Sidley Austin’s former executive committee chair Mike Schmidtberger is trading Big Law leadership for an AI‑first experiment, stepping in as chairman and funds/regulatory head at two‑month‑old Norm Law LLP, an “AI‑native” firm built around legal agents rather than billable hours.
This is a live test of whether a partner who doubled Sidley’s revenue can now help industrialise legal work for institutional clients through an AI‑engineered law firm model.
Global Chair to AI‑native builder
Schmidtberger chaired Sidley’s executive committee from 2018–2025, a period in which the firm says annual revenue doubled, and he was also managing partner of the New York office and global co‑leader of the investment funds group. After stepping down under Sidley’s age rules and retiring from the partnership, he says walking into Norm Ai’s office “completely changed” his view of post‑Sidley life, convincing him that the future was in AI‑enabled legal delivery rather than a slower glide path into retirement.
Norm Law, launched in November, has appointed him chairman, partner and head of investment funds and regulatory, with a remit that includes recruiting lawyers and selling an AI‑centric service model to sceptical but curious financial‑services clients. Early hires include former Brown Rudnick partner David Sorin and former Cadwalader partner Mike Rupe, plus senior associates, with more partners expected as the firm scales.
Norm Law’s AI offer
Norm Law markets itself as an “AI‑native legal services” firm built in tandem with affiliated company Norm Ai, which develops AI agents that encode legal and compliance workflows. In practice, that means:
- AI agents, designed by lawyers, produce first‑draft outputs for tasks like regulatory analysis, policy mapping, playbooked negotiations and document generation, with human partners and associates supervising, editing and advising.
- The firm focuses on financial‑services and highly regulated clients, leveraging Norm Ai’s existing user base across asset managers and financial institutions, including those linked to investors like Blackstone.
Blackstone invested US$50 million into Norm Ai and is collaborating via its in‑house legal team to shape Norm Law’s offering, with other investors including Bain Capital, Vanguard, Coatue and New York Life. This capital and client proximity allow Norm to build AI agents around specific regulatory regimes and in‑house policies, effectively turning bespoke compliance know‑how into reusable, auditable systems.
How Norm Law differs from traditional firms
Norm Law is not just using AI as a back‑office tool; it is structuring the entire firm around it. Compared with traditional Big Law models:
The distinctive play is “legal engineering”: lawyers are hired explicitly to convert doctrine and process into machine‑readable workflows, something Schmidtberger had foreshadowed at Sidley by pushing investment in knowledge management so the firm could function as a “collective intelligence.” For in‑house teams, Norm’s pitch is that this model delivers consistency across a global organisation while freeing internal and external counsel to concentrate on strategy, complex structuring and contentious work.
Strategic implications for firms and careers
Norm Law is one of a small group of AI‑powered law firms testing how far legal work can be automated while staying within professional‑responsibility rules, with lawyers retaining oversight and accountability. Founder John Nay says the firm was effectively built “backwards” from conversations with existing Norm Ai users who wanted a law firm architected around AI from day one, not a legacy practice bolting tools on at the margins.
For lawfuel readers, three angles stand out:
- Senior‑partner exits now include AI‑platform leadership: Schmidtberger’s move sits alongside former Big Law partners joining or founding players like Harvey, Casetext and Ironclad, with roles that blend leadership, product and client strategy.
- Associates and mid‑levels may find new careers as “legal engineers,” working on workflow design, data, testing and client implementation rather than pure hourly drafting.
- Traditional firms face pressure to decide which work types will be re‑engineered internally – and soon – if they do not want AI‑native firms like Norm to become the default conduit for high‑volume regulatory and documentation tasks.
If Schmidtberger helped double Sidley’s revenue by professionalising knowledge and management, his Norm Law chapter will test a sharper question: can that same mindset, wired directly into AI agents rather than precedent banks, become the core architecture of a profitable, scalable law firm?
