Key highlights:

• • • Technology satisfaction is in freefall and needs human-side investments — Satisfaction with tax technology dropped sharply to just 34%, from 56%, in a single year, even as many tax departments continued investing in tools.

    • Training cutbacks are accelerating, as the AI era deepens — Only 50% of tax departments provided technology training in 2025, down from 59% the prior year.

    • Hiring changes reveal a false choice between tax expertise and tech fluency — After years of prioritizing tech and IT hires (which were 57% of new roles in 2024), tax departments sharply reversed course, with 62% of new hires in 2025 emphasizing tax expertise over technology skills.

After years of investing in tax technology, corporate tax departments have yet to see peak efficiency because of underdevelopment in workforce training and a growing mismatch between what advanced AI tools can do and what employees can handle. In fact, the , from the Thomson Reuters Institute and Tax Executives Institute, reveals that satisfaction with tax technology has plummeted to just 34%, from 56%, in a single year.

That leaves many tax departments struggle with a widening frustration gap between what they want to achieve and what their current tools will allow. The key to closing this chasm is for heads of tax to reinvest in the human-side of their technology capabilities.

Tech competency remains a challenge

Only 9% of tax professionals rate their colleagues as very competent with technology, according to the report. The majority (60%) said they consider their teams merely somewhat competent, while nearly one-third admit their departments lack technological competence altogether.

What makes this especially alarming is that larger companies with more resources are almost three times more likely to report competency gaps, with 39% of professionals saying this, compared to just 15% at smaller firms. Indeed, these larger organizations are the ones that have invested most heavily in sophisticated tech stacks and should theoretically have the most capable users.

Perhaps a reason for this competence gap is the failure to invest in consistent technology training and knowledge-sharing among peers. Despite being one of the most cost-effective performance levers available, only 50% of corporate tax professionals surveyed said their departments provided technology training in 2025. This is down from 59% the previous year.

This training deficit has consequences because most corporate tax departments remain stuck in the reactive or chaotic phase of technological maturity. Meanwhile, AI timelines are compressing rapidly. In fact, 39% of tax professionals said they now expect AI to be central to their workflow within 1 to 2 years, up from the 31% who thought it would take that long just last year.

Pendulum swing in hiring

The 2026 Corporate Tax Technology Report also reveals a dramatic reversal in hiring priorities that deserves careful attention. In 2024, 57% of new tax department roles were dedicated to tech/IT expertise, with only 24% prioritizing tax knowledge. By 2025, the script had completely flipped, with 62% of new hires now emphasizing tax expertise.

At smaller companies (those with revenue of less than $1 billion), the swing is even more extreme. In fact, 100% of new hires are now those with tax expertise rather than technology specialists.

This pendulum swing likely reflects a correction after years of heavy tech/IT hiring combined with greater technological maturity that subsequently requires less technology expertise. At the same time, however, the solution is not one or the other; rather, hiring for both makes the most sense. In fact, the data supports this as hybrid tax/tech roles are on the rise, according to the report.

4 actions corporate tax leaders should take now

While the data makes the problem of this frustration gap clear, the more pressing issue is what tax leaders can do about it right now. Four concrete actions stand out:

1. Make training non-negotiable — If corporate tax leaders are investing in technology but not in developing their people’s ability to use it effectively, they are wasting money. Make formal training — along with mentoring and peer knowledge-sharing — a performance requirement.

2. Hire for the future — The pendulum swing back to tax expertise is understandable, but it’s essential that heads of corporate tax departments do not overcorrect. Prioritize candidates who demonstrate both deep tax knowledge and technological fluency or invest in upskilling current staff with explicit development paths to build in the missing capability.

3. Track what matters — Two-thirds of tax departments now measure time savings and efficiency gains, while 55% track accuracy improvements. In addition, it is important to track where your corporate tax department staff are struggling with tools and where additional training or process optimization could unlock value.

4. Prepare for the AI acceleration — With 39% of corporate tax professionals expecting AI to be central to their work within the next 1 to 2 years and another 15% expecting it within a year, corporate tax executives must start experimenting with AI for technical research, compliance automation, and document analysis to build the team’s comfort and competency through hands-on experience.

The bottom line

The frustration gap among corporate tax professionals highlights the mismatch between advanced technological capability and the human capacity to leverage it. As one survey respondent described: “Technology is extremely important to reduce manual processes and help reduce errors. I don’t see a path for any tax department to not lean into technology.”

However, leaning into technology without investing equally in your people is a recipe for disillusionment. The 56% dissatisfaction rate with current tech stacks underscores the frustration in the human-technology relationship and the perception that the technology tools are not solving users’ problems very well.

Those corporate tax departments that will thrive in the AI era will be the ones that invested in building technological competence, hired for hybrid capabilities, and created cultures of continuous learning. The technology maturity curve and the talent maturity curve must ascend together.

You can download a full copy of from the Thomson Reuters Institute and Tax Executives Institute here

Key takeaways:

• • • Prompt engineering pays off — Tax professionals who master clear, contextualized AI instructions see immediate gains in output quality and speed.

    • AI doesn’t replace professional responsibility — Every output that carries your name requires your verification and your judgment.

    • Link learning to a real problem — The most effective way to build needed skills is to focus on your current workflow, not to chase every new tool as it emerges.

For tax professionals, technical excellence used to be enough. Know the code, understand the cases, apply the rules correctly — that was the job, and it was sufficient. It isn’t anymore. Not because the technical knowledge matters less, but because the professionals competing for the same work increasingly bring other talents to the table, such as the ability to do in an hour what used to take a day; to provide insights from data that would have taken a week to compile manually; and to deliver polished, well-reasoned analysis at a pace that wasn’t possible five years ago.

This rarified capability doesn’t come from intelligence or experience alone; rather, it comes from skills — specific, learnable, practical skills.

