Key insights:

• • • The duty of competence now includes technology 鈥� Rules first written for legal knowledge and diligence are being read to cover the tools lawyers use, not just the arguments they make.

    • The rules didn’t anticipate AI, but they still apply 鈥� Formal opinions and updated guidance make clear that generative and agentic AI fall squarely within lawyers鈥� existing ethical obligations.

    • What reaches the court carries the highest stakes 鈥� A lawyer’s technology missteps are most consequential, and most visible, the moment they show up in a filing, an exhibit, or an argument made to a judge.

Every attorney holds a duty of competence, and that duty has always included legal knowledge and sound judgment. Today, however, it now extends to technology as well. Often called 鈥�technical competence鈥�, today鈥檚 duty of competence requires understanding the benefits and risks of the tools used in practice, not just the law itself.

The American Bar Association’s Model Rules of Professional Conduct describe an attorney’s duty of competence as the obligation to provide representation using the (Rule 1.1). Comment 8 of the rule states explicitly, in part: 鈥淭o maintain the requisite knowledge and skill, a lawyer should keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology鈥� .鈥�

Indeed, competence matters well beyond a lawyer’s own file. Every filing, brief, and exhibit is, in effect, a lawyer’s communication to the court, and the court relies on the presumption that what it receives has been prepared with care. When a lawyer misunderstands or misuses technology, whether that means citing an AI hallucination as precedent or mishandling e-discovery output, the failure lands directly on the judge’s desk.

Rules of professional conduct are written broad and durable, so they do not need constant revision. Even so, few could have anticipated the pace of technological change now reaching the legal field.

A lawyer cannot simply plead ignorance when technology goes wrong, and failing to understand the tools being used can lead to ethics complaints, sanctions, or malpractice claims. Perhaps even more damaging, it can just as easily undermine a judge’s confidence in everything else that lawyer submits.

Rules built to last meet a technology no one predicted

Each state and territory maintains their , but most draw heavily on the ABA’s Model Rules as a foundation. Precedent is also shaped by disciplinary proceedings and case law, including a growing number of cases in which judges have sanctioned lawyers for submitting AI-generated content that was never checked for accuracy.

Rules of professional conduct are written broad and durable, so they do not need constant revision. Even so, few could have anticipated the pace of technological change now reaching the legal field. E-discovery was an early example, already raising real questions about what a lawyer could certify to a court in good faith. The more significant shift today is generative AI (GenAI) and agentic AI, capable of producing legal analysis or even taking action with minimal human oversight, often producing material that looks polished and authoritative right up until a judge or opposing counsel checks it.

Recognizing this shift, the ABA issued in July 2024 on the use of GenAI tools in legal practice, confirming that the duty of competence applies squarely to AI. The Formal Opinion requires lawyers to understand these tools well enough to use them responsibly, supervise their output, and avoid overreliance on unverified results 鈥� a standard that matters most the moment a document is filed, or an argument is made in open court.

5 ways to stay ahead of the curve

Given how quickly legal technology is evolving, and how little margin for error exists once something reaches a judge, there are five practical ways that lawyers can maintain their technical competence, including:

1. 1. 1. Pursue CLEs and structured education 鈥� Continuing legal education courses focused on AI, e-discovery, and cybersecurity offer a reliable, credentialed way to stay current. Many state bars now offer, and some require, CLE credits specifically on legal technology, exposing lawyers to real-world case studies that include those involving AI missteps that have drawn judicial sanctions.
      2. Build personal familiarity through hands-on use 鈥� Reading about a tool is no substitute for using it. Treating AI as a “thought partner,” for drafting, brainstorming, or spotting issues, helps professionals develop an intuitive feel for what these tools do well and in which ways they fall short, long before a document ever reaches a court. This low-stakes experimentation on matters that don鈥檛 impact client confidentiality or sensitive data can help build practical AI fluency.
      3. Practice in sandboxes and controlled environments 鈥� Before relying on a new platform in an active matter, test it in a sandbox first. Many vendors and firms now offer walled-off spaces to explore a tool’s features and failure points without exposing real client data.
      4. Review organizational guidelines 鈥� Firms, courts, and bar associations increasingly publish their own AI use policies that cover permitted tools, disclosure requirements, and data security. A growing number of courts also require lawyers to certify or disclose any AI use in filings, making familiarity with local rules as important as firm policy.
      5. Choose the right tools for the task 鈥� Free consumer-grade AI tools may suit general research, but should not be used in matters involving privileged or sensitive information, let alone a court filing. Premium and fiduciary-grade platforms, built with legal-specific safeguards around data handling and auditability, are better suited for substantive casework. Matching the tool to the sensitivity of the task, rather than convenience, is critical.

Used together, these five habits can help lawyers build a durable foundation in AI literacy. While technology will keep evolving, of course, any lawyer who has internalized this approach will be far less likely to be caught off guard once their work is tested in front of a judge.

Why this is about more than just the rules

Maintaining technical competence is not simply about avoiding disciplinary consequence. It is about preserving what the legal system is meant to provide. When lawyers understand the technology they use, including AI, they can apply it to research and review in ways that benefit clients and courts alike.

Just as importantly, technical competence protects the public’s trust in the legal profession, and something more immediate: a judge’s ability to rely on what lawyers put in front of them. In the end, technical competence is not a burden imposed by the rules; rather, it鈥檚 what allows the relationship between lawyers and the court, and the profession itself, to keep working.

For more on AI in the courts, check out the 听鈥� a joint effort by the National Center for State Courts听(NCSC) and the 成人VR视频 Institute (TRI)

Key insights:

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

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

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

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

Today, clients are expecting their outside UK law firms to go further into truly understanding the client鈥檚 business proposition, according to the recent 2026 State of the UK Legal Market Report from the 成人VR视频 Institute (TRI). And while efficiency and expertise remain top priorities, more corporate general counsel than ever before are rating business savviness and commerciality as key areas of focus. Clearly, GCs don鈥檛 just want legal advice from their outside firms, they want positive business outcomes.

