integral part of their operations and measuring its direct impact on the organization. It鈥檚 a natural progression, as individual use of publicly available GenAI technologies such as ChatGPT or Claude turns into institutional investment in business-centric tools such as Microsoft Copilot or industry-specific GenAI tools.

Of course, organizational leaders whose teams are using these tools want to see how much these tools really help, and attempt to quantify GenAI鈥檚 return-on-investment (ROI).

However, those that have undertaken the ROI exercise have found that arriving at an answer may be easier said than done for a number of reasons. Many professionals are just beginning with the tools and have not yet fully integrating them into their workflow, which makes the true impact of GenAI harder to measure. Determining the time saved by AI tools requires an intricate knowledge of how these professionals work on a daily basis; and most professional services firms are not yet talking to their outside clients about GenAI, making calculations around business won or client satisfaction next to impossible to compute.

That said, however, there already are some simple ways to start to map GenAI usage to a set of ROI metrics. It starts with knowing what your organization wants to achieve by using GenAI.

Mapping use cases to goals

GenAI, as is the case with all business-oriented technologies, should not be treated as a goal in itself. When determining metrics around AI use, start with the organization鈥檚 primary set of strategic initiatives then extrapolate from there.

For instance, increasing revenue is a way 81% of C-Suite respondents say they measure success, according to the 成人VR视频 Institute鈥檚 recent 2025 C-Suite Survey. GenAI, therefore, should be rolled out with this in mind, with potential use cases for the technology aimed squarely at increasing revenue such as by delivering stronger market analysis and predictive analytics for client issues. If instituted with the larger revenue goal in mind, the ultimate metric for the technology鈥檚 success then is not simply usage, but how well the technology actually contributes to revenue gains.

The chart below from the Future of Professionals Report provides some examples from a law firm perspective of how other organizational goals can lead to ROI metrics, including bolstering the client experience, creating operational efficiencies, and attracting and engaging talent. Other industries such as tax, audit & accounting; government agencies; and courts have their own sets of goals that can be adapted in the same fashion.

GenAI is a powerful tool particularly because of its versatility. While many past technologies aimed at professional services were focused squarely on one or two use cases, GenAI, as demonstrated above, can be adapted to serve a number of different uses and goals. As a result, implementing these use cases 鈥� and crucially, measuring their success 鈥� requires more strategic planning than past technologies.

The importance of strategy

Even with the rate of GenAI adoption continuing to climb, formal AI strategies are not climbing at the same rate. The Future of Professionals report found that just 22% of respondents say their organizations have a visible AI strategy, while 43% say their organizations are moving ahead with adoption despite having no formal strategy in place. About one-third of respondents, meanwhile, say their organizations have no significant plans for widespread adoption.

Unsurprisingly given the above, this lack of strategy has a tangible impact on measurable ROI, particularly as it relates to underlying revenue. The report notes that organizations with a strategic AI plan are almost twice (1.9-times) as likely to already be experiencing revenue growth as a result of their AI investment than those organizations that are adopting AI informally. Similarly, 81% of respondents at organizations with an AI strategy report seeing some sort of positive ROI from AI; only 64% of respondents at organizations adopting AI informally say the same.

Measuring proper ROI from GenAI implementation is not an impossible undertaking, but at the same time, it is not an easy proposition. The 成人VR视频 Institute鈥檚 2025 Generative AI in Professional Services Report from earlier this year found that even of those organizations measuring GenAI鈥檚 impact, the most common metrics were simple and often internally-focused, such as internal cost savings, user adoption, and user satisfaction. Metrics focused on client satisfaction or external revenue generation, meanwhile, were tracked by less than 40% of organizations, according to survey respondents.

That is the wrong way to approach AI measurement, particularly in a professional services landscape that expects GenAI (and soon, agentic AI) to become a central part of the profession鈥檚 workflow within the next five years. If GenAI is becoming so crucial to the organization, then its measurement should be based not on simple technology metrics, but on larger strategic metrics for the organization.

And that means, for organizations without an AI strategy that links to the larger organization鈥檚 overall strategy, the time to begin that planning in earnest for the AI-driven future has arrived.

You can download your copy of the听2025 Future of Professionals Report here

Key takeaways:

• • • Embrace value, risk, and execution 鈥� for good and bad 鈥斕齈rofessional services firms must weigh the value of AI applications against potential risks, embracing both successes and failures as learning opportunities to improve responsible adoption.

