Norm Ai

Norm Ai is proud to partner with CodeX, The Stanford Center for Legal Informatics for FutureLaw 2026. On April 16th, John Nay, Founder & CEO of Norm Ai, will be featured in two sessions: The Great Unbundling: Can Traditional Firms Compete with AI-Native Challengers? and Building Legal AGI. Joined by fellow speakers, they will explore how AI, automation, and new operating models are fundamentally reshaping legal services, and how to deploy supervised AI agents in high-stakes legal and regulatory workflows. FutureLaw will bring together global leaders in law, technology, and policy to explore how computational law and legal AI are evolving legal processes, education, and practice. We look forward to joining the conversation. Learn more about the event here: https://lnkd.in/eZ2q3caN

Going to chat AI policy with some leading U.S. Congressional candidates in a couple weeks See below for more details on the April 13 event on Governing Intelligence

On April 13th in New York City, Norm Ai and Norm Law will convene leading voices from law, policy, and industry, for a discussion on one of the most consequential issues emerging across the 2026 election cycle: how AI should be governed, regulated, and advanced. Featuring Alex Bores, New York State Assemblymember for the 73rd District and Democratic Candidate for New York’s 12th Congressional District, Jack Schlossberg, Democratic Candidate for New York’s 12th Congressional District, Anu Bradford, Henry L. Moses Professor of Law and International Organization, and more, the forum will explore questions of innovation, safety, economic competitiveness, and the government’s role in AI deployment. Moderated by John Nay, the forum will offer guests a front-row perspective on this critical policy dialogue, followed by a formal reception. Monday, April 13, 2026 | 5:00–6:30 PM ET New York Historical Society Attendance is limited. Request an invitation today: https://lnkd.in/eX7weXvh

After 35 years at Sidley Austin, including serving as Chair of its Executive Committee, Mike Schmidtberger joined Norm Law and, in the process, fundamentally changed how he thinks about technology and legal practice. Reflecting on that move, he told Bloomberg Law that when he arrived at Norm Law, he “confronted the future.” That shift reflects something deeper than new tools or incremental efficiency gains. For generations, law firms have built value through the expertise and judgement of their partners and associates. Today, an AI-native firm has the opportunity to extend that expertise by embedding AI directly into its service delivery model and legal workflows, making knowledge more scalable, accessible, and durable over time. At Norm Law, powered by Norm Ai, knowledge compounds, representing the future of institutional legal services that deliver outcomes faster, at greater value, and oriented completely around the client. Read more from Mike Schmidtberger in Bloomberg Law today: https://lnkd.in/eRFUxVcr

Don't miss the opportunity to learn how policymakers and industry leaders are approaching AI innovation, AI safety, economic competitiveness, and the government's role in AI. Monday, April 13th from 5:00 - 6:30 pm The New York Historical Society Request your invitation today.

Modern enterprises face a growing legal and compliance gap: content production and regulatory complexity have accelerated, but review capacity has not. Norm Ai is working with the world’s most sophisticated regulated organizations to close that gap with AI agents that are encoded with expert judgement, empowering legal and compliance teams with the speed, depth, and consistency required to achieve business goals. That impact is applied to the workflows that matter most: Regulatory & Firm Policy Review Regulatory AI agents follow guidance tailored to your firm, flag risks with rationales and citations, and generate compliant, on-brand alternatives Disclosure Management Disclosures are centralized and validated, each powered by AI agents that know when and where it belongs, surfacing exact language in context. Fact Verification & Substantiation The fact bank links claims to pre-approved sources and usage history, highlighting gaps so teams can use data-driven content with confidence. Learn how firms achieve a +90% reduction in total cycle review time with Norm Ai’s regulated content and marketing review.

This International Women’s Day, Norm Ai had the privilege of bringing together senior women across legal, compliance, marketing, investor relations, and more for an afternoon on New York’s Upper East Side. The 2026 IWD theme, Give to Gain, set the tone and across every conversation, the message that community is a career accelerant kept resurfacing. Many of the biggest breakthroughs and celebrations shared around the table traced back to relationships built over time with peers, mentors, direct reports, and sponsors. Those connections shape how women show up in executive conversations, make space for one another, and champion the success of those around them. The main takeaway was to be bold about seeking out these moments and building the relationships that make them possible. The conversation also turned to AI, and the guidance was equally clear: be ambitious. Don’t stop at implementing AI in one or two isolated places. Make room to step back and rethink the full value chain—where the work starts, where decisions get made, and what “great” looks like end to end. In the spirit of Give to Gain, what you invest in reimagining your work will compound. A special thank you to Stevi Petrelli, Melissa A. Marquis, Abigail Penzell, and Lilly Raymond for sharing your insights. We’re proud to be building this community, and excited to continue bringing leaders together across organizations.

There are questions about how Legal AI companies and law firms should engage in AI research partnerships with universities. Industry coalitions, academic think tanks, and Silicon Valley committees are getting involved. Norm Ai Founder and CEO John Nay was recently interviewed about Norm Ai and Norm Law’s collaboration with Stanford. "As a society, we've come up with a great mechanism...to make laws and other forms of policy that are publicly developed and determined collectively," Nay says. "The target of AI alignment should be democratically endorsed law, as it is the most democratic encapsulation of the attitudes, norms and values of the governed." Collaboration with Stanford and other leading research universities is essential to advancing this conversation. Norm Ai is proud to partner with CodeX, The Stanford Center for Legal Informatics to bring an industry perspective on how to regulate AI agents that perform economic activities and develop the research benchmarks for AI’s capability to perform legal tasks. Read the full article by Alexis Keenan here: https://lnkd.in/egFd5duE

Last week, Norm Ai’s Head of Legal Engineering, Paul Healy, joined the Investment Adviser Association Executive Roundtable alongside VP of Member Engagement Nancy Hancock to discuss trends in AI adoption and what it takes to remain competitive in an era of democratized access to frontier models. In conversation with senior legal and compliance leaders, three key takeaways emerged: 1. Your context matters.  In order for AI systems to prove truly useful for legal and compliance purposes, they must leverage each firm's full context. Legal and compliance workflows are inherently firm-specific with every firm having its own policies, procedures, clients, and regulatory history. The organizations that pull ahead will be the ones leveraging systems that encode their own legal standards and get more accurate over time, something off-the-shelf models alone can't do. 2. High-stakes AI systems should be built around the complementary strengths of people and AI agents.  Firms that do this intentionally will have a structural advantage over those that don't. AI handles high-volume, pattern-based execution; people handle the subjective, judgment-intensive pieces of an analysis. That division has to be intentional and built into how a system is constructed and maintained over time. 3. For regulated entities, full auditability in an AI system is non-negotiable.  Audit trails and documentation are necessary but not sufficient. Legal interpretations survive or fail against regulators, counterparties, and enforcement, making the real question whether or not the system is built to learn from its own track record. A system where every human intervention, correction, and approval feeds back into future performance is categorically different from one that just generates output and moves on. That feedback loop is what the most defensible AI systems are built around. Thank you to IAA for hosting us, and to the participants for a thoughtful and rich discussion.