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

Increased focus on enabling business processes

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

Amid this pressure, GCs have seen mixed results. They have instituted a number of changes to their departments in recent years, leading to the development of corporate legal operations teams and an increased focus on success metrics that tie back to the rest of the business. And while 86% of global GCs say they believe their legal department is a significant contributor to organizational objectives, according to TRI interviews, only 17% of C-Suite executives agree. GCs are doing the work, but corporate executives aren鈥檛 seeing their preferred results.

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

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

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

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

The impact of commercial focus

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

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

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

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

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

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

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

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

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

You can download a full copy of the 成人VR视频 Institute鈥檚 recent 2026 State of the UK Legal Market Report here

Key insights:

• • • De-banking reasons have to be articulated and verifiable 鈥� De-banking that鈥檚 driven by category avoidance rather than individual risk assessment, exposes institutions to legal, regulatory, and reputational harm and pushes legitimate customers out of the regulated financial system.

    • A screening flag is not a conclusion 鈥� Proper investigation must follow any identified red flag before any de-banking decision is made.

    • Political considerations have no place in de-banking decisions 鈥� The only defensible standard is documented, individualized risk analysis that would be applied consistently not matter the customer.

De-banking 鈥� or the involuntary removal of a customer from financial services 鈥� has moved from a compliance back-office concern to a front-page issue. Members of Congress have called for hearings.; advocacy groups representing small businesses, cryptocurrency firms, firearms dealers, and faith-based organizations have filed complaints; and financial institutions, often caught between genuine compliance obligations and growing pressure to justify their de-banking decisions, are operating in an environment with significant legal and reputational exposure on both sides.

Banks have the legal right to exit customer relationships, of course; however, what is in dispute is whether the decisions driving those exits are defensible. Are they grounded in documented, individualized risk analysis? Or are they being shaped by broad category avoidance, reputational anxiety, or political considerations that have no formal basis in law?

Getting this wrong is not a minor procedural failure; rather, it鈥檚 a legal exposure, a regulatory liability, and, increasingly, a legislative headache.

Objectivity requires removing politics from the process

The de-banking debate did not emerge recently. During , the U.S. Department of Justice (DOJ) initiative began in 2013, the government applied pressure on banks to exit relationships with industries it found undesirable, including payday lenders and firearms dealers, without formal legal prohibition.

The episode revealed a structural vulnerability: Financial institutions are susceptible to removing customers not because individual accounts present documented risk, but because external pressure, political or otherwise, has labeled entire categories of customers inconvenient. (The DOJ ultimately acknowledged the program was in August 2017.)

Banks have the legal right to exit customer relationships, of course; however, what is in dispute is whether the decisions driving those exits are defensible.

Yet, that pattern has persisted in subtler forms. Today, cannabis businesses operating legally under state law, money services businesses, crypto exchanges, and organizations associated with politically sensitive causes routinely report being dropped from banking relationships with little explanation and no apparent individualized analysis. The common thread is not confirmed financial crime, rather it鈥檚 membership in a certain category of enterprises.

In , President Trump issued an Executive Order titled “Guaranteeing Fair Banking for All Americans,” directly addressing this pattern and directing federal banking regulators to remove “reputation risk” and other subjective criteria from supervisory guidance and examination materials.

This is precisely where objectivity becomes a legal and operational imperative, not just a principle. A risk-based de-banking or off-boarding process must apply the same documented criteria to every customer, regardless of industry association, political affiliation, or public profile. When an institution debanks one customer for activity it tolerates in another, the inconsistency itself becomes the liability. have long reinforced that risk-based compliance means evaluating customers on their own merits, and that blanket policies applied to industries rather than individuals do not satisfy that standard.

Screening raises questions, and investigation answers them

One of the most consequential errors that financial institutions make is treating a screening alert as a final determination rather than a starting point. Know your customer frameworks, customer due diligence requirements, governmental watchlists, adverse media flags, and transaction monitoring alerts are tools for identifying accounts that warrant closer review. By themselves, they are not grounds for termination.

The gap between a flag and a confirmed risk finding is where decisions 鈥� both defensible and indefensible 鈥� are actually made. An adverse media hit on a business owner may reflect a decade-old civil dispute that has no bearing on current account activity. A transaction pattern that triggers a monitoring alert may have a straightforward, documented business explanation. Enhanced due diligence exists precisely because some customers require deeper analysis before a meaningful risk determination can be made.

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A risk-based de-banking or off-boarding process must apply the same documented criteria to every customer, regardless of industry association, political affiliation, or public profile.

A sound investigation process includes several elements that are often absent in practice, such as documented escalation paths from front-line staff to BSA officer to legal review; a genuine opportunity for the customer to respond to concerns before a decision is finalized; findings recorded in writing with sufficient specificity to withstand external scrutiny; and a proportionality review requiring the institution to evaluate whether risk mitigation short of termination is viable before defaulting to de-banking.

The stakes extend well beyond any single customer relationship

Financial institutions often treat de-banking as a discrete internal risk decision; however, the aggregate effect of category-based de-banking carries systemic consequences that regulators and legislators are increasingly unwilling to overlook.

When categories of legitimate customers cannot access banking services, the burden falls hardest on those with the fewest alternatives. Equally important, pushing customers out of the regulated financial system does not eliminate risk; instead, it relocates it to less transparent channels in which illicit activity is harder to detect and report.

Three states 鈥� Florida, Tennessee, and Idaho 鈥� have already enacted fair access laws requiring that financial institutions make services available based on objective risk criteria. And more than a dozen additional states have proposed . At the federal level, the would require larger banks to provide services based on quantified, documented risk standards.

Practical steps for financial institutions

Institutions need to build defensible, consistently applied processes as the foundation for any de-banking decision. There are several steps they can take, including:

• • • Audit current de-banking criteria for political and categorical language 鈥� Review existing off-boarding policies for any language that excludes industries or customer types based on perceived political sensitivity or reputational association rather than documented risk.
    • Establish a neutrality standard in all de-banking decisions 鈥� Require that every de-banking decision be traceable solely to facts in the customer file. External pressure, government signals, and industry headlines should play no role in the determination.
    • Separate screening from decision-making 鈥� Build a formal investigation step between any monitoring alert or red flag and a de-banking decision. Document what was reviewed, who reviewed it, and what the findings support.
    • Create a customer response mechanism 鈥� Where legally permissible, provide customers with an opportunity to respond to concerns before a final decision is made. Record whether and how that response was considered.
    • Establish a proportionality review 鈥� Before exiting a relationship, require a written determination that any other risk mitigation, including enhanced monitoring, transaction limits, or additional documentation requirements, was evaluated and found insufficient. Document everything.

