AI-Native Firms, Built by Private Equity, Will Strain Legacy Model

At the end of 2025, Mike Schmidtberger left Sidley Austin, one of the nation’s leading and largest law firms, after chairing its executive committee for seven years. The next month, he became chairman of another law firm: Norm Law—a two-month-old AI-native legal platform backed by Bain Capital, Blackstone, and Vanguard.

Schmidtberger described a completely “changed mindset” about technology and legal practice. In joining an AI-native firm—one built from the ground up with AI integrated into its service delivery, pricing, and workflow—he drew a sharp contrast with traditional firms that layer AI onto a legacy model. When he walked through the doors of Norm Law, he told Bloomberg Law he “confronted the future.”

The emergence of AI-native law firms reveals the limits of a fixed binary that has characterized the legal market over the last year.

The consensus view has been that law firms can’t access third-party capital to support their core business because of regulatory barriers in most jurisdictions. So capital flows instead to legal tech platforms, alternative legal service providers, and back-office managed service organizations, all in the service of legacy law firms.

The result is a market entrenched on one side—a durable but capital-strained legacy model—while on the other, innovation is propelled by investment not in law firms, but around them.

Legal tech platforms illustrate the scale: Harvey raised $300 million at a $3 billion valuation; Fastcase and Brightflag each merged with legal tech consolidators; Anthropic entered the market with a legal plugin for Claude that sent shockwaves through legal tech valuations.

But this false binary misses an emergent third way.

The straightest path to AI law firms isn’t innovation within the legacy model, or capital investing around it, but external capital being deployed to build competitors to legacy firms. These firms use AI and narrow regulatory openings to create from scratch tech-enabled law firms.

Not acquire them. Not invest around them.

Build them.

This third path is no longer theoretical. Arizona’s Alternative Business Structure framework—allowing non-lawyer ownership of law firms—opened regulatory space that didn’t previously exist. Eudia (on whose Client Advisory Board I sit) established Eudia Counsel last fall, an ABS-licensed law firm combining the capabilities of AI and alternative legal service providers. KPMG opened a US law practice under ABS rules. LegalZoom and others followed similar paths.

AI-native law firms will follow this model: establish a technology platform, build client relationships as a vendor, develop service delivery capabilities, then create a regulatory-compliant law firm that competes for work that otherwise would go to traditional firms.

These aren’t one-offs. They represent a new strategic paradigm—one that sidesteps both the cultural resistance of established partnerships and the circuitous investment models that try to work around them. When forces like these converge—AI restructuring how legal work gets done, external capital funding those positioned to leverage it, and legal regulatory reform creating an opening for new entrants—they don’t add. They multiply.

READ MORE: GC x AI: Reinventing the General Counsel Role in the AI Era

Movie Theater Economics

Understanding why tech-first platforms pose a structural threat means examining how legal work itself is splitting into segments.

One segment—“industrial legal”—is process-dense, labor-intensive, high-volume, and offers substantial margins: document review, due diligence, contracting at scale, compliance monitoring. This work is analytical, repeatable—and increasingly automatable.

Another segment is relationship-dependent and strategically ambiguous. It blends experience and creativity. This “judgment legal” work—governance advice, complex negotiations, high-stakes litigation, regulatory strategy where the law is fundamentally unclear—resists systematization and depends on deep contextual synthesis.

Traditional firms make their greatest profits not necessarily from the star partners of the judgment practice, but from bundling both segments. Singular expertise is packaged with large teams of associates doing industrial analytical work at scale.

At its core, it’s movie theater economics: The star sells tickets, but the theater makes its money on popcorn. Tech-first platforms may not offer the blockbuster name, but they’re designed to capture the popcorn sales. And in legal services, industrial work is the popcorn—and the profit.

One theory posits that Big Law will bridge this divide by synthesizing deep expertise with AI efficiency. But the default incentive within partnership economics will be to use AI to increase profits at existing price points, not to decouple “prestige” from “price” and sell the commodity work at a discount. The cultural and governance structure of large partnerships tilts toward margin preservation, with profits-per-partner and associate leverage still treated as primary scorecards.

Knowledge as Compounding Asset

It’s a truism of law firm economics that the most valuable assets walk out of the building every night. When key lawyers leave, institutional knowledge leaves with them—insight about the client’s people, strategy, risk tolerance, and business approach. What remains is the documentary residue: files that capture outcomes, but not the judgment that generated value.

This is why the best outside counsel relationships are often rooted in specific partner relationships, not firms. When a partner retires or moves, the client either starts over or also moves. Either way, the firm is exposed.

In the tech-first platform, every contract, negotiation, and filing feeds a system that captures not just what was done, but how it was approached—the reasoning, the tradeoffs, the institutional logic. That knowledge compounds independently of any individual lawyer. And crucially, it belongs to—and resides with—the client, not the firm.

For general counsel overseeing broadly capable—and expanding—legal departments, this creates an entirely new calculus. AI-enabled centralization of knowledge mitigates the risks of a legacy model in which in-house teams produce inconsistent documents, deploy differing strategies, or adopt varied risk profiles. As a fellow GC put it to me directly: “AI has its risks—but so does having a hundred lawyers each doing things their own way.”

AI-enabled knowledge systems hedge both inconsistency and attrition: New talent can be coached by AI on “how we do things here” rather than learning through trial and error.

There’s a deeper point. Lawyer knowledge is fundamentally not shelf-stable—memories fade, contexts shift, people leave. AI-retained knowledge is stable, current, and always available. The GC who owns the institutional memory—rather than renting it from a firm—has a structural advantage that traditional outside counsel relationships no longer match.

The Partnership Trap

If the synergy of collective legal expertise is a law firm’s organizing principle, annual cash distribution is its fuel. The emphasis that law firms place on annual cash distributions is in perennial tension with long-term capability building. Every dollar invested in infrastructure benefits future partners and clients at the cost of current partners’ cash. In an active lateral market, those yearly distributions become essential to talent retention. When those distributions are expressed as profits-per-partner, they drive the rankings that determine a firm’s prestige and viability.

Near-term cash is what holds partnerships together. While it may be true, as an old maxim has it, that great societies are built by those who plant trees in whose shade they will never sit—this has not been the operating principle of even great law firms.

The shift also reflects how consumers of legal services are already changing. Corporate legal departments increasingly unbundle work. Rather than routing work to an all-purpose firm, they frequently match matter type to provider specialty—such as sending IP matters to a specialized boutique. As in-house teams build their own AI capabilities, the institutional knowledge that once locked clients to specific firms becomes portable. Tech-first platforms align with how legal consumers are already behaving.

This leaves traditional firms at a structural disadvantage against new competitors. External capital is knocking on the door at some traditional firms—both Quinn Emanuel and McDermott Will & Schulte have signaled openness to outside investment—but its biggest impact is funding the entirely new AI-native model.

Law firms have long been protected by a knowledge moat. The convergence of capital and tech is beginning to breach it. The future Schmidtberger saw isn’t a destination—it’s a gateway. How traditional firms respond will shape what’s on the other side.

Part Two of this series examines whether legal work continues to unbundle—and what the market will look like as a result.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law, Bloomberg Tax, and Bloomberg Government, or its owners.

Author Information

Eric Dodson Greenberg is executive vice president, general counsel, and corporate secretary of Cox Media Group. Eric also writes about leadership, legal operations, and the intersection of law and AI for Bloomberg Law’s Good Counsel column.

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