The pattern repeats across all three, though. Adoption has outrun governance. Client and stakeholder expectations have outrun delivery. The organizations pulling ahead aren’t the ones talking about AI, they’re the ones putting it to work. As Raghu Ramanathan, President of Legal Professionals at ³ÉÈËVRÊÓƵ, puts it: “The firms creating a true competitive advantage today are not the ones talking about AI. They’re the ones operationalizing it.”

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Law firms: clients stopped waiting a while ago

Law firm leaders are caught between two forces moving at once. Clients want proof, not promises: 77% say AI-enabled quality improvements from their firms matter enormously, but only 5% say they’re actually seeing them. Seven in ten in-house legal professionals expect firms to change how they charge as AI use grows. Only 28% of firms have changed their pricing at all.

Talent is watching the same gap. Nearly a quarter of law firm professionals would turn down a job offer that didn’t include real access to professional-grade AI, and when a lawyer’s own view of AI clashes with their firm’s actual direction, they become nearly three times more likely to leave within the year.

There’s also a liability many firms haven’t priced in yet: a third of law firm professionals are using AI tools their firm never approved, often on matters involving privileged, sensitive client information. The firm carries that exposure whether it chose to or not.

What should law firm leaders do? Two moves matter most.

1. Train lawyers to lead the AI conversation with clients themselves, in plain language, grounded in real matters, honest about where the firm is still figuring things out.
2. Open the pricing and value conversation early rather than waiting for clients to force it.

The industry has already moved past “should we use AI?” The real question now is “can we afford not to?” The action report for law firm leaders walks through how firms are already answering it.

Law firms under pressure

Practical actions law firms can take to remain competitive

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Corporate leaders: this is a leadership problem, not a licensing one

For corporate leaders, Liz Zimick, President of Corporates at ³ÉÈËVRÊÓƵ, names the challenge without softening it: “Taken together, these findings point to a change management and leadership challenge that no software license alone will solve.”

Well over half of corporate professionals feel real stakeholder pressure to move faster on AI, and 15% are already seeing financial consequences from moving too slowly, with another 29% expecting them within the year. 59% lack access to tools built to the accuracy standard their fiduciary work demands, so more than a third fill that gap with AI their organization can’t see or govern.

What should corporate leaders do?

1. Stop waiting for direction to arrive from the C-suite. Audit where your people are already using AI, formally or otherwise, and where real demand goes unmet.
2. Plan for every stage of the journey at once, since most departments start by scaling capacity and only later discover they need to rebuild the underlying workflow to reach something better.
3. Lead the AI governance conversation across the enterprise rather than simply joining it.

General counsel, in particular, are well positioned to define what responsible AI use means for the whole organization, not just their own function. The action report for corporate leaders breaks down where to start.

How corporate functions are responding

Strategic paths leaders can take to prepare for the future

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Tax and audit firms: talent already sees where this is going

Elizabeth Beastrom, President of Tax, Audit & Accounting Professionals at ³ÉÈËVRÊÓƵ, frames the stakes around a single insight: “Accounting and audit firm employees increasingly see professional-grade AI tools as a non-negotiable part of their jobs.”

Eight in ten tax and audit professionals now use AI several times a week, yet more than a third are doing it with tools their firm never sanctioned. Clients are watching just as closely: 89% say AI-enabled quality improvements matter enormously, and nearly a third of professionals believe their firm risks losing clients within the year if it can’t keep pace.

What should tax and audit leaders do? Four priorities scale from a two-person practice to a national firm.

1. Govern the tools your people already use instead of pretending they don’t; approving one professional-grade AI tool built on verified content changes your risk profile far more than a policy with no tooling behind it.
2. Know your direction even while the path evolves and decide early whether freed-up time should fund growth, work-life balance, or higher-value advisory work, because chasing all three at once dilutes each.
3. Ask your people honestly what they want AI to change about their work, then build your deployment, and your recruiting pitch, around the real answer.
4. Decide now what work your early-career professionals still need to do by hand, before AI quietly removes the chance to teach it.

The action report for tax & audit firm leaders goes deeper on each of these four moves.