As regulatory scrutiny around de-banking decisions intensifies, financial institutions can no longer treat it as a routine internal decision. The path forward demands consistent, well-documented, and objectively applied processes that stand up to legal, regulatory, and public scrutiny. Institutions that embed neutrality, transparency, and proportionality into their decision-making will not only reduce risk but also will strengthen trust in the financial system as a whole.

You can find more about the challenges facing financial institutions here

Key insights:

• • • Agentic AI acts autonomously, creating new accountability challenges 鈥� Agentic AI acts and makes decisions with minimal human intervention, and this shift changes everything about responsibility and oversight.

• • • With intentional design, the risks can be addressed confidently 鈥� Silent failures, accountability diffusion, and confidentiality breaches can only be mitigated through governance, testing, and rigorous human oversight.

• • • AI is changing legal work, not eliminating it 鈥� When agentic AI handles routine tasks, legal professionals can move their attention onto higher-value work and increased responsibilities.

It is no longer useful to treat all AI as a single category or a tool for a single use case. Generative AI (GenAI) has already begun reshaping legal work by drafting documents, researching precedents, and answering questions with remarkable speed. At its core, however, GenAI remains a responsive tool. Agentic AI, on the other hand, represents a distinct evolution. Rather than waiting for a prompt, agentic AI systems can plan workflows, carry them out autonomously, and make decisions along the way.

As technology and the judicial system become increasingly intertwined, it is essential to examine where these more advanced tools intersect and what that convergence means for legal institutions. Ankita Upadhyay, Senior Director of AI Enablement at 成人VR视频, recently shared her perspective during a recent webinar,听, presented by the听听鈥� a joint effort by the National Center for State Courts听(NCSC) and the 成人VR视频 Institute (TRI) 鈥斕齛nd offered valuable insight into the opportunities and responsibilities that accompany this shift.

One of the key notes to understand from the panel is that 鈥済enerative AI gives you an answer. Agentic AI takes an action 鈥� and that distinction changes everything about the accountability,” Upadhyay said, adding that the distinction is not merely technical. It must reshape how we think about professional responsibility and the integration of AI into institutions that are built on trust and accuracy.

The promise of efficiency and transformation at scale

The potential of agentic AI is already visible in courts across the country. In Palm Beach County, Fla., for example, court officials are using agentic AI to process incoming documents at unprecedented scale. When an attorney files a document, the system autonomously identifies the document type, classifies it, extracts data, and routes it appropriately. The county already has processed up to 5 million documents using this process, operating 20 hours a day, every day of the year.

The most important part isn’t just the volume, however, it’s what happened to the people.

The staff who spent time on routine document processing were not laid off; instead, they were reassigned. Clerk 1 positions were transitioned to Clerk 3 and Clerk 4 roles, and that meant greater responsibility, more complex decision-making, and increased compensation for those making that transition.

“The staff that was doing all the processing of documents has been reallocated to customer experience and more complex tasks,” explained Parik Chokski, Director of IT for Palm Beach, on the webinar. This development reflects a broader truth: AI is not taking jobs in the legal sector; rather, it鈥檚 changing what those jobs entail.

You can explore the white paper听听here

As more repetitive work moves to AI, legal professionals move their attention toward the kind of work that demands their judgment, expertise, and accountability.

Risks are real, but not insurmountable

Yet the promise of agentic AI comes with genuine risks that differ from those posed by generative AI. Because agentic AI acts autonomously, for instance, failures can occur silently and invisibly, and sometimes repeatedly before detection.

成人VR视频鈥� Upadhyay identified three predominant risks for legal professionals and their organizations with agentic AI use:

1. Accountability diffusion 鈥� When an agentic AI system produces a document through a chain of autonomous decisions, it becomes difficult to determine where human judgment ended, and machine decision-making began. This ambiguity directly challenges professional conduct rules, which assume lawyers make every material decision. The result is an unclear line of responsibility and potential legal exposure for the lawyer.

2. Confidentiality at scale 鈥� Agentic AI systems operate across entire databases and multiple use cases simultaneously. A single misconfiguration of permissions can allow an AI agent to access privileged information to which it shouldn’t have access, potentially sharing sensitive client data across unintended matters. The danger lies in the fact that this often happens silently and repeatedly until discovered.

3. Irreversibility 鈥� Unlike GenAI, where a flawed draft often gets caught during review, agentic AI can send client communications, file documents, or update records based on faulty reasoning even before human oversight intervenes. The speed of action outpaces the speed of review, and thus, it creates a gap that traditional legal processes weren’t designed to address.

“The risk isn’t that AI gets it wrong,鈥� Upadhyay said. 鈥淭he problem is agentic AI systems, when it gets things wrong, it happens silently in a black box until you monitor it, and that’s the biggest challenge.”

Guardrails for responsible implementation

Given this, how do courts and legal organizations implement agentic AI thoughtfully? The webinar panelists, drawing on real-world implementations and NCSC research, emphasized several critical actions, including:

Establish clear governance 鈥� Begin with centralized registration of all agentic AI agents, conduct rigorous risk classification based on task impact, and start with low-risk workflows before advancing to high-stakes tasks. “Having a proper agentic AI governance is really important,” Palm Beach’s Chokski said.

Commit to rigorous testing 鈥� Extensive stress-testing in development and Q&A environments must precede any production deployment. Palm Beach’s implementation required weeks, if not months, of testing before going live 鈥� but that investment paid dividends in reliability and organizational confidence.

Design for transparency 鈥� Build workflows with built-in checks, balances, and fail-safes. Establish comprehensive logging that tracks what the AI agent does, what permissions it has, and what decisions it makes at each step. Monitor continuously for behavioral drift.

Maintain human oversight 鈥�”Trust but verify,” Chokski noted. Agentic AI is powerful and here to stay; but so are human professionals, and they must always retain oversight, the ability to intervene, and ultimate accountability for outcomes.