The data bears this out. Improving efficiency through technology has been the top strategic priority for firms for three consecutive years, with 44% of firm leaders citing it as their primary focus, according to the Thomson Reuters Institute’s . Indeed, 47% of tax professionals surveyed said investing in AI should now be a top priority — and yet, 18% of firms still use no automation at all.

This gap between intention and capability is real, and it sits squarely with the individual tax professional.

The skills most needed by today’s tax professionals

To help close this gap and improve tax professionals’ overall work value, there are several specific skills that demand attention, including:

Prompt engineering: The skill nobody takes seriously until they see what it does

The name doesn’t help — but set that aside, because the underlying skill is straightforward: giving your AI tools clear, precise, well-contextualized instructions that produce outputs that are worth using.

Most people start badly when approaching a blank AI screen. They type something vague, get something generic, and conclude the tool isn’t useful. That conclusion is wrong, because it was the instructions given, the prompt, that was the problem. Specify the entity type, jurisdiction, tax year, audience, and format. Then tell the tool what you need and why. The difference in output quality is not marginal.

Of course, it’s important to remember that AI will tell you things that are wrong with complete confidence. It will cite an amended provision, apply a rule from the wrong jurisdiction, or construct a plausible analysis on a flawed premise — all without flagging any of it. The professional responsibility to catch it remains entirely upon the user. That’s not a flaw in the tool; it’s a reminder that expertise isn’t being replaced here — it’s being put to better use.

Data literacy: The capability gap most tax professionals don’t know they have

Tax work is data work. Today, what has changed is the expectations around the volume and complexity that professionals are now required to handle, interpret, and present, often with fewer resources than a decade ago.

Advanced spreadsheet proficiency is the starting point, and the emphasis on advanced is deliberate. The features that most professionals have never explored are precisely the ones that separate those who spend three hours processing data from those who spend 20 minutes. The ability to build visual dashboards that communicate tax data clearly — effective tax rates, provision variances, deferred movements, and more — is increasingly an expectation in corporate environments rather than a differentiator. For those professionals who handle large datasets or complex scenario modeling, even a foundational understanding of represents a significant capability uplift.

The Tax Professionals Report found that 57% of firm leaders cited getting better use out of existing technology as their top investment priority — more than those planning to buy new systems. The problem, in other words, isn’t the tools; it’s having the skills and the understanding to use them.

Workflow automation: Reclaiming time from work that shouldn’t exist

Look at any tax workflow closely and you’ll find steps that are repetitive, rule-based, and time-consuming — not because they require a tax professional’s skilled judgment, but because nobody has stopped to ask whether these routine tasks could be done differently.

Again, the harder part of improving your skill set as a tax professional isn’t learning the tools; rather, it’s developing the habit of process analysis, a way of thinking that will allow you (among other things) to distinguish between steps that require genuine expertise and steps that are simply consuming time.

AI judgment: Knowing what to trust and what to verify

This is the skill that determines whether AI makes you more effective or creates problems you didn’t anticipate. This means validating outputs against primary sources before they reach a client. It means recognizing that AI reflects training data that may be outdated or jurisdiction-specific in ways that aren’t readily apparent in the output. And it means knowing when a task is too nuanced or too high stakes for AI to handle reliably.

Professional responsibility does not transfer to the tool itself. If an AI-generated analysis carries your name, it is your analysis.

Communicating and staying current

As routine tax compliance work becomes more automated, the premium on communication rises sharply. The Tax Professionals Report found that three-quarters of clients now strongly desire advisory services beyond tax preparation from their outside tax professional — yet most tax firms still derive their greatest profits from simple tax return preparation.

Those professionals who can close that gap are those who can translate technical work into clear, confident guidance that their clients can act on.

Going forward, the tools will keep changing. Identify the problem in your current workflow that costs the most time, find the skill that addresses it, and build from there. The professionals who will define the next decade will combine this deep technical knowledge with the ability to work faster, more clearly, and more adaptively than those who came before them. That combination is not yet common, but it’s also not out of reach.

For more on how tax professionals are navigating technological change, visit the or download the full 2025 State of Tax Professionals Report

Key takeaways:

• • • Employees face contradictory messages or none at all — 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 — 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 — 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 ReportĚýfrom the Thomson Reuters Institute (TRI), reveals a disconnect between AI availability and organizational guidance, which is creating confusion that may undermine both employee experience and the technology’s potential value. (The report’s 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 — 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 — or failing to measure — 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 — but that may be happening without roadmaps from their employers.

In addition, notable barriers in employees’ 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’ 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 — 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 — 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 — 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 Thomson Reuters Institute’sĚý2026 AI in Professional Services ReportĚýhere

Key highlights:

• • • Universities face pressure over pedagogy— Academic institutions are adopting AI as a reputational marker that’s driven by market pressure rather than educational need, creating a risk for students who can work with AI but not independently of it.

    • Entry-level roles under threat— AI is being deployed most heavily to automate the grunt work of entry-level positions in which foundational professional skills are traditionally built through struggle and feedback.

    • K-shaped cognitive economy emerging— Experienced professionals with existing expertise are gaining efficiency from AI, while entry-level workers are losing access to skill-building experiences.

According to Harvard University’s Professional & Executive Development division, innovation is defined as a “process that guides businesses through developing products or services that deliver value to customers in new and novel ways.” Along this journey, professional judgement in decision-making is used numerous times to determine next steps at key stages.

Notably, the word technology is nowhere to be found in this definition — an absence , Assistant Professor of Learning Technologies at the University of Minnesota, has long found revealing. Instead, innovation is framed as creative problem-solving, contextual intelligence, and the ability to work across perspectives. Interestingly, Dr. Heinsfeld adds, none of these require constant automation. In fact, many of them are undermined by it.