    • Ethical oversight is everyone鈥檚 responsibility 鈥斕鼸nsuring responsible AI use in professional services requires active participation from all members of an organization, not just legal or IT teams.

    • Human creativity and feedback remain essential 鈥斕齏hile AI can generate ideas and accelerate processes, human judgment, creativity, and continuous feedback provide the proper pathways for ethical decision-making and successful integration.

AUSTIN, Texas 鈥� With the professional services world now squarely into the AI era, it鈥檚 clear that the speed of business is quicker than ever. Clients expect results in hours or even minutes rather than days, while generating documents can happen at the click of a button. Ask a research question, and a machine can intuit what you鈥檙e looking for with striking accuracy.

Alongside these business changes, however, it鈥檚 clear that the ethics of technology usage within professional services is shifting just as quickly. 鈥淓very time you come and do a talk with a group of people, within four weeks if not sooner, it鈥檚 changed,鈥� says Betsy Greytok, Associate General Counsel in Responsible Technology at IBM. 鈥淪o, it really does require you to keep on your toes.鈥�

Ensuring that AI is used responsibly is paramount within professional services than in other professions, given the ethical and regulatory constraints placed on legal, tax, audit & accounting, financial services and risk, and more. During a recent session, A Unified Field: Ethical Considerations amid AI Development and Deployment, at the 成人VR视频 Institute鈥檚 2025 Emerging Technology and Generative AI Forum, panelists describe an ethical world that should be tackled as a challenge, rather than shied away from as an unsolvable risk.

Or, as Paige L. Fults, Head of School at the AI-centric Alpha School & 2-Hour Learning program, put it: 鈥淣ot being afraid of replacement, but leaning into repurpose.鈥�

Embracing success 鈥� and failure

John Dubois,听the Americas AI Strategy Leader at Big 4 consultancy Ernst & Young, says he regularly gets questions from customers about AI and how they should use it, given that there are new AI applications arising seemingly every day. 鈥淭he way we describe it is a balance,鈥� Dubois explains. 鈥淟et鈥檚 start with value. If we know there鈥檚 value in something, then we can figure out the risk behind it, then we can figure out how we can execute.鈥�

Just as importantly, however, this focus on value, risk, and execution can also aid professional services firms when an AI plan fails. For example, Dubois cites an MIT report from August 2025 that showed , often because of flawed integration. Embracing the value, risk, and execution strategy from the beginning not only allows for better chances of success, but even in the event of failure, 鈥渨e actually have a better shot at mitigating, when it does fall down.鈥�

This sort of planning is not limited to just one group, Dubois says, noting that ethical oversight is seen as a key responsibility of everyone in the organization. He explains that E&Y has an internal implementation of OpenAI that has 150,000 distinct users each month. Because of an internal process called SCORE that removes customer data at the source, E&Y鈥檚 instance of OpenAI is largely clear of customer data 鈥� but it鈥檚 still not perfect.

E&Y has set a culture so that if someone sees proprietary data when using GenAI to develop a proposal or create a PowerPoint, they not only delete the data before use, but work to scrub it from the system entirely. 鈥淚t is all of our job to ensure that whatever you鈥檙e putting into that system or extracting out of that system, you鈥檙e cleansing,鈥� Dubois says. 鈥淚t鈥檚 not the job of the general counsel, or the risk team, or the IT team, it鈥檚 all of our job.鈥�

When it comes to keeping up with AI ethics in a rapidly advancing space, professionals can rely on the same methods they have been employing for years to solve ethical quandaries: human creativity.

IBM鈥檚 Greytok agreed, noting that she鈥檚 part of an internal review board that examines major AI-related projects for ethical issues. There is a board review at the beginning of the development process to determine how risky a use case is, and then the system will give a response, considerations, and steps. If there is an issue, the board is empowered to stop development, even on a major project.

She drew an analogy to writing a paper in high school, in which there is a marked difference between simply turning in the paper, proofreading your own work, and asking a friend for peer review feedback. 鈥淭hat鈥檚 what you want, is that disagreement, because that鈥檚 critical thinking.鈥�

She adds: 鈥淭he researchers sometimes get so excited about what they鈥檝e discovered that they forget to look at the other side of what can happen. You should want that. You shouldn鈥檛 be punished for saying, Is this the right thing or not?鈥�

The importance of feedback

Fults says that at the Alpha School, AI is not only baked into the curriculum, it . Students spend just two hours a day on academics, led by AI tools that are supplemented by off-line learning on a variety of subjects by in-person instructors that fill in the gaps that AI is not able to provide.