The conversation continues

The choice legal organizations face today is not whether agentic AI will exist, but how to engage with it responsibly.

Organizations that approach agentic AI with intentionality, clear frameworks, and commitment to human judgment will unlock its potential to expand capability, improve efficiency, and free legal professionals to do work that requires their expertise and accountability. Those that rush forward without guardrails risk silent failures that could undermine trust in both the technology and in the overall institution.

The path forward demands partnership: AI handles scale and speed, while humans provide judgment, accountability, and ethical reasoning. When those work two parts work together intentionally and with clear guardrails, that’s where justice is served.

For more on the impact of AI in courts, visit the听

• • • The real gap in AI transformation is between tools and strategy 鈥� Many law firms mistake owning AI tools for having an AI strategy, measuring success through usage data alone rather that measuring the created value for clients and the firm.

    • 鈥淐hange agility鈥� is operationally required 鈥� Because AI reinvents itself every few months, firms must embed continuous learning as a standard operating reflex rather than a one-time training event.

    • There are 5 key markers that denote true transformation 鈥� Firms pulling ahead share five consistent traits that compound into a durable competitive advantage.

Organizations with a visible AI strategy are 3.5-times more likely to experience critical AI benefits compared to those without one, and almost twice as likely to be experiencing revenue growth because of their AI investment, according to recent 成人VR视频 research.

For law firms 鈥� organizations in which the human dynamics of transformation are particularly complex 鈥� new details are emerging that separate those firms that are executing AI transformation well from those firms that are not, say two practitioners that work on law firm AI transformation every day 鈥� , Principal Consultant of AI Strategy and Transformation Services at 成人VR视频; and , an organizational and process transformation specialist on the same team. Together these two help firms move from adopting AI tools to rethinking how their legal work gets executed and delivered.

Both have said they鈥檝e observed that the firms pulling ahead are those that have put their lawyers at the center of the firm鈥檚 transformation strategies.

The gap between activity and accomplishment

Many law firm lawyers who are serious about their AI strategies have attended AI webinars, learned the vocabulary, and can readily name the leading tools in their practice area. Going one layer deeper, however, begs a key question on whether those tools have changed how those lawyers work and deliver value to clients.

Snavely says he sees this disconnect often, especially as firms can confuse having AI tools with having an AI strategy. In fact, many firms measure the effectiveness of their AI strategies with usage data, but Snavely and Lein argue that only focusing on usage does not give a full picture. Rather, they say that the key to effective AI transformation is driving measurable value for clients and the firm. 鈥淎wareness and simple use are not a strategy,鈥� Snavely notes. 鈥淭he real question is whether lawyers have actually changed how they work and the benefits that brings to the firms and its clients.鈥�

Since AI is always evolving, law firms need to alter their cultural paradigms to better prioritize a proactive mindset that treats constant technological change as a standard operating environment rather than a temporary disruption 鈥� a concept known as 鈥渃hange agility.鈥�

Lein underscores the challenge by pointing out that the technology-first mindset is getting the order of operations backwards. When firms lead with the tool rather than the lawyer’s problem, they are asking people to change their entire workflow for a solution that does not yet feel worth the investment of time and mental bandwidth to change.

鈥淲hen you lead with the tool, you are asking lawyers to change their process or approach to the work for something that has not yet proven its value,鈥� Lein says. 鈥淪tart with the problem, then the right technology becomes obvious.鈥�

To address this challenge, Snavely and Lein recommend that law firm leaders do the harder work of mapping lawyer problems to AI capabilities and identifying those professionals who can bridge that gap before investing broadly in AI adoption. Simultaneously, they should also focus on opportunities that AI can unlock for clients that were not previously possible.

What ‘change agility’ looks like

Since AI is always evolving, law firms need to alter their cultural paradigms to better prioritize a proactive mindset that treats constant technological change as a standard operating environment rather than a temporary disruption 鈥� a concept known as 鈥�change agility,鈥� Snavely explains.

鈥淐hange agility is not a skill you train once,鈥� he adds. 鈥淚t鈥檚 a strategic reflex you build into the organization 鈥� change agility means continuous learning is baked in, not bolted on.鈥�

Lawyers are being asked to keep up with a technology that reinvents itself every few months; and without careful prioritization, firms will see their professionals burn out from the noise of the technology changing.

At the same time, the pair acknowledge that constant change is exhausting. Lein flags a particular fatigue risk that leaders often underestimate. With prior technology cycles, there was a stabilization window in which people could absorb, adapt, and refine 鈥� however, this does not exist with AI tools.

Lawyers are being asked to keep up with a technology that reinvents itself every few months; and without careful prioritization, firms will see their professionals burn out from the noise of the technology changing.

Emerging indicators that some firms are succeeding

To strike the balance, both experts agree that a key part of the solution to better AI transformation within a law firm is clarity of direction. People can tolerate a great deal of ambiguity if they understand where the firm is heading and what their role is in getting there. Firm leaders who communicate a clear AI strategy 鈥� one that is connected to the firm’s overall direction and not just bolted on 鈥� give their people something on which to orient themselves amid constantly changing dynamics.

Further, Snavely and Lein identify five markers that consistently distinguish those law firms making progress from those generating activity without resulting AI transformation. These five markers include:

1. Fostering an acceptance of failure 鈥� Firms that have normalized rapid experimentation 鈥� trying, adjusting, and moving forward 鈥� without the expectation of getting it right the first time are outpacing those that still operate under the assumption that AI adoption will occur solely through webinars and one-time training events.

2. Developing consistent storytelling as a key tactic in communications 鈥� In the highest performing firms that Snavely has assessed, the same client success stories circulate repeatedly and consistently across interviews with different lawyers. These firms treat these success stories as cultural infrastructure, repeating them until they become part of the firm鈥檚 shared identity.

3. Establishing role clarity 鈥� Lein observes a meaningful difference between firms that formally incorporate AI into job descriptions and those that have left it as an informal add-on. 鈥淓nsuring AI is a clear part of a lawyer鈥檚 role is a meaningful job satisfaction signal and a leading indicator of adoption depth.