However, AI adoption has the real potential to automate away the very experiences that build these capabilities from university lecture halls to corporate offices. With notable data already suggesting that , the risk that the current approaches to AI use in universities and companies are engineering away innovation and professional judgement skills is real, notes , Group Leader in AI Research at Harvard and NTT Research.

Indeed, some observers view AI as the largest unregulated cognitive engineering experiment in human history. Yet, unlike medical drugs that require years of approval and testing, AI systems are reshaping how millions of students think, learn, and make decisions without a comparable approval process or a shared framework for discussing any potential “side effects,” as Dr. Heinsfeld pointed out.

Most worrisome is that AI is being deployed most heavily to automate precisely the entry-level roles where foundational professional skills are built.

So, what happens when an entire generation of future employees learn to delegate judgment before they develop it? And what actions do universities and companies need to take now to avoid this reality?

Risks of universities adopting AI under pressure

For universities, AI “has become a reputational marker, and not adopting AI is framed as institutional risk, regardless of whether an educational case has been made or not,” says Dr. Heinsfeld, adding that this is being driven, in part, by market pressure rather than pedagogical need.

Already, companies can greatly influence universities as employers of new graduates; and as such, AI systems are currently being optimized for speed, agreeability, and accessibility to stimulate ongoing use. However, as Dr. Heinsfeld contends, as universities race to earn the label AI ready without a careful, cautious and detailed understanding of how it may impact students’ cognitive processes, they run the risk of damage to their reputations of pedagogical integrity.

In addition, the “data as truth” paradigm is a complicating factor, she says. Drawing on her research, Dr. Heinsfeld explains how data “is often framed as the idea of being a single source of truth based on the assumption that when collected and analyzed, it can reveal objective, indisputable facts about the world.” Indeed, this ubiquitous mindset across universities and corporations treats data — such as that used to train large and small language models — as objective and indisputable.

Yet this obscures critical decisions about what gets measured, whose perspectives are included, and what forms of knowledge are systematically excluded from AI systems. As Dr. Heinsfeld warns, when data becomes synonymous with truth, “knowledge is what is measurable and optimizable.” This narrows professional judgment to efficiency metrics rather than the interpretive depth, ethical reasoning, and cultural context that are essential for sound decision-making.

Judgment gap widens in workforce downstream

Under the current AI adoption approach, students could leave universities able to workĚýwithĚýAI but not independentlyĚýofĚýit, a distinction emphasized by Dr. Heinsfeld. Like calculators, AI works as a tool only when foundational skills for its use exist first. Without this, graduates enter the workforce with a critical judgment gap that compounds from their lives as students at college campuses to becoming employees working in corporations.

AI adoption has the real potential to automate away the very experiences that build these capabilities from university lecture halls to corporate offices.

Most worrisome is that AI is being deployed most heavily to automate precisely the entry-level roles where foundational professional skills are built, warns Dr. Tanaka. Indeed, this is exactly the type of grunt work that teaches judgment through struggle and feedback. Over time, overuse of AI will result in quality being sacrificed because critical evaluation skills have atrophied.

Looking into the future, Dr. Tanaka foresees a K-shaped economy of cognitive capacity. Experienced professionals with existing expertise and contextual judgment built through years of experience will gain increasing efficiency from AI. Entry-level workers, however, will lose access to the valuable experiences that build professional judgement. This gap widens between professionals who can independently accelerate their workflows using AI and those whose traditional tasks are merely displaced by it.

Intervention may be able to break the cycle

The pattern is not inevitable, as both Dr. Tanaka and Dr. Heinsfeld explain. Drawing on Dr. Heinsfeld’s emphasis on institutional agency, meaningful intervention will depend on conscious, intentional choices made at every level. Both experts share their guidance for how different organizations can manage this:

Academic institutions — Universities must first recognize that AI adoption is a decision rather than an inevitability and make educational need the North Star for decision-making around AI. In her analysis, Dr. Heinsfeld emphasizes that when vendors set defaults, they quietly redefine academic practice. Defaults shape what is made visible or invisible and what becomes normalized. In AI-driven environments, universities often lose control over how models are trained and updated, what data shapes outputs, how knowledge is filtered and ranked, and how student and faculty data circulate beyond institutional boundaries — especially if decision-making is left to vendors. As a result, the intellectual byproducts of teaching and learning increasingly become inputs into external systems that universities do not govern.

Private entities — For organizations, Dr. Tanaka calls for feedback loops and other mechanisms that will promote more open discussion about AI use without stigma. In addition, companies need to proactively redesign entry-level rolesĚýto ensure these positions continue to cultivate judgment and foundational skills in an AI-driven environment. Likewise, Dr. Tanaka suggests that companies explicitly provide feedback about cognitive trade-offs to employees, fostering an understanding of possible skill entrophy.

Employees — Similarly, individuals working for organizations bear much of the responsibility for making sure critical thinking is enhanced by AI. Indeed, strategic decisions about when to use AI while seeking to preserve cognitive capacity and professional judgement are key.

Looking ahead

In today’s increasingly AI-driven environment, a new paradigm is needed to combat the current operating assumption that optimization from AI is the sole path to progress. And because the current trajectory sacrifices human development for efficiency, the need for universities and companies to choose a different path is urgent — while they still have the judgment capacity to do so.

You can find out more about how organizations are managing their talent and training issues here

Key takeaways:

• • • Tax departments lack resources and confidence — More than half (58%) of tax departments are under-resourced, and 59% are not confident that they can upgrade their tax technology over the next two years.

    • Under-resourced departments incur more penalties — At least half of respondents from under-resourced tax departments say their departments incurred penalties over the past year, compared to only about one-third of those from properly resourced departments.