Explore key findings

Four calculated moves for tax & audit firms

Read the report

Choose your path. Don’t drift into one.

Across law, corporate, and tax alike, the organizations getting real value from AI share one thing in common: they named a direction instead of waiting for one to emerge. The biggest gaps were never really technical, they were organizational: the right tools not yet in place, people never trained to work the new way, a strategy that never made it past the leadership deck. Closing that AI value gap takes leadership, not procurement.

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As ³ÉÈËVRÊÓƵ President and CEO Steve Hasker writes in the report’s foreword,

Read that twice, because it’s the sentence that explains almost everything else in this year’s findings.

Everyone’s using it. Not everyone has what they need.

Here’s what makes this moment strange: 74% of professionals now use AI several times a week, and nearly half turn to it multiple times a day. By any normal measure, that’s a technology success story.

But look closer and the picture shifts. 41% of professionals who use AI at work still don’t have access to tools built for the standards their profession actually demands, tools that protect confidential data, ground their answers in authoritative content, and show their reasoning clearly enough to defend it. So people do what motivated professionals always do when the tools they’re given fall short: they find their own. More than a third now use AI their organization hasn’t approved or can’t see, quietly building risk no one is tracking.

Clients feel this gap too. Nearly 78% corporate buyers of professional services say AI-enabled quality improvements matter enormously to them. Just 6% say they’re getting that from most of the firms they hire. Almost a third are already reconsidering those relationships, and among the ones walking, a third estimate more than $1 million in annual work is on the line.

Talent is walking too, for the same reason. 91% of professionals feel some degree of AI value gap between what they expect AI to deliver and what they’re actually getting at work. One in four of them is already planning to leave within two years, and replacing them costs an estimated $232,000 each. The people driving the most change in how their work gets done, the changemakers inside every firm and department, are also the ones with the most options elsewhere.

Three futures, and every organization is already choosing one

Here’s the part of the report we find most useful for leaders: whether your organization has thought about it deliberately or not, you’re already answering one question through your actions: what is AI really for?

The data shows three distinct answers taking shape:

Some organizations are choosing AI to Elevate, putting human expertise at the center and using AI to clear away routine work so people can spend more time on judgment, strategy, and relationships. It’s the answer most professionals want for themselves, chosen by 52% as their preferred future.

Others are pursuing AI to Scale, treating AI mainly as a capacity solution: more volume, faster turnaround, steadier quality, without growing headcount at the same rate. Roughly a third of professionals see this as their path.

A smaller group is going further still with AI to Reimagine, rebuilding how they operate and what they offer clients around capabilities that didn’t exist before, rather than optimizing what’s already there. Only 7% describe this as their current reality, but they’re also the most ambitious professionals in the survey, and the least patient with organizations still moving at the old pace.

None of these paths is wrong. What the data does make clear is that choosing one on purpose, and following through, beats drifting into one by accident. Where organizations have named an AI strategy, 66% of professionals say AI is meeting or beating expectations for creating value. Where there’s no active strategy at all, that number drops to 22%.

Why the strategy on paper never seems to reach the desk

This is where so many organizations lose the thread. 35% of professionals whose organization has a named AI strategy say they don’t truly see it in their day-to-day work. The strategy exists. It just hasn’t traveled.

Professionals point to the same handful of reasons, again and again. Nearly half say the right tools simply aren’t in place yet. 43% say they were never trained to work the way the strategy assumes, no one taught them when to trust AI’s output, when to double-check it, and when to override it entirely. 32% say the strategy never got translated into anything concrete enough to act on. And nearly a third say there’s no shared understanding of the plan across the organization at all, different teams are quietly working from different assumptions about where things are headed.

The choice in front of every professional

What comes through most clearly across all 1,816 responses is that this moment rewards the organizations willing to choose deliberately and build toward that choice with discipline, rather than wait for the perfect strategy to arrive fully formed. As Hasker puts it, “AI is a powerful force multiplier, but the judgment, relationships and accountability remain human, and that won’t change.”

That’s the real dividing line in this year’s data, not who has access to AI, but who decides on purpose what to do with it. The professionals and organizations pulling ahead aren’t waiting for someone else to hand them a strategy. They’re changemakers, whether or not they’d use the word, and they’re exactly who we build for.

