Highlights

Throughout my career, one belief has remained constant: technology should make professional work better, not just faster. That belief shapes how I think about the future of legal, tax, risk, and compliance teams and the role technology should play in helping them succeed. So when people ask me what it means as 成人VR视频 accelerates its transformation through technology, my answer comes from what I see in my own business every day.

Corporate legal, tax, risk, and compliance teams keep organizations moving safely through complexity. They don’t get to be “almost right.” A missed clause, misapplied regulation, an unverified answer 鈥� all carry real consequences for the businesses they serve. When I look at who’s leading through that pressure well, I see the same pattern we celebrate in our Chosen by changemakers stories: people who decide to work differently before they’re forced to.听 We’re not just digitizing old workflows. We’re rebuilding the tools these teams rely on to meet a standard worthy of the responsibility they carry.

The Future of Professionals Report 2026 found that 96% of professionals say AI must safeguard confidential data, 94% say its outputs must be grounded in authoritative content, and 90% say it must produce reasoning that can be explained and defended. Yet the gap between expectation and delivery is stark: 78% of corporate clients say receiving AI-enabled quality improvements from their providers is very important or essential, but only 6% say most or all of their providers actually deliver.

That’s the thinking behind what we call Fiduciary-Grade AI: AI built for professionals who operate under real duties of care, not just general productivity gains. It means:

• Authority you can verify: outputs grounded in trusted, domain-specific content, not the open internet.

• Transparent reasoning: the professional can examine and defend the answer.

• Accountability that stays human: responsibility never shifts to the tool; it exists to support judgment, not replace it.

I care about this distinction because I’ve sat across the table from corporate customers who don’t need another AI demo. They need something they can trust with work that matters.

‘s legal team is a good example of what this looks like in practice. Their privacy impact assessments connect directly to the private health data of real patients, so speed can never come at the cost of rigor. Using , they’ve reduced the review process by roughly 60%, cutting what once took five days down to two. Proof that moving faster and moving carefully aren’t in conflict when the technology is built for the responsibility the work carries. It’s an example of how trustworthy AI can help professionals move faster while maintaining the standards their work demands.

That鈥檚 the changemakers story听that matters to me: the general counsel redesigning how their department engages with the business, the tax leader moving from compliance to strategic planning, the compliance team building always-on risk intelligence instead of quarterly reviews. It鈥檚 not a technology story. It鈥檚 a leadership story, and it鈥檚 the one I want my team to write alongside our customers.

I don’t think the corporate function that emerges from this period will look like the one that entered it. Legal, tax, risk, and compliance leaders are redefining how their teams create value, influence strategy, and manage complexity. I want us to be part of shaping that change, not just reacting to it. Our role isn’t simply to provide technology. It’s to help those professionals meet a higher standard, with tools they can trust when the stakes are high.

That’s what Fiduciary-Grade AI听is about. And that’s why I believe the changemaker mindset isn’t a trend. It’s the bar.

The right technology can change everything

The best don't just do their work. They change what is possible.

See how

The post appeared first on .

Highlights

There’s a moment every legal professional knows. You’re deep in a document review 鈥� hundreds of contracts, thousands of clauses, a deadline closing in 鈥� and you ask an AI tool a question that shouldn’t be complicated. The answer comes back confident, well-written, and subtly wrong. Not wrong enough to catch on first read. Just wrong enough to matter.

That’s why we built Thomson. Not just because general models get the details wrong sometimes, but because owning the model outright changes what we can do about it.

成人VR视频 doesn’t just deploy AI. We build it.

Why general-purpose AI isn鈥檛 enough

The past few years have brought extraordinary AI advances. General-purpose large language models (LLM) can write code, summarize articles, and hold nuanced conversations. But legal and compliance professionals work in a different environment. Imprecision has consequences. A misread clause or a missed precedent isn’t an inconvenience; it’s a risk you can’t take.

So what separates a tool that’s merely useful from one you can stand behind?