    • Making the shift to proactive planning and value creation — For many tax departments, the winning model blends in-house expertise, targeted external support, and a coherent tech/AI stack that allows teams to shift from tactical compliance to proactive planning and strategic value creation.

Under-resourced corporate tax departments spend more of their budget on external support compared to well-resourced teams — yet they’re more likely to incur penalties and less confident in forecasting, according to the Thomson Reuters Institute’s .

Given this, the problem isn’t a lack of spending — it’s the operating model. With respondents from 58% of tax departments saying they are under-resourced, 59% saying they lack the confidence needed to upgrade their existing tax technology over the next two years, and most spending more than half their time on reactive compliance work when they’d prefer to focus on strategic planning, clearly the gap between ambition and reality has never been wider.

The answer isn’t working harder or throwing more money at consultants, however. It’s building a hybrid ecosystem of people, platforms, and partners designed to shift capacity from firefighting to foresight.

The Groundhog Day problem

Every year feels the same: New tax legislation (such as the One Big Beautiful Bill Act or Pillar 2), new compliance burdens, new geopolitical uncertainty — coupled with the same old constraints. Too much work, not enough time, and technology that lags.

When deadlines hit, under-resourced teams rely on two blunt levers: overtime and reactive outsourcing. Internal staff end up working longer hours, and external providers plug the gaps at short notice. This model is breaking departments and it’s breaking down itself.

Under-resourced departments are significantly more likely to incur penalties, with 50% of respondents saying their under-resourced department had been penalized in the past year, compared to just 34% of respondents from well-resourced departments that say that, according to the report.

Further, under-resourced department respondents said they were less confident in their ability to forecast accurately, with just 26% saying their ability to forecast accurately was “very likely” compared to 43% of well-resourced department respondents. Ironically, under-resourced departments also spend more on external support as a percentage of budget (44%) compared to 37% for well-resourced departments. Clearly, spending more doesn’t solve structural problems — it often masks them.

Meanwhile, tax professionals report spending more than half their time on tactical or reactive work, even though they would prefer to spend up to two-thirds of their time on strategic analysis. Not surprisingly, when the team is locked into manual reconciliations and last-minute fixes, it’s nearly impossible to influence business decisions or shape strategy.

Why “all in-house” or “all outsourced” no longer works

When more work is moved onto the plates of the internal tax team, all in-house can often come to mean all heroics — talented people drowning in compliance volume with no time to use the analytical tools already on their desks. Conversely, all outsourced risks hollowing out the department’s institutional knowledge and weakening its seat at the table.

A hybrid model asks better questions: What kind of work is this, and where does it create the most leverage? These questions can be used to determine where and to whom work should go. For example, high-volume, rule-based, recurring tasks are prime candidates for automation, shared services, or managed services under strong tax oversight; while complex, judgment-heavy, strategically sensitive work should remain anchored in-house, with external advisors extending capacity and offering specialized insight.

Thus, the best model for a modern corporate tax department is a hybrid ecosystem — not a fixed organizations chart, but a deliberate blend of internal expertise, enabling technology, and external capability partners.

Four layers of the hybrid ecosystem

This hybrid ecosystem can be delineated into four layers, each bringing their own insight and value:

1. 1. 1. People and roles redesigned — High-performing tax functions invest in analyst and tax-tech roles that connect tax to enterprise resource planning (ERP) systems, data hubs, and analytics, thus freeing technical experts from manual data work. Senior professionals then become embedded advisors to finance, treasury, and the business, not just compliance reviewers.
      2. Processes segmented into “run” and “change” — The biggest barriers to strategic work are excessive volume, heavy compliance burdens, limited resources, and time pressure. Modern tax departments respond by explicitly segmenting work in which run the business processes are documented, standardized, and increasingly automated or pushed into shared or managed service models. Change the business work remains tightly linked to senior tax staff.
      3. Technology becomes the data spine — More than half of respondents say they expect above-normal increases in their tax technology budgets, and more than half say their main resourcing strategy is introducing more automation. The goal isn’t collecting point solutions; rather, it’s building a coherent data spine that includes ERP integration, tax-specific data models, consistent workflow tooling, and strategic platforms that flex as regulations shift.
      4. AI act as an accelerator — Two-thirds of tax departments aren’t yet using generative AI (GenAI), according to the report. And among the one-third that are, usage clusters around research, document summarization, drafting, and some analytical support. The next step up the AI chain is for departments to move from individual experiments to standardized, governed workflows that scan legislation, prepare first drafts of memos, or interrogate large data sets for anomalies.

What high-performing hybrid tax departments do next

Departments that feel well-resourced, allocate more time for their professionals to conduct proactive work, and invest deliberately in technology and skills are significantly more confident in their ability to forecast accurately, avoid penalties, and minimize tax liabilities, the report shows.

Indeed, these high-performing hybrid tax departments:

• • • invest ahead of crises in people, tech, and processes
    • treat external providers as capability partners, not emergency relief
    • actively protect time for strategic work by automating or outsourcing routine tasks
    • insist on a durable seat at the strategy table, not just one for compliance reporting
    • experiment with automation and AI in focused, repeatable use cases

It is worth noting that smaller companies (those under $50 million in annual revenue) and the largest one (those with more than $5 billion in revenue) are leading the way by securing leadership buy-in early and leveraging specialized external expertise rather than trying to build everything in-house. Midsize companies, by contrast, are more likely to rely on in-house teams to lead automation efforts and less likely to use third-party vendors — a cautious approach that risks having them fall too far behind to catch up.

The message: Design the ecosystem, don’t just work harder

For corporate tax professionals, the message may be harsh but hopeful: You cannot work your way out of structural constraints by effort alone. Rather, a well-designed hybrid ecosystem can turn those constraints into a catalyst that will allow the department to deliver more value to the business. In fact, the modern corporate tax department is hybrid by necessity; but the question is whether it’s hybrid by design — or just by accident.