4. Aligning performance incentives with AI experimentation 鈥� Most law firms are still in early thinking mode on compensation structure alignment, but those firms with incentive frameworks that reward AI-driven value creation with new service offerings, recovered time that can be redirected to higher-value work, and measurable client outcomes, will more effectively reinforce the behaviors that drive transformation.

5. Defining what 鈥済ood鈥� looks like at the work-product level 鈥� Firms that define explicit standards for quality and build those standards into how AI output is supervised and evaluated will position themselves better over the next few years than those that leave expectations undefined.

Lein frames all these markers as both a cultural and a structural imperative because AI can amplify existing organizational behavior 鈥� both productive and dysfunctional 鈥� within a firm. 鈥淎I is an accelerator of work, but it is also an exacerbator of bad cultural issues,鈥� he explains.

Together, these five signals can complement each other and more importantly, compound into a durable competitive advantage for those law firms that act upon them.

You can find out more about the challenges of AI in the legal industry here

Key takeaways:

• • • Understanding is not preparation 鈥� Most EU businesses are aware of 鈥� but not necessarily prepared for 鈥� the sweeping changes that ViDA is bringing.

    • Few businesses have a solid transition plan in place 鈥� Only 22% of tax and finance professionals surveyed say their organization has a formal, funded ViDA transition program in place.

    • Some key requirements are already changing 鈥� With e-invoice and real-time reporting requirements already shifting, businesses are in danger of falling behind, risking business continuity and non-compliance.

The European Union鈥檚 reforms around its value added tax (VAT) 鈥� known as VAT in the Digital Age (ViDA) 鈥� represent the most significant shift in tax compliance for businesses operating in the EU in a generation. ViDA is more than merely another new compliance requirement or technology upgrade. Indeed, many organizations will need to modernize their entire invoicing and tax reporting systems to get into compliance.

Jump to 鈫�

The new compliance horizon: 2026 ViDA Readiness Report

While ViDA鈥檚 EU-wide mandates for cross-border e-invoicing and digital reporting take effect in 2030, the pressure on organizations is already mounting as individual EU member states roll out a patchwork of national requirements.

Digging deeper on this, a new report from the 成人VR视频 Institute, , reveals a striking paradox in how EU tax and finance professionals are preparing for this overhaul. While awareness is nearly universal, a significant gap remains between awareness of ViDA and tax teams鈥� readiness for its changes.

Indeed, 86% of EU tax and finance professionals say they are familiar with ViDA; however, a deeper look reveals that only 35% possess a detailed understanding of the specific requirements of the regulatory reform package. This creates a state of “comfortable uncertainty,” in which high initial confidence can often mask a lack of preparation for the massive technological and operational changes ahead.

Riding the 鈥淐onfidence Curve鈥�

One of the most compelling findings from the report is the “Confidence Curve” that shows how many organizations often start their journey with high levels of optimism. In fact, even among respondents who say their organization does not yet have a transition program in place or has one that is fragmented across EU member states, 90% say they feel confident in their organization鈥檚 ability to achieve ViDA compliance.

However, the Confidence Curve shows that confidence often regresses during the assessment and planning phase. As teams begin to uncover the complexities of new multi-jurisdictional compliance and real-time reporting requirements, the percentage of respondents who say they are “not very confident” doubles. It is only after a program is funded and embedded into digital transformation strategies that confidence strongly rebounds.

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Despite the high stakes, the majority of organizations are still finding their footing, the report shows. Unfortunately, more than three-quarters (78%) of respondents say their organization has no formal, funded ViDA transition program with central governance in place, meaning that they鈥檙e working in a fragmented country-by-country fashion or are still in the assessment stage.

These delays are risky Many EU member states have already begun rolling out e-invoicing mandates. That leaves those organizations without programs in place at greater risk of falling further behind.

The ViDA-enabled opportunity

Despite the massive changes in VAT requirements that ViDA brings, the reform package also offers corporate tax functions a tremendous opportunity to elevate themselves from a cost center to a strategic business partner. As the report outlines, taking that path forward requires a cross-functional commitment across numerous corporate functions, including tax, finance, IT, and legal departments.

Yet, those organizations that move beyond providing the “minimum viable compliance” and instead take the opportunity to invest in standardized data and central governance will be better positioned to turn these regulatory mandates into a compliance advantage for the tax function and a competitive advantage for the organization going forward.

You can download

a full copy of the 成人VR视频 Institute’s 听here

Key insights:

• • • UK law firms face a more selective growth market in 2026听鈥� Client demand remains steady, but external legal spend expectations have cooled, with growth concentrated in areas such as Regulatory, Labor & Employment, and international work.

    • Legal expertise alone is no longer enough 鈥� UK legal buyers increasingly favor law firms that combine technical excellence with commercial judgment, business understanding, and practical guidance aligned to client priorities.

    • AI adoption is becoming a client expectation听鈥� Corporate legal teams are moving faster than their outside law firms on GenAI, and many UK legal buyers now expect outside counsel to use AI to improve efficiency, workflows, and the quality of legal work.

The legal market in the United Kingdom today has shifted into a new normal. While law firms saw an explosion of demand and spending immediately following the pandemic, increasing client caution has resulted in a shift in priorities. Today鈥檚 law firms cannot simply rely on their old ways of providing legal service to succeed, as UK clients expect firms to combine expertise, commercial judgment, international reach, and visible AI-enabled improvements in how legal work is delivered.

Jump to 鈫�

2026 State of the UK Legal Market

A new report from the 成人VR视频 Institute, “2026 State of the UK Legal Market,” reveals how the UK legal market is shifting, as more judicious clients are beginning to force law firms to reassess their strategy. Overall anticipated net spend from legal clients has seen declining growth rates in recent years, and while some practices like Regulatory and Labor & Employment continue to see strong demand growth, other practice areas such as Insurance, IP, and Disputes face potential contraction.

This shift is also guided by emerging buyer preferences. The report reveals an increasing commerciality to the UK legal market, one in which clients increasingly favor advisors that combine legal excellence with commercial judgement, and those that are leveraging AI to bolster not only efficiency but improve the overall legal work product.

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Taken as a whole, the report paints a picture of clients that now are moving faster than their outside legal advisors, strengthening their internal capabilities, and setting clearer (and higher) expectations. This means that UK law firms cannot rest on their laurels, as clients increasingly push their outside firms to keep up with new business challenges.