Not all AI is built for the same stakes. At one end are general-purpose tools 鈥� broadly useful, but shallow on any one domain. A step further are professional-grade tools, built for a specific field, in environments where an occasional error is tolerable. And then there’s a third tier: Fiduciary-Grade AI, built for work where a small error doesn’t just cost time, it can mean a lost case or a client’s trust.

That’s the tier legal and compliance work lives in. It’s the tier Thomson was built for.

The decision to build our own

We’ve always been an expertise company. Grounded by 175 years of intelligence, we’ve combined proprietary data with domain knowledge to give professionals the intelligence they need for their most important work. Thomson is the next chapter of that mission.

Owning more of the AI stack gives us greater control over performance, economics, deployment, and sovereignty 鈥� how the model behaves, what it costs us to run, where it runs, and how our clients’ data is protected. Just as importantly, it lets us continuously improve Thomson using the content and expertise only 成人VR视频 has, rather than depending on what a third party chooses to build next.

That decision started in 2024, when we acquired Safe Sign Technologies, an AI research company founded by leading AI and legal minds. The result is a model that’s built on open-source foundations we can evolve as the AI landscape shifts, while the legal intelligence we put into Thomson only deepens over time. We’re not locked into any single foundational system 鈥� and we’re not standing still.

What we built

Thomson is our proprietary LLM, purpose-built by 成人VR视频 for high-stakes professional work. It was built on our proprietary content, including Westlaw and Practical Law, two of the most authoritative legal data sources in the world, and reflects input from our vast network of human legal experts.

Think of it as a “T-shaped” model. The horizontal bar is broad general capability 鈥� language understanding, reasoning, and the fundamentals any strong AI needs. The vertical column is what makes Thomson different: authoritative legal content and deep subject-matter expertise, refined by expert guidance, producing a level of legal comprehension optimized specifically for professional work. We built it to be both broad and deep.

Thomson and CoCounsel aren’t the same thing, and that’s by design. CoCounsel is the product 鈥� the agentic workspace, skills, and workflows legal professionals use every day. Thomson is one of the LLMs CoCounsel calls on.

What it’s already doing

Thomson’s first implementation just launched, powering CoCounsel Legal’s Tabular Analysis feature. You can extract structured answers from up to 10,000 documents across up to 100 questions you define 鈥� at a scale and consistency that used to be impossible without significant time and cost.

Powering the engine behind Tabular Analysis, Thomson gives you deeper comprehension of complex legal documents, more consistent extraction across question types, lower variance across large document sets, and verifiable, citation-grounded outputs your attorneys can review and rely on. These aren’t incremental improvements 鈥� the numbers show it. As of Q1 2026, CoCounsel has crossed one million users. The share of our business that’s Gen AI-enabled has doubled in a little over a year. Monthly CoCounsel SKUs in legal have quadrupled year-over-year. That’s not a pilot program. That’s a shift in how the work gets done.

Independent testers agree. A Washington University law professor pitted Thomson against ChatGPT and Claude using real questions from his own Corporate Tax class and preferred Thomson’s answers overall, pointing to its linked citations to treatises as especially useful. A separate review from Queen’s Conflict Analytics Lab and Cornell Legal AI Lab found Thomson’s citation quality held up against leading frontier models 鈥� even on Canadian employment-law questions the model wasn’t specifically tuned for.

We hold Thomson to the same standards you hold your own work to. It’s developed and deployed within enterprise-grade governance frameworks grounded in the principles of Fiduciary-Grade AI: transparency, traceability, verifiability, structured evaluation, and expert validation. Thomson is built for repeatable performance you can trust.

Built for the people who make change real

Speed is the easy part. Any AI tool can give you an answer fast. What you need is one you can stand behind 鈥� in front of a judge, a client, a board. That’s what we mean by Fiduciary-Grade AI: intelligence built to the standard your profession already holds itself to.

The legal professionals who rely on us every day aren’t passive consumers of information.