Read the full to see where your organization stands, and where your biggest opportunity is hiding.

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AI has split into systems built for casual use and systems built to be trusted with consequences, and the two look almost nothing alike under the hood. The chat-window version answers one question at a time, drawing on whatever it absorbed from the open internet. Newer is a system that plans across multiple steps: pulling the current version of a regulation, drafting against it, checking its own citations, and flagging where a person needs to step in — one connected process, not a single reply. That’s agentic AI: the difference between a tool that finishes a task and one that finishes the work.

Adoption has outrun trust. Per the , 74% now use AI several times a week and 44% multiple times a day — yet 91% feel some degree of AI value gap between what they expected and what they’re getting. That’s not the technology failing; it’s a sign much of what’s in daily use was built for a lighter job than it’s now handling. 41% lack access to AI built specifically for professional work on verified content, and 34% admit to using unsanctioned AI tools their organization can’t see.

Which kind of AI is actually in your hands?

The interface often looks identical regardless of what’s underneath. But a system trained on the open web and one grounded in validated, domain-specific authority behave very differently the first time something genuinely matters — a filing, a clause, an opinion a client acts on. The tell isn’t confidence; both sound confident. It’s what happens when you ask how do you know: whether the system points to a checkable source or just restates the answer more firmly.

That’s the line ³ÉÈËVRÊÓƵ draws across today’s market: general-purpose assistants trained on the open web, productivity copilots built into office software, domain wrappers layered on general models, and Fiduciary-Grade AI, grounded in authoritative content and built for outputs a professional can trace, verify, and defend. Only the last was built for work where almost right isn’t good enough.

Why ³ÉÈËVRÊÓƵ built a new standard

Legal decisions, financial filings, tax positions, and audit findings carry accountability that can’t be shared with an algorithm. ³ÉÈËVRÊÓƵ formalized the standard it believes AI must meet to be trusted with that work: Fiduciary-Grade AI.

The report also shows professionals agree almost unanimously on what they need: 96% say AI must safeguard confidential data, 94% say it must ground outputs in authority, 90% say it must produce defensible reasoning. And 47% say final responsibility for an AI-assisted error lands on the professional themselves, not the vendor or the model — an instinct that only holds up when the tools they’re given can back it up.

In practice, the standard comes down to where a system’s answers originate. A Fiduciary-Grade system traces every material output to a verifiable source, carries the full context of a matter, and builds privacy and security into its architecture rather than layering it on. It’s shaped by credentialed experts from the outset, built to recognize the edge of its own knowledge, and leaves a trail a professional, regulator, or court could review.

The cost of getting the category wrong

The AI value gap has a price tag. Nearly a quarter of professionals experiencing it are considering leaving within two years, at an estimated $232,000 replacement cost each. On the client side, 78% of corporate clients say AI-enabled quality is essential, yet just 6% say most providers deliver it, and 32% are already reconsidering firm relationships over it. It’s a talent signal too: 32% using Fiduciary-Grade AI would turn down a role without it, versus 12% of those without access.

The pattern is consistent: professionals use AI constantly, clients expect it, and a large share of both feel let down. That’s rarely AI failing outright — it’s the wrong category doing a job it wasn’t built for. A tax filing citing an outdated regulation, a contract clause built on the wrong jurisdiction’s case law, an audit finding grounded in a superseded standard: in each case, the professional who signed off, not the AI, bears the consequence.

The question worth asking about the AI you already use

You don’t need a new framework to see the difference — just ask where the AI in front of you gets its answers. If it can’t point to a checkable source, if nobody can say which experts shaped it versus reviewed it after the fact, if you don’t know what happens to your data when the vendor swaps in a new model underneath — you’re looking at a tool built for a lighter job than the one you’ve handed it.

That’s the gap Fiduciary-Grade AI was built to close: not a faster assistant, but a different category of technology, grounded in authority, accountable for its reasoning, and honest about what it doesn’t know.

Fiduciary-Grade AI

What it is, why it matters, and how to buy it

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