The market is cautious, but opportunity remains

The report reveals that UK legal buyers are more cautious about external legal spend than they have been at any point in the last five years. That may mean law firms can no longer rely on the broad-based demand that defined the post-pandemic period and instead need to be more precise about where opportunity exists 鈥� and where it doesn鈥檛.

The report tracks buyer sentiment through net spend anticipation (NSA), which measures the share of buyers expecting to increase external legal spend over the next 12 months minus those expecting to decrease it. Since its 2021 peak, UK NSA has fallen steadily to +5 percentage points in 2025, returning the market to the more stable, single-digit baseline that was seen before the pandemic.

For those law firms looking to capture increased business, the report makes clear that legal expertise is now the price of entry, not the point of differentiation. The firms that stand out will be those that know how to apply their expertise in ways that reflect the client’s business realities.

Indeed, that is becoming even more important as corporate legal departments face growing pressure to demonstrate their own value to the wider organization, and they鈥檙e increasingly pointing to improvements in their own quality and effectiveness even before mentioning cost savings, efficiency, or time savings. Not surprisingly, more than one-third of UK legal buyers now cite business savviness as a reason they favor a particular law firm.

To help demonstrate their internal value, clients are pushing their outside law firms to leverage advanced technology to improve the overall effectiveness of legal work. Of course, this has resulted in a clear gap, the report notes, between how corporate legal teams are moving and how law firms are responding. For instance, the report shows that more than half of UK corporate legal respondents say their organizations are already using GenAI tools across the business, compared with just about one-third law firm respondents who said this.

That difference in outlook matters because clients increasingly believe AI will become a larger part of how legal work is delivered, and they鈥檙e not content to simply wait and see whether their outside counsel will fully adopt the technology. Indeed, corporate legal departments are expecting their outside law firms to keep pace with how legal work is changing, and they will reward those firms that do.

You can download

a full copy of the 成人VR视频 Institute’s “2026 State of the UK Legal Market” by filling out the form below:

Key points:

• • • AI capability is jagged 鈥� Ethan Mollick’s frontier metaphor describes a coastline of strengths and weaknesses, in which a model that excels at contract analysis can fabricate a citation in the same conversation.

    • Human intelligence is jagged too 鈥� A century of psychology, from multiple intelligences to the Big Five, shows that each lawyer has their own coastline of strengths and weaknesses.

    • Person-AI fit is the next discipline 鈥� Firms that take this seriously will move from one-tool deployments to portfolios that match each lawyer to an AI partner whose jagged edges meet theirs.

Welcome back to The AI Law Professor. Last month, I examined how AI first drafts can blind us to other lines of reasoning and hijack our legal judgment. This month, I want to take up what determines whether an AI works for any given lawyer at all: Not which model is best, but which model is best for this lawyer, on this kind of work, at this point in their career

Professor and author gave us the metaphor that started this conversation 鈥� the jagged frontier of AI capability. Picture a coastline, irregular and unpredictable. On one side, the model is capable; on the other, it fails, sometimes catastrophically. The line itself does not run where you expect. Tasks that look hard turn out to be easy, and tasks that look easy turn out to be hard.

In terms of legal work, this means that a model that has just produced a useful contract analysis will confidently invent a citation. A model that has summarized a 90-page deposition with insight will fail at basic arithmetic. The capabilities of AI form a coastline, with bays and inlets and the occasional cliff. Mollick’s contribution was to give us a way to see this clearly. AI is not uniformly competent or uniformly incompetent 鈥� rather, it is jagged.

Humans are jagged too. Psychology has been telling us this for a century, although the message is uncomfortable enough that we keep flattening it back into a single number. The single-number version is IQ; yet the deeper issue with IQ is that it pretends intelligence is one-dimensional.

Developmental psychologist Howard Gardner’s , whatever its empirical limits, points us toward a more honest picture, one in which linguistic, logical-mathematical, spatial, musical, interpersonal, intrapersonal, and kinesthetic intelligences, are each largely independent. People are not equally strong across all these dimensions. So, it follows that a great trial lawyer and a great patent lawyer are drawing on different intelligences, and each could be lost in the other’s territory.

Human intelligence, like AI capability, is jagged, and each of us has an edge. The jaggedness is not a flaw to be smoothed; rather, it鈥檚 a feature of being a unique individual.

When two jagged edges meet

Place the two coastline maps 鈥� the human and the AI model 鈥� side by side. Press them together at random and they grind, with gaps where neither side fills the space and ridges where both claim the same territory. The lawyer’s strength overlaps with the AI model’s strength, so neither is amplified. The lawyer’s weakness overlaps with the model’s weakness, so neither is covered. The pair produces less than either party would produce alone.

However, align the same two surfaces with attention to their contours and something different happens. The peaks of one fit the valleys of the other. The lawyer’s weakness is met by the model’s strength; and the model’s weakness is met by the lawyer’s strength. The pair becomes more capable than either party alone.

A law firm that takes this seriously will not deploy a single AI tool across all of its lawyers and call the rollout complete. It will offer a portfolio of models and configurations and help each lawyer find the AI partner that works with their actual mind.

Every foundational model now ships with a model card, a document describing the model’s intended uses, training data, performance characteristics, and known limitations. The cards exist because models are not interchangeable. Read three of these cards side by side and the matching question becomes clear. A cautious generalist that hedges and flags uncertainty fits a lawyer who already holds strong views and wants a partner that will test them. A citation-anchored specialist that refuses to invent cases and stays grounded in retrieval fits a lawyer in heavily regulated practice areas in which errors are catastrophic.

The matchmaking discipline

Organizational psychology has worked on a version of this problem for 50 years under the . When a person’s strengths, values, and working style align with the demands and culture of their role, performance and well-being both rise. When they misalign, performance drops and burnout follows.

The same logic applies to person-AI fit. On the human side, cognitive style, domain expertise, personality profile, and the actual tasks performed in a typical week are key. On the AI side, behavior under different prompt styles, default tone, willingness to push back, hallucination patterns, and the shape of strengths and weaknesses across the practice areas in question may matter most. Yet, law firms are still treating AI procurement as a software decision rather than a partnership decision.