You can learn more about the challenges facing modern corporate tax departments here

You can read TRI’s latest “Inside the Shift” feature,ĚýThe human side of AI: The growing risks of ubiquitous use of AI on talent here

It’s no exaggeration to say that AI is everywhere in our workplaces right now. It writes our emails, summarizes our meetings, generates slides, and even helps us think through problems. On the surface, this may sound like progress — and in many ways, it is.

However, our latestĚýInside the ShiftĚýfeature, The human side of AI: The growing risks of ubiquitous use of AI on talent by Natalie Runyon, Content Strategist for Sustainability and Human Rights Crimes for the Thomson Reuters Institute, makes a clear and timely point: When AI use becomes excessive and unchecked, it can quietly undermine the very people it’s meant to help.

One major consequence of cognitive decay is the weakening of the brain’s capacity to engage deeply, question systematically, and — somewhat ironically — resist the potential manipulation of AI.

As the article goes into in much greater detail, these harms caused by AI overuse can include a slow erosion of human connections, a loss of a professional’s sense of purpose, and a general sense of feeling overwhelmed in the workplace.

Of course, the solution isn’t to reject AI, it’s to use it better. To this end, the article makes a strong case for organizations to foster hybrid intelligence, a process by which human judgment and creativity work alongside AI capabilities.

In today’s workplace, AI can be a powerful advantage; however, that is only if organizational leaders can remember that technology should enhance the human experience, not replaces the parts of professional life that workers value.

To examine this and many more situations, the Thomson Reuters Institute (TRI) has launched a new feature segment,ĚýInside the Shift, that leverages our expert analysis and supporting data to tell some of the most compelling stories professional services today

Key highlights:

• • • Human connection is now a competitive capability — Treat relationships as core infrastructure instead of cultural fluff by designing work to keep real collaboration, accountability, and regular face-to-face interaction at the center with AI in a supporting role.

    • Protect your judgment and meaning as “human-owned” — Start with independent frameworks and reasoning, then use AI to refine and stress-test; and schedule recurring “no-AI” blocks to keep analytical muscle and professional agency strong.

    • The winning model is hybrid intelligence — The standout professionals in 2026 will be those who are fluent in both human dynamics and AI assisted workflow.

Professional services work fundamentally relies on judgment, trust, and relationships. Clients engage firms for confidence and strategic guidance, while a good reputation in this sector develops through the consistent delivery of high-quality counsel. While AI can enhance these capabilities, these technologies may also erode professional value if permitted to displace the distinctly human elements that differentiate exceptional service.

The imperative for 2026 is to maintain full professional capability by embracing human strengths while leveraging technological tools. Consistent application of the following practices will protect and develop the competencies that AI cannot replicate.

Build your human connections muscle

In the near future, professionals may spend more time interacting with AI systems than they do with colleagues. Over time, AI creates opportunities to disengage from human interaction; and AI systems remain consistently agreeable, perpetually available, and never introduce tension into professional discourse.

For time-constrained professionals, this predictability may appear advantageous; however, this convenience carries a substantial cost. In professional services, relationships constitute essential infrastructure rather than supplementary benefits. When professional interaction shifts from human to machine interface, social acuity diminishes as professionals lose exposure to subtle human dynamics. Critical developmental experiences — including the ability to manage discomfort, resolve misunderstandings, and navigate the productive friction that builds capacity for maintaining and repairing strained relationships — become scarcer.

To preserve human connection capacity with intention, implement these measures:

• • • Prioritize work that requires genuine collaboration and shared accountability and keep AI as a supporting resource.
    • Establish regular face-to-face interaction, both virtual and in-person, with colleagues to invest in relationship-building conversations that extend beyond project deliverables and timeline discussions.
    • Actively engage in professionally challenging interactions, including those involving constructive feedback delivery and negotiation. These experiences maintain trust and prevent the gradual atrophy of human collaboration skills.

Protect your brain and your meaning at work

AI technologies offer substantial efficiency gains through automated drafting, summarization, and information analysis. However, excessive reliance on these capabilities may diminish the cognitive repetitions that maintain professional acuity. In professional services, intellectual capacity, which includes attention to detail and analytical reasoning, constitutes the primary asset. This capacity requires the ability to discern significance, interrogate underlying assumptions, and articulate complex tradeoffs with precision.

Delegating these cognitive tasks to AI systems daily may yield short-term efficiency while lowering costs, but this may lead to work becoming ambiguous and require less nuanced judgment. As a result, professional instincts may atrophy.

An additional consequence of AI overreliance involves the erosion of professional meaning and engagement. When AI systems generate the majority of intellectual output, professionals may risk becoming approvers rather than creators. Work devolves into review and authorization — a repetitive pattern that can lessen one’s connection to making a substantive professional contribution. Indeed, the role begins to resemble a production line of incremental validations rather than meaningful professional practice.

To avoid this, you should implement the following practices to preserve both intellectual rigor and a meaningful sense of agency over critical professional activities:

• • • Integrate deliberate cognitive exercises into weekly routines — Initiate substantive work with independent analysis — by establishing frameworks, identifying priorities, and constructing logic — before employing AI to refine structure, enhance clarity, and stress-test reasoning. Subsequently, critically evaluate AI-generated output by identifying omissions, examining underlying assumptions, and assessing potential errors.
    • Establish dedicated periods for unassisted professional work — Schedule regular intervals for research, conceptual development, and drafting without AI support to ensure sustained development of analytical capacity and professional judgment.
    • Anchor work to meaning and outcomes — Identify work of particular professional significance and maintain direct engagement with these tasks, again without AI assistance. Regularly reflect on the tangible impact of contributions, including the delivery of client value and the support of colleagues, in order to better sustain meaningful connection to professional purpose.