You’re the people who protect businesses from harm, hold institutions accountable, and shape the frameworks that govern how society works. You’re changemakers 鈥� and you deserve tools built with the same seriousness you bring to your work. don’t just need answers. You need answers you can defend.

You’re in good company: a million professionals like you have already chosen to trust 成人VR视频 with the work that can’t afford to be wrong.

We built Thomson for you. Not because AI is a trend worth chasing, but because the next phase of professional AI won’t be defined by general capability 鈥� it’ll be defined by domain mastery, measurable outcomes, and trust. That means higher-quality outputs and greater confidence when you’re using AI in the workflows that matter most.

You shouldn’t have to settle for AI built for everyone. Now you don鈥檛.

Thomson

The purpose-built, proprietary LLM, engineered for high stakes professional work

Learn more

The post appeared first on .

That is the lens through which my team and I approach everything we do. We are not observers of a transformation happening around us. We are changemakers, and we hold ourselves to that standard.

The question that actually matters

Our 2026 AI in Professional Services Report makes something clear: the window for AI experimentation has closed. Enterprise-wide AI usage nearly doubled across legal, tax, and corporate sectors in a single year. More than 80% of professionals using AI today do so at least weekly. And 87% expect it to be a central part of their workflow within five years. The early adopter advantage is gone. What remains is the question of who builds on the right foundation, and who doesn’t.

Almost every AI system today can help professionals move faster. The harder question, the one that actually matters in high-stakes legal work, is whether you can stand behind the answer. Speed is the easy part. Knowing you can stand behind the answer, that is what we are focused on.

The same report found that accuracy and reliability concerns remain the top reasons professionals hesitate to trust AI. That is not a technology problem. It is a trust problem. And trust, in legal work, is not abstract – a missed citation, an unsupported analysis, an output no court would recognize are not productivity losses. They are professional failures. In some cases, they are justice failures.

Not all AI is used in the same way, and it cannot be held to a single standard. This is especially true in industries with professional liability; AI must meet a higher bar than general productivity tools. Where outputs shape legal judgments, regulatory filings, or client advice, 鈥渁lmost right鈥� falls short. 成人VR视频 defines this higher bar as Fiduciary-Grade AI, the standard for how AI should perform in high-stakes professions, and the standard we build to.

What this looks like practice

CoCounsel Legal is that standard. Built on Anthropic’s Claude Agent SDK, it is a unified agentic platform that plans, retrieves authoritative content, and adapts mid-workflow 鈥� just as a senior associate would. It is built with Westlaw and Practical Law natively embedded, guided by 35 million West Key Number classifications. The lawyer stays in control throughout, able to see the agent’s reasoning, challenge its assumptions, and redirect its approach.

When , a partner at Troutman Pepper Locke, tested it on a complex TCPA question, her conclusion was that she had found not a faster tool, but a different kind of tool. That distinction is everything.

One million professionals across 107 countries have now chosen CoCounsel, including 97 of the Am Law 100 firms and 95 of the Fortune 100. That number doesn’t represent market share. It represents professionals who needed to get it right and trusted us to help them do it.

How changemakers build

Changemakers don’t wait for certainty before moving. They move when the direction is right and the foundation is sound, and then they build in partnership with customers. That is exactly how we launched the next generation of CoCounsel Legal: as a beta, with leading firms, inviting them to shape what the product becomes.

We hold ourselves to the same accountability standard we ask our customers to hold themselves to. The professionals who move the world, who uphold the rule of law, defend the wrongfully convicted, and keep the engines of commerce turning deserve AI that is worthy of the work they do.

That is what we are building. And that is why, when professionals choose who they want to build this future with, they keep choosing 成人VR视频. That is what it means to be chosen by changemakers.

The window for AI experimentation in legal has closed. What comes next is building on the right foundation. I share what that means for legal professionals, and why the question that actually matters is not whether AI is fast, but whether you can stand behind what it produces.

The post appeared first on .