It鈥檚 a revolutionary concept but not a static one. Fults notes that 鈥渢he two-hour learning model has already changed so much since I鈥檝e been part of the school,鈥� and the instructors have a Slack channel on ways to find improvement that receives hundreds of messages a day.

It鈥檚 through this marrying of human intuition and the possibilities of the technology that Fults says she believes the school has found success and used AI ethically within education. 鈥淓ven though we have this tool, the human levers, the motivational levers that are happening day to day, actually make it work,鈥� she says, insisting that she 鈥渃an鈥檛 just hand [the technology] to any school鈥� without the corresponding processes in place.

Dubois and Greytok also call feedback a crucial part of the process in order to overcome AI barriers. Dubois tells the story of a large retailer that bought satellite images to determine footfall within a store. Shoppers, however, felt that was a privacy risk, and the idea was almost scrapped. Then, however, the legal and IT teams worked together to come up with an idea: Can you track clothing, but not faces, to get the same information of where within the store shoppers were going?

鈥淚t鈥檚 a creative workaround to get us to the same thing,鈥� Dubois explains. 鈥淲hen you have a constraint, what鈥檚 a clever way to work around this so we鈥檙e not taking a brand risk or a compliance risk?鈥�

Indeed, when it comes to keeping up with AI ethics in a rapidly advancing space, professionals can rely on the same methods they have been employing for years to solve ethical quandaries: human creativity. AI can provide information and context more rapidly than ever before, but ultimately, professionals themselves will be the ones relied upon to make sure AI is used ethically and responsibly.

鈥淎I is an idea generator,鈥� Greytok says. 鈥淭he solution comes from the human.鈥�

You can find out more about how emerging technologies are impacting professional services here

Key findings:

• • There鈥檚 a gap between AI awareness and understanding 鈥� The recent 2025 Future of Professionals Report shows that while 96% of professionals have at least a basic awareness of AI, 71% lack a strong understanding of its practical applications. This gap limits professional services organizations from truly maximizing their investment in AI tools.

  • AI strategy drives both professional development and ROI听鈥� Professionals with good or expert AI knowledge were found to be 2.8-times as likely to see organizational benefits from AI when compared to those with lesser knowledge. Similarly, companies and firms with a visible, top-down AI strategy are 3.5-times as likely to see positive returns on investment from AI. Both show a clear benefit to aligning skills training and overall organization AI strategy.

  • Identifying and addressing AI-related skills gaps is essential 鈥� Nearly half of professionals said they see skills gaps within their teams, including both technical and soft skills needed for successful AI adoption. Leaders who identify these gaps and tailor AI training to specific team needs will maximize the benefits of AI in the workplace.

In the nearly three years since ChatGPT introduced generative AI (GenAI) to a wide public audience, AI applications have increasingly been making their way into business tools and workflows. Whether AI, GenAI, or (increasingly) agentic AI, professionals in the legal, tax & accounting, and government industries have been introduced to new AI concepts at a dizzying speed.

As many professionals try to keep up, they are understandably having trouble staying ahead of the pace of change. According to results from the recent 成人VR视频 2025 Future of Professionals Report, which examines the trends impacting professionals careers, most professionals at this point know what AI can do. Where they鈥檙e struggling, however, is making the next step in determining how those use cases apply to them. This leap is even more pronounced with more senior members of many organizations, the report shows.

Although many professionals now have access to these next-generation tools, it鈥檚 clear that despite their best efforts, some don鈥檛 quite know how to apply AI, GenAI, and other related technologies to the best of their ability and for maximum advantage. For senior leaders of organizations, this means a change in approach is needed 鈥� and that may mean crafting an overarching AI strategy that allows professionals to achieve real goals that will also help the organization at large.

A gap between awareness and understanding

The idea that professional services organizations are behind the times with regards to technology may be an antiquated concept. Law firms of all sizes, for instance, have continued to invest in technology at a rate above inflation for the past decade, according to the 成人VR视频 Institute鈥檚 Law Firm Financial Index. Studies in tax & accounting and government have yielded similar results. Further, the interest in GenAI has amplified, with many large organizations adopting GenAI technologies, and even beginning to build their own proprietary systems.