Hybrid intelligence is the future

The most effective professionals in 2026 will be those that are focused on their capacity to integrate human literacy with algorithmic literacy, which is a competency framework known as hybrid intelligence.

Human literacy remains the fundamental differentiator in professional services, encompassing the ability to interpret interpersonal dynamics, establish trust amid complexity, deliver constructive feedback with appropriate sensitivity, and maintain both self-awareness and relational intelligence.

Algorithmic literacy involves understanding the specific capabilities and limitations of AI tools, including honing a proficiency for output verification, tool evaluation, and sustained awareness of bias and risk considerations.

The combination of these two factors within hybrid intelligence can give professionals a potent way of fighting the accelerating cognitive deterioration andĚýagency decayĚýthat some may experience with AI overuse.

Today, organizational mandates for AI adoption are becoming increasingly prevalent and will approach universality over the next few years. While firms compete through technological capability, competitive differentiation will ultimately derive from the human excellence of their professionals — a dynamic that will similarly shape individual career trajectories.

You can find out more about how a focus on power skills can help professionals in the workplace here

Key takeaways:

• • • Immediate R&D deductions — The One Big Beautiful Bill Act introduces Section 174A, which restores immediate deduction of domestic research and experimental expenditures starting in tax years beginning after December 31, 2024, reversing the controversial five-year amortization requirement that took effect in 2022.

    • Retroactive tax changes — Small business taxpayers with average annual gross receipts of $31 million or less (for tax years beginning in 2025) will generally be permitted to apply this change retroactively to taxable years beginning after December 31, 2021, offering significant opportunities for amended returns and potential refunds.

    • Planning considerations needed — The legislation modified Section 280C, which now requires that domestic R&E expenditures be reduced by the amount of research credit, creating new planning considerations for businesses claiming R&D tax credits alongside Section 174 deductions.

The Tax Cut and Jobs Act (TCJA), enacted in December 2017, brought significant changes to Section 174, impacting how businesses account for research and development (R&D) expenditures. With the passage of the One Big Beautiful Bill Act earlier this year, the landscape has shifted dramatically once again, requiring tax departments to engage in strategic planning and proactive tax management.

Section 174: From immediate expense to amortization

First enacted in 1954, Section 174 allowed for the deduction of expenditures related to R&D in the year the expense occurred. The TCJA eliminated the ability to deduct R&D costs as an expense in the year incurred, requiring costs to be amortized over five years for domestic research and 15 years for research outside of the United States.

Over the years, the IRS released guidance several times on how best to approach Section 174’s R&D capitalization. The most recent substantive guidance came in Notice 2023-63 (in September 2023), which provided interim guidance on the capitalization and amortization of specified research or experimental expenditures; and Notice 2024-12 (December 2023), which clarified the earlier guidance. Additionally, Revenue Procedure 2025-8 (December 17, 2024) provided updated procedural guidance for taxpayers filing automatic accounting method changes related to Section 174 expenditures.

Since the changes to Section 174 took effect in 2022, businesses have struggled to track R&D costs, including what should be excluded or included. This shift created cash flow challenges for innovation-driven industries, leading to widespread calls for reform.

The One Big Beautiful Bill Act: A game-changer for R&D expensing

The One Big Beautiful Bill Act (OB3) that was signed into law by President Trump on July 4th, brought sweeping changes to the tax treatment of domestic R&D expenditures. Under a new addendum, Section 174A, capitalization is no longer required for qualified domestic research activity for tax years beginning after December 31, 2024.

This represents a major victory for businesses that have been lobbying for relief from burdensome amortization requirements. For many businesses, this change will simplify tax compliance, improve cash flow, and reduce overall tax liability.

Importantly, amounts paid or incurred in connection with software development are treated as R&E expenditures eligible for immediate expensing, which can provide particular relief to technology companies and startups. However, research or experimental expenditures attributable to research conducted outside the United States must continue to be capitalized and amortized over 15 years, creating a bifurcated system that requires careful tracking of domestic R&D activities, compared to foreign activities.

The OB3 legislation also includes particularly generous provisions for small businesses. Small taxpayers — those defined by a gross receipts threshold established in Section 448(c) — can amend tax returns as far back as 2022 to reverse the capitalization of R&E expenses. The Section 448(c) threshold is adjusted annually for inflation; and currently, for tax years beginning in 2025, the threshold is $31 million in average annual gross receipts over the prior three tax years.

For all taxpayers that made domestic research or experimental expenditures after December 31, 2021, and before January 1, 2025, will be permitted to elect to accelerate the remaining deductions for such expenditures over a one-year or two-year period, providing flexibility in managing taxable income.

Planning for the new landscape

While the OB3 provides welcome relief, corporate tax professionals must remain vigilant and proactive. The legislation introduces new complexities, particularly around . The change mirrors the Section 280C rules that were in place prior to the enactment of TCJA in 2017, although taxpayers still have the option to make an election under Section 280C that would reduce their research credit by the maximum corporate tax rate (21%) in lieu of reducing their domestic R&E expenditures.

Here are other key considerations for corporate tax department leaders navigating the new Section 174A landscape:

Understanding qualified research — Tax departments must understand what is considered qualified research and development under the new rules. This involves staying current on all guidelines issued by tax authorities and working closely with the company’s R&D team. Critically, teams must now distinguish between domestic and foreign R&D activities, as the tax treatment differs significantly. This information should be communicated to upper management when considering product expansion or enhancements.

Documentation & recordkeeping — Concise documentation of any expense activity remains essential. Tax departments should capture now and decide later — because it’s better to have the data than not. For any R&D activity that takes place outside of the US, all data should be captured separately from domestic activities. Corporate tax departments should systemize documentation, collection, and storage of R&D expense-related information.