A law firm that takes this seriously will not deploy a single AI tool across all of its lawyers and call the rollout complete. It will offer a portfolio of models and configurations and help each lawyer find the AI partner that works with their actual mind. The first generation of legal AI has been dominated by the question of which model is best; however, the second generation will be dominated by a different question: Not which model, but which pairing works best. Not capability, but fit.

Those lawyers that flourish with AI will not necessarily be the most technical or the most enthusiastic users. Instead, they will be the ones that found, by luck or by design, an AI partner whose jagged edges meet theirs.

When two jagged intelligences fit well together, they can accomplish more than what either 鈥� human or AI 鈥� could do alone. Today, fit is the frontier.

Tom Martin is CEO & Founder of LawDroid, Adjunct Professor at Suffolk University Law School, and author of the forthcoming

听

Key insights:

• • • AI can improve officer safety听鈥� By helping them prepare for high-risk situations and make better decisions under pressure, advanced technology can enhance officer safety.

    • AI can increase operational efficiency听鈥� AI can reduce administrative burdens and improve efficiency overall, allowing officers to spend more time on police work.

    • Responsible implementation is essential听鈥� To ensure AI strengthens public trust while protecting civil liberties, proper guardrails and oversight need to be enacted.

Each year, during , we pause to honor the brave men and women in law enforcement who have made the ultimate sacrifice in service to their communities. As we pay tribute to those we have lost, we are reminded of the inherent dangers officers face every day.

In recognition of the importance of reflection and advancement, it is imperative that we examine the responsible application of emerging technologies, especially AI, to enhance officer safety, support their objectives, and reinforce overall public safety.

AI is already being integrated into public safety systems in meaningful, measurable ways. When guided by strong ethical principles, transparency, and commitment to community trust, AI can serve as a force multiplier and a protective partner for members of law enforcement. The goal is not to replace officers, of course, but to equip them with better tools, that allow them to reduce risk and return home safely after every shift.

Improving situational awareness and operational readiness

One of the most immediate benefits of AI in law enforcement is its ability to enhance situational awareness. When officers respond to a call, the first minutes on scene are often the most critical 鈥� and the most dangerous. AI can help reduce uncertainty by providing rapid access to relevant information.

For example, AI-powered systems can analyze incident data, criminal records, and community reports to give officers a clearer picture of what to expect when they arrive on scene. This includes identifying patterns of violence, recognizing repeat offenders, or flagging locations that may have a history of high-risk activity. Such insights allow for better preparation, smarter deployment, and more informed decision-making under pressure.

Additionally, AI can assist in public records and open-source searches, pulling critical data from comprehensive databases, the internet, and connected devices in seconds rather than hours. This immediate access to information enables faster, more effective responses. In short, AI can save valuable time when seconds count.

Streamlining administrative work to focus on the mission

Law enforcement officers spend a significant portion of their time on administrative duties, such as writing incident reports and managing court schedules and citations. These tasks, while necessary, take officers away from community engagement and proactive policing.

AI can help reduce this administrative burden by automating routine documentation. Natural language processing tools can draft reports based on officer input, ensuring consistency and freeing up time for frontline duties. Similarly, AI-driven scheduling systems can optimize shift assignments, account for court appearances, and manage on-call rotations. This AI-enabled administrative assistance goes a long way in ensuring that staffing levels are appropriate and that officers are not overburdened.

When guided by strong ethical principles, transparency, and commitment to community trust, AI can serve as a force multiplier and a protective partner for members of law enforcement.

By reducing the administrative load, AI allows officers to focus on what they do best 鈥� serving and protecting their communities. This not only improves job satisfaction among officers themselves but also increases operational efficiency and public safety outcomes.

Building guardrails for responsible AI use

As with any powerful advanced technology, the integration of AI into law enforcement must be guided by clear policies, oversight, and accountability. The goal is not to deploy AI indiscriminately, but rather to ensure its use enhances safety without compromising civil liberties or public trust.

This requires proactive collaboration between technologists, law enforcement agencies, policymakers, and the communities they serve. Standards must be developed for data privacy, algorithmic transparency, and bias mitigation. AI-enabled systems should undergo rigorous testing and independent review before deployment. Further, officers must be trained not only on how to use these tools, but also on the limitations and ethical implications of using these tools as well.

Finally, public trust is essential. Members of the community need to know that AI is being used to protect their safety and that of law enforcement 鈥� it is not a tool to surveil them without cause. Communicating transparently how the AI systems are designed, what data they use, and how decisions are made will be key to maintaining legitimacy and trust with the public.

A future of safer streets and stronger trust

The integration of AI into law enforcement is not about replacing human judgment 鈥� rather, it鈥檚 about augmenting officers鈥� judgment. When used responsibly, AI can reduce risk, improve preparedness, and support officers in carrying out their duties more safely and effectively.

In the years ahead, we can expect to see broader adoption of drone first responders, real-time language translation tools, and predictive systems that further help enhance officer and community safety measures. However, technology alone is not the answer. Success will depend on how thoughtfully these tools are implemented, how well citizens鈥� rights are safeguarded, and how deeply communities are involved in the process.

This week, as we honor those officers who have fallen in the line of duty, let us also commit to doing everything we can to protect those who serve today. AI, when applied with care, can be a powerful ally in their mission, keeping officers safe, allowing them to make better decisions, and together, building stronger, safer communities for all.

The data provided to you may not be used as a factor in establishing a consumer鈥檚 eligibility for credit, insurance, employment, or for any other purpose authorized under the Fair Credit Reporting Act.

You can find more on the challenges facing law enforcement here

Key insights:

• • • Real-time tax compliance has restructured the tax function 鈥� Dozens of nations now require structured invoice data in real time, with the EU mandating cross-border digital reporting by 2030. The traditional file-and-wait audit cycle is gone now, replaced by clearance regimes that can freeze multi-million-dollar invoices for nonconforming data.

    • Regulators have pulled ahead of the businesses they oversee 鈥� Tax authorities in mature CTC jurisdictions now arrive at audits with structured transaction data already processed by their own analytics. Government turnaround times that took months now take weeks, forcing multinational tax leaders to compress multi-year roadmaps into 12- and 18-month cycles to keep up.