With this in mind, it鈥檚 not surprising that the Future of Professionals Report found that 96% of surveyed professionals said they have some basic awareness of AI capabilities. AI has been baked into the systems that underpin daily work product and back-office functions at a rapid pace.

However, when asked whether they have an understanding of AI鈥檚 practical applications, rather than simply awareness, many professionals begin to falter. In fact, 71% said they feel they do not have a good understanding of the practical applications of AI to their own careers. This percentage is even higher for the Baby Boomers, who due to seniority are more likely to hold positions of leadership.

There are a number of reasons why this gap can have occurred, according to the research. For one, less than half (39%) of all professionals say they have personal goals linked to AI adoption, creating less of an impetus to actually setting aside precious time to discover the practical applications of these tools. Some professionals also reported that they do not feel like they have input into AI policy, or do not feel encouraged to explore new ways of working, particularly at more junior levels.

The business implications of this are clear. The research found that knowledge of AI鈥檚 applications has a direct correlation with receiving benefits from AI鈥檚 use in the organization, as professionals with good or expert AI knowledge were found to be 2.8-times as likely to see organizational benefits from AI when compared to those with lesser knowledge.

The evolution of the modern professional

Given the rapid rate of AI adoption, it鈥檚 no surprise that corporations and firms alike are increasingly looking to develop more business strategy around AI usage. And indeed, the Future of Professionals research indicates that organizations with a visible AI strategy are 3.5-times as likely to be experiencing at least one form of positive return on investment from overall AI usage.

So, how does that top-down strategy filter down to legal, tax & accounting, and government professionals themselves? According to the research, the discrepancy between AI awareness and AI understanding is not a matter of desire. Professionals want to be upskilled in this area. In fact, more than three-quarters of professionals said they are voluntarily reading reports and articles about AI in their industry, and more than two-thirds have said they鈥檝e voluntarily experimented with AI tools or held informal learning sessions with their colleagues.

Yet, the difference between awareness and understanding remains, even with these increased opportunities for learning. According to the research, however, it鈥檚 not one way of learning alone that lends itself best to closing this gap. Instead, the biggest predictor of AI proficiency is engaging in a wide variety of learning methods, both on an organizational and personal level. Put another way, it鈥檚 a plan for comprehensive training and education, rather than simply a single training session or a module.

This clearly indicates that organization leaders need to take an active role in developing a more comprehensive strategy to convert awareness into understanding 鈥� and map AI understanding to what skills their teams need to grow.

Almost half of professionals reported skills gaps within their teams that are need to be addressed before the team can become a fully actualized contributor to the organization. In many cases, these skills gaps may be technology or data skills and could include the ability to use technologies such as GenAI. In other cases, however, there may be gaps in more soft skills, areas that touch technology but are not inherently technical 鈥� such as organizational and efficiency skills, interpersonal effectiveness, and higher-order thinking.

Closing the gap between AI awareness and AI understanding will not be the same for every person and every team. The most effective leaders will be the ones who take the time to identify where those gaps exist and determine the specific use cases in which AI can be leveraged to aid those deficiencies. As the 2025 Future of Professionals Report shows, however, taking this time can yield tangible results 鈥� both in getting the most out of these new technologies and helping professionals reach their true potential in an AI-enabled future.

You can download a copy of听成人VR视频 Future of Professionals 2025 here

For professionals in legal, tax, risk & fraud, and government industries, the shift has been both quick and dramatic. Already more than half of all legal, tax, risk & fraud and government professionals have used GenAI in some fashion, with a wide range of use cases already arising, according to the newly published 成人VR视频 Institute鈥檚 2025 Generative AI in Professional Services Report. In fact, the report shows that professionals from across the United States, the United Kingdom, Canada, Latin America, Australia, and New Zealand are not only expecting GenAI to become a more common part of their work, but they鈥檙e feeling more positive about the impact GenAI will have on their profession.

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However, even with usage skyrocketing, many of the firms, departments, and agencies in which these professionals work still have a way to go to fully extract value from GenAI. The report shows that few organizations are capturing return-on-investment (ROI) metrics, regularly training staff on GenAI updates, or integrating GenAI use into their policies. In addition, few professionals say their firms and their clients are having conversations around GenAI use. And even more worrisome, questions about GenAI鈥檚 impact on billing rates and costs remain unanswered.