Amended return opportunities — Small businesses should immediately evaluate whether they qualify for retroactive relief and assess the potential benefits of amending their returns for the years 2022 through 2024. Even larger taxpayers should analyze whether electing to accelerate remaining unamortized amounts into 2025 or splitting them between 2025 and 2026 provides optimal tax outcomes.

Section 280C planning — Departments must carefully model the interaction between R&D tax credits and Section 174A deductions. The restored reduction requirement means businesses must evaluate whether making the Section 280C election to reduce the credit rather than taking the deduction would provide better overall tax results.

Scenario planning — Departments should develop multiple financial models based on different elections and timing strategies. This will help the company understand the range of impacts these changes will have on cash flow, net operating losses, and overall tax liability.

The OB3 represents a major course correction for R&D tax policy, but it requires tax professionals to adopt a proactive approach to maximize benefits. Corporate tax departments can navigate these changes effectively by staying informed about legislative developments, engaging in continuous learning, and leveraging advanced tax planning strategies. Also, collaboration with internal teams and external advisors will be crucial in identifying opportunities and mitigating risks.

Ultimately, establishing a proactive and nimble mindset will enable corporate tax professionals to optimize their positions and drive business success in this evolving regulatory landscape.

You can find more about how the One Big Beautiful Bill Act has impacted tax issues here

Key takeaways:

• • • Advocate for investment in technology and talent — As compliance and strategic demands grow, tax departments should use benchmark data from industry reports to build compelling business cases for automation, generative AI, and additional headcount.

    • Explore transferable tax credit opportunities — The transferable tax credit market has matured significantly, more departments should pursue these to offset tax liability, reduce estimated quarterly payments, and free up cash flow.

    • Proactively manage the OB3 transition — The One Big Beautiful Bill Act introduces substantial federal tax changes requiring strategic planning for 2026. Document analysis carefully as state conformity issues create future audit exposure.

The corporate tax landscape in 2025 is defined by resource constraints, regulatory complexity, and rapid technological change. And many corporate tax department leaders face mounting pressures from compliance demands, talent shortages, and evolving legislation — all while being asked to deliver more strategic value to their organizations, according to the , published by the Thomson Reuters Institute and Tax Executives Institute.

Under-resourcing and strategic gaps persist

Perhaps the most striking finding from the 2025 report is that 58% of corporate tax department professionals said their departments are under-resourced — an increase from 51% who said that the previous year. This apparent deterioration in resourcing creates cascading risks for businesses. Departments facing resource constraints report higher rates of penalties and audits, with 44% of survey respondents saying their under-resourced department experiencing penalties in the past year and 12% saying it had faced penalties exceeding $1 million.

The good news is that more departments are planning to hire rather than rely on overtime from existing staff, the report shows. However, the talent pool remains tight, making recruitment challenging. For tax department leaders, advocating for investment in both talent and technology is essential for risk management and maintaining compliance.

For tax department leaders, advocating for investment in both talent and technology is essential for risk management and maintaining compliance.

The report also showed that corporate tax departments continue to struggle with an imbalance between strategic and tactical work, with in-house tax professionals noting that they spend the majority of their time on reactive, tactical tasks while ideally wanting to reduce this to approximately 30% to 38% of their time.

What’s holding teams back? Excessive workload volume tops the list, they said, followed by complex compliance requirements, limited resources, and outdated technology. While two-thirds of respondents said their departments are still in the chaotic reactive stage of technology maturity, more than half said they expect higher-than-normal budget increases for investment in tax technology in the coming year, with many beginning to incorporate generative AI (GenAI) into their workflows.

Opportunities to create value exist

While these challenges exist, there are ways that corporate tax departments can identify and pursue value in the coming year. For example, the passage of the One Big Beautiful Bill Act (OB3) in mid-2025 introduced substantial changes to federal tax provisions including the ability to immediately expense research and experimentation costs under Section 174, reintroduction of full bonus depreciation, and liberalized interest deduction limitations.

The new Section 904(b) rules significantly improve the foreign tax credit mechanism by eliminating the allocation of interest expense and research and experimental (R&E) expenses to foreign source income, potentially lowering effective tax rates from 18.9% to approximately 14% at the aggregate level.

Departments that invest in technology, build strong business partnerships, and track their value contributions are demonstrating that having a strategic impact is possible even in resource-constrained environments.

However, OB3’s retroactive application to tax year 2025 creates immediate compliance complexity. State conformity issues compound the challenge, as many states have not yet updated their codes, creating potential mismatches between federal and state taxable income calculations.

Further, the transferable tax credit market has matured significantly, with nearly 25% of Fortune 1000 companies now participating, which is a 60% increase over 2024. Current market conditions favor buyers, with investment tax credits and production tax credits trading at discounts of 89-cent to 91-cents on the dollar.

These credits can offset tax liability, reduce estimated quarterly payments, and free up corporate cash flow. Tax departments should explore this opportunity as another tool for creating measurable value for the business.

Planning for 2026 and beyond

Despite the challenges facing corporate tax departments in 2025, success stories abound. Departments that invest in technology, build strong business partnerships, and track their value contributions are demonstrating that having a strategic impact is possible even in resource-constrained environments. The key is making the case for investment, staying ahead of regulatory changes, and continuously communicating your added value back to the business.

You can downloadĚýa full copy of theĚý, from the Thomson Reuters Institute and Tax Executives Institute, here

Key takeaways:

• • • Reframe your value proposition — Translate tax achievements into business language the C-suite understands, such as protecting shareholder value, enabling growth, and mitigating risk rather than simply reporting compliance metrics.

    • Invest strategically in technology and talent — Prioritize automation and AI tools while outsourcing strategically to free internal resources for high-value strategic work that demonstrates the department’s business impact.