    • The lessons travel beyond tax 鈥� There are two ways to lose this race: Outrun your own controls or surrender entirely. Both showed up in Las Vegas, and both will show up in every other regulated profession over the next decade.

LAS VEGAS 鈥� The听 sold out. A guest list that included tax directors from Amazon, Walmart, and Procter & Gamble, OpenAI’s tax department, the Big Four, 成人VR视频 and every other major tax software provider in the market spent three days at the Aria with pool deck, casino floor, and restaurants worth lingering over all a few steps away.

The room had every reason to spend its evenings somewhere else other than a sunless conference room talking about tax. Yet almost no one did. They were too busy grappling with an arms race the corporate audit side had begun to suspect it was losing.

And it鈥檚 one they cannot afford to lose.

End of the traditional model

The arms race is real-time tax compliance, and it has dramatically restructured the ground beneath the tax profession in less than a decade. By April, more than 60 jurisdictions have moved or are moving to continuous transaction controls. Italy and Hungary were early; Poland, France, Belgium, Brazil, Saudi Arabia, India, and Singapore are now operational or imminent, and countries like Spain, Germany, the United Kingdom and the United Arab Emirates are on the way. The European Union has locked onto a 2030 deadline for cross-border real-time digital reporting and a 2035 backstop for harmonizing what’s left.

The traditional model 鈥� issue an invoice, file a return weeks later, audit when the auditor gets around to it 鈥� no longer exists in those jurisdictions. Tax authorities now see the transaction as it happens, validates it in structured form, and pre-fills the return on the taxpayer’s behalf.

What this new process has done to the tax function is fundamentally alter its structure in a way leaves practitioners reeling. The job used to be a craft of Excel, judgment, and institutional memory. Now, at the high end, it has become as much a data science problem as an accounting one.

The arms race is real-time tax compliance, and it has dramatically restructured the ground beneath the tax profession in less than a decade.

Attendees at TEI鈥檚 2026 Tax Technology Seminar polled themselves on tooling, and the answers came back as a list of data pipelines that dozens of attendees seemed to favor: Alteryx, Power Platform, Snowflake, Databricks, Microsoft Fabric, & Palantir Foundry. These platforms are running agentic AI systems against historical filings, deploying validation agents to critique their own outputs, and using AI-driven image-to-text solutions to pull structured data out of state tax notices that never arrive in the same format twice. They are data integration pipelines in 15 minutes that would have sat in an IT queue for two months before being answered.

They have little choice as the stakes are far higher and the challenges far more demanding than they used to be. In a clearance regime, an invoice has no legal force until the tax authority returns its identifier. Did you submit the wrong VAT ID, malformed schema, or mismatched master data? Congratulations! Your invoice is rejected. That means the truck doesn’t move, the buyer doesn’t pay an invoice that may be in the millions of dollars and then the penalties stack on top. Italy, for instance, charges a fee of 70% of the disputed VAT.

And then there are the audits.

Outgunned

The audit isn’t an occasional event anymore. In government jurisdictions with mature continuous-transaction-control tax regimes, it is a conversation that started weeks before the auditor walked in, on data their analytics had already processed.

A speaker on a seminar panel led by Deloitte and 成人VR视频 described the dynamic plainly: Tax authorities in those jurisdictions have arrived at audits already knowing more about the transactions than the companies and their in-house audit teams sitting across the table. Not because anyone is hiding anything, but because the data arrived at the tax authority in structured form, in real time, and the authority had run its analytics on it before the meeting was even on the calendar. One panelist said this represents “a shift from us preparing returns to us answering notices on the data that’s been shared.”

What the room kept circling around, however, was that regulators have not just kept pace with their counterparties, they鈥檝e now pulled ahead. Singapore, one panelist noted, is doing more with AI than even major companies. Indeed, government turnaround times that used to take months are now closing in weeks, which is forcing multinational tax leaders to compress their multi-year roadmaps into 12- and 18-month cycles 鈥� not because they want to but because their counterparties already had.

The lesson that corporate tax functions have been forced to absorb is that there are two ways to lose this race, and both were on display at TEI鈥檚 2026 Tax Technology Seminar as cautionary tales.

This asymmetry is structural, and that is what makes it an arms race rather than a transition. There is no version of this dynamic in which the company being audited wins by being more careful, more thorough, or more well-prepared at the end of the quarter. The advantage now accrues to the side with the fastest and cleanest pipelines, that runs the smartest AI, and that understands the way these increasingly complex systems interact. Increasingly, that winning side is the government. And, more alarming, this isn鈥檛 just a problem for this particular industry 鈥� tax just happened to get here first. However, it鈥檚 coming for everyone.

Two ways to lose

The lesson that corporate tax functions have been forced to absorb is that there are two ways to lose this race, and both were on display at TEI鈥檚 2026 Tax Technology Seminar as cautionary tales. The first is to outrun your own controls. AI coding tools that let a tax analyst build a working data integration pipeline in 15 minutes are genuinely valuable; they also let that same analyst deploy something nobody else has reviewed, documented, or knows how to maintain. An OpenAI panelist conceded the point when an audience member asked about the security implications of vibe coding 鈥� clearly, a new capability is also a new problem.

The second way to lose is harder to talk about. One panelist described, to attendees鈥� general dismay, hearing of companies that have given up on compliance entirely 鈥� instead, they pad their numbers with a safety margin and treat the eventual audit as the cheaper of the two costs. The panel recoiled 鈥� one member responded with a flat “Do not do this.” However, the anecdote landed because it isn’t theoretical. When the gap between what regulators can see and what your team can produce becomes wide enough, surrender starts to look rational.

Playing to win

Of course, the attendees at TEI鈥檚 2026 Tax Technology Seminar were not surrendering. If they were, they’d have been at the pool deep into their third cocktail. Or they’d have been on the casino floor or were about to catch an afternoon show. Instead, day after day, the tables filled, the exhibit hall ran hot, and the room was buying, listening, and building.

The game has changed and the stakes have risen 鈥� and the room is dead set on playing to win.

You can find more of听our coverage of Tax Executives Institute events here