This year鈥檚 report reflects a crossroads: GenAI itself is seeing adoption on a wide scale, but professional services industries largely still have yet to discern what it means for the future of their businesses.

Key findings in the report

Some key findings in this year鈥檚 Generative AI in Professional Services Report include:

• • • Steady usage increases 鈥� A large portion (41%) of respondents said they personally use publicly-available tools such as ChatGPT, and 17% said they personally use industry-specific GenAI tools. On an organization-wide level, the percentage of respondents who said their organizations were actively using GenAI nearly doubled over the past year, to 22% in 2025, compared to 12% in 2024.
    • Soon to be central to workflow 鈥� Just 13% said GenAI is central to their organizations, workflow currently, but an additional 29% said they believe it will be central within the next year. Further, 95% of all respondents believe it will be central to their organization鈥檚 workflow within the next five years.

• • • Maintaining positivity 鈥� More than half (55%) of all respondents categorize their sentiment towards GenAI in their profession as excited or hopeful. Meanwhile, the proportion who said they were hesitant, concerned or fearful fell 12 percentage points over the past year.
    • Business questions remain 鈥� Only 20% said they knew their organizations were measuring ROI of GenAI, and many firm respondents remain unsure about GenAI鈥檚 impact on rates or client costs. And while 57% of corporate clients want their outside firms to be using GenAI, 71% of law firms鈥� clients and 59% of tax firms鈥� clients said they did not know whether their firms were using it or not.
    • Policies & training still needed 鈥� More than half of respondents (52%) said they believed their organizations had no policies around GenAI at work, whether a standalone policy or as part of a larger technology policy. Nearly two-thirds (64%), meanwhile, said they had received no GenAI training at work.

At this point, it is evident that GenAI is here to stay. Professionals across multiple industries are adopting it for their own personal use in droves, whether leveraging free tools or, increasingly, business or industry-specific technologies. Organization-wide adoption is beginning to occur as well, albeit slowly.

The question, then, becomes what will professional services industries do with GenAI once it鈥檚 adopted. As the report reveals, many may not yet know 鈥� but they do know they need to begin having those conversations quickly.

鈥淭he next 24 months will be extremely telling on the impact of GenAI on the legal industry and professional work more broadly,鈥� said one Australian law firm attorney. 鈥淎s products move out of development [and in]to production, we will be able to see the actual effects of this technology across various sectors.鈥�

You can download a full copy of the 2025 Generative AI in Professional Services Report here

At the same time, however, as GenAI begins to move rapidly from hypothetical to reality, its introduction creates a host of related issues 鈥� perhaps none greater than the energy that the operation of GenAI consumes. AI data centers鈥� annual power consumption is expected to reach 90 terawatt-hours by 2026, a roughly a 10-fold increase from 2022 levels and representing one-seventh of all data center energy consumption, according to a from late-2024. Further, that figure will only increase in the coming years as GenAI becomes more prevalent within professional settings.

As a result, many companies may find it more difficult to meet their energy transition goals to lower overall emissions as they increasingly embrace AI. In fact, the recent , produced by Reuters Events in cooperation with Siemens, found that nearly half (46%) of all respondents said they believe their organization is at risk of missing interim energy transition targets.

Clearly, AI does not occur in a vacuum. As GenAI implementation continues apace, the next necessary step is to incorporate its use into energy targets 鈥� a natural fit for the type of advice typically given by professional services organizations. Indeed, legal, tax, and risk & fraud professionals can help design their clients鈥� architect for a future in which AI usage can even be a positive step towards their energy goals.

鈥淪ustainability is interconnected with all other business objectives, simultaneously influencing and being influenced by them,鈥� said Pina Schlombs, Sustainability Lead for DACH (the region comprising Germany, Austria, and Switzerland) for Siemens Digital Industries Software, within the report. 鈥淭hese relationships can either compete with or reinforce progress, meaning businesses must develop a thorough understanding of the cause-and-effect chains. This is a complex feat, but mastering it allows organizations to leverage the right strategies and technology stack at the right time and maturity, to scale progress fast.鈥�

Simplifying the complex

One of the primary goals of AI systems is to simplify complex actions, breaking them down into more repeatable, automatable components. Consider the research component of any sort of legal case or tax problem 鈥� by leveraging data to anticipate questions and more quickly identify the type of information needed, the time required for the research process can be drastically reduced.