    • Build cross-functional partnerships — Proactively collaborate with IT, legal, operations, and HR on enterprise-wide initiatives that will position the tax function as an essential strategic partner rather than an isolated compliance department.

SAN FRANCISCO — In recently released , published by the Thomson Reuters Institute and Tax Executives Institute,Ěýa large portion of the tax department professionals surveyed expressed their desired to do more strategic work compared to simple tactical work. This was a theme we’ve seen repeatedly across our research: Tax professionals are shedding their traditional compliance-focused image and moving toward becoming strategic business partners to their organizations.

By articulating their value proposition, investing strategically in technology and talent, and aligning with broader business objectives, tax department leaders can secure the resources and influence needed to drive meaningful organizational impact.

Yet, the tax function has long been viewed as a necessary cost center — a department that ensures compliance, files returns, and manages audits — despite the essential work that in-house tax professionals do. Rarely did these professionals feel they are treated as strategic business partners. However, perception is rapidly changing, according to the insights shared at the recentĚý.

Today’s tax leaders are positioning their teams as strategic partners who provide critical insights that influence business resilience, growth strategies, and organizational risk management, conference panelists explained.

The evolving role of the tax function

Amid ongoing tax and trade policy shifts and increased business uncertainty, opportunities abound for tax professionals in corporate tax departments. Indeed, several panelists noted that the State of the Corporate Tax Department report showed that tax leaders are increasingly becoming deeply involved in strategic decisions ranging from business resilience strategy (with 63% of survey respondents saying their tax department is involved in this area) to M&A transactions (60%), organizational risk management (58%), and supply chain management (55%).

Further, CFOs are increasingly looking to their in-house tax leaders for support across multiple strategic areas, including digital transformation and AI, ESG strategy, workforce strategy, and economic resilience planning. This expanded role creates for the tax team creates both opportunities and challenges for those seeking to demonstrate their strategic value.

By articulating their value proposition, investing strategically in technology and talent, and aligning with broader business objectives, tax department leaders can secure the resources and influence needed to drive meaningful organizational impact.

In fact, one of the most pressing question tax leaders face is how to secure adequate budget funding in an environment of competing corporate priorities. The answer lies in strategic thinking about resource allocation and being intentional about having a seat at the table to better advocate for necessary investments. Tax department leaders must educate executive leadership on the risks that come with not having enough budget resources — from trying to do more with less to the potential for the company to face more exposure and risk that includes increased audits and fines.

As session panelists explained, the key is to frame discussions in terms that C-Suite leaders understand. Rather than simply requesting more resources, tax leaders should articulate how investments in the tax function can all it to better protect revenue, enable growth opportunities, and mitigate organizational risk.

Creating a value-focused identity

That articulation to management is a big step toward a tax function’s goal to move from feeling and acting like a cost center to being a strategic partner to the business. Indeed, corporate tax department leaders must change their own perceptions of how the department is perceived first — in essence, rebranding themselves and reimagining their identity. This starts with creating a compelling value story that resonates with the C-suite.

Start with creating (or recreating) a department mission statement that emphasizes value creation rather than mere compliance, aligning with broader priorities of the organization, such as business partnership and growth. Then, work to provide insights to drive decisions, and support regulatory demands while maintaining transparency.

Check out for more insight on how corporate tax professionals shift from compliance to strategic work

One practical approach is to speak the language of the C-suite by translating tax achievements into business metrics that executives care about, panelists added. For example, rather than reporting that the department completed the tax provision on time, frame it instead as the department protected $X million in shareholder value through accurate financial reporting or enabled the acquisition to close on schedule by providing timely tax due diligence.

It is also important for tax departments to track and communicate their wins consistently, panelists said, creating regular touchpoints with executive leadership to share accomplishments that position the tax function as a proactive business partner.

Navigating technology, talent, and collaboration

Technology investment represents both an opportunity and a challenge for tax departments, as the State of the Corporate Tax Department report makes clear. More than half of the respondents say they expected some increase in their budgets to invest in new tech tools over the next few years, and many indicate they plan to invest in tools and solutions to automate their workflow, especially those that support machine learning and generative AI (GenAI).

While it is great they are anticipating an increased budget, panelist explained that tax department leaders must educate management on the practical challenges of AI adoption, including the need for clean, well-structured data as a foundation.

It is also important for tax departments to track and communicate their wins consistently, creating regular touchpoints with executive leadership to share accomplishments that position the tax function as a proactive business partner.

On another point, staffing remains one of the most critical challenges facing tax departments, and many survey respondents cited hiring as key strategic priority, according to the report. Many departments will also look to technology to augment the missing talent and strategically use outsourcing and co-sourcing to alleviate talent pressure as well. And by partnering with external advisors for specialized compliance work or surge capacity during peak periods, tax departments can further free up internal resources to focus on higher-value strategic activities.

In fact, a central theme the session panelists leaned into was how the most effective tax departments build strong collaborative relationships across the organization. According to the report, 94% of CFOs and tax leaders report that the CFO helps facilitate cross-collaboration between tax and other functions such as legal, IT, operations, and finance.

Tax department leaders should proactively seek these opportunities to partner with other departments on strategic initiatives; for example, collaborating with IT on digital transformation, working with operations on supply chain optimization, partnering with legal on M&A transactions, and supporting HR on workforce strategy.

Today, the transformation of the corporate tax function from cost center to strategic partner is not merely aspirational — it is already underway in many forward-thinking organizations. As tax, audit, and trade policy become more complex and business uncertainty continues to mount, the opportunity for tax leaders to demonstrate their strategic value to the organization has never been greater.

You can downloadĚýa full copy of theĚý, from the Thomson Reuters Institute and Tax Executives Institute, here