Industrial AI can take these concepts and apply them on a large scale for the goal of reducing emissions. The report gives an example of a digital twin for an entire factory, which allows adjustments to be modeled and tested before implementation. Through AI-powered trial and error, companies can find ways to reduce industrial complexity, process and analyze data quickly, and streamline tasks to remove unnecessary use of energy.

James Cole, Chief Innovation Officer at the Cambridge Institute for Sustainability Leadership (CISL), points to the start-up Monumo, which has developed AI to run through 10 million motor design simulations in one day, 200-times faster than the industry standard. Even traditional industries such as construction have found uses: Titan Cement, for example, reduced its energy consumption by 5% to 10% through AI modeling of its manufacturing operations.

鈥淲e鈥檝e never had such powerful tools to solve the challenges we face in sustainability,鈥� said Cole within the report. 鈥淎rtificial intelligence systems have the potential to help us understand the world in all its complexity and optimize industrial processes not only for strong business outcomes, but also for holistic social and environmental outcomes.鈥�

The result is that as these systems progress, industrial AI is set to dramatically transform industry energy transition in the near future. Only 14% of survey respondents said they believe industrial AI has a high impact on accelerating industry transitions today; but at the same time, 50% said they believe industrial AI will do so within the next three years. This quick adoption will require buy-in and coordination from all levels of the organization.

Overcoming adoption challenges

So, what does all this mean for professional services? As noted above, no AI occurs in a vacuum, and similarly, no business runs without legal, tax, or risk & fraud input. Thus, as professional services organizations are increasingly looked upon as strategic partners and business generators rather than simply cost centers, there is an opportunity to counsel clients on the energy opportunities afforded by AI.

As noted previously, AI adoption can be sorted into three main categories: financial, partnerships, and internal capabilities and skills. By focusing on overcoming all three types of barriers, professional leaders can influence clients to not only adopt AI, but to do so in a way that encourages energy-neutral use.

鈥淎I is not optional, it鈥檚 out of the bag, it鈥檚 going to happen, and it has the potential to transform business models,鈥� CISL鈥檚 Cole said. 鈥淪o, companies that are assuming everything is broadly going to stay the same except for their investment in AI risk missing the point.鈥�

Legal, tax, and risk and professionals 鈥� both within corporate functions and at outside firms 鈥� should make sure they are a part of the AI ecosystem and have their thoughts heard.

First, by encouraging greater measurement and data collection, professionals can help their clients determine exactly the financial impact and risk they could face associated with AI adoption. Just 20% of professional services organizations actively measure return-on-investment from GenAI tools, according to our internal research, which also showed that data collection around these tools is poor across the board 鈥� and that includes their impact on ESG.

Second, legal, tax, and risk and professionals 鈥� both within corporate functions and at outside firms 鈥� should make sure they are a part of the AI ecosystem and have their thoughts heard, keeping in mind ESG as an element of the overall impact. If a company is using industrial AI to transform factory operations, for instance, those changes will require a financial and risk assessment. Legal leaders should be integrating ESG into those assessments, aiming for energy-neutral processes wherever possible.

Finally, to provide proper advice, professionals will need to learn how AI not only impacts their own work, but how it impacts the business at large. For example, our research also shows that less than one-third of professionals have received training specifically focused on GenAI. However, to be able to be proper partners on AI projects, professionals will need to at least learn the basics of how AI can be used to streamline projects, rather than simply consuming energy.

In the near future, these actions will become central to energy goals rather than simply helpful additions. According to the Reuters Events/Siemens report, 70% of respondents agreed that future innovation in sustainability will be driven by industrial AI applications and solutions. Thus, planning across all parts of an organization must begin now to better design AI usage in a way that aligns with achieving future sustainability goals.

鈥淭he meta challenge of businesses is how to balance productivity and commercial outcomes with the imperatives of social and environmental outcomes,鈥� added Cole. 鈥淰ia big data and AI, there鈥檚 the opportunity to not just optimize operations but drive symbiosis across entire industries where there鈥檚 historically been a disconnect, to align increasingly digital systems and make sense of a broader 鈥榮ystem of systems鈥�.鈥�

You can find more about how organizations are handling the challenge of sustainability here

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