Point of view

BigLaw built it so mid-market doesn't have to.

The AmLaw elite have entered a nine-figure AI arms race. It's a race the mid-market should sit out, and here's what to take from it instead.

The legal industry is witnessing an unprecedented capital deployment event. Driven by the fear of disruption and the promise of hyper-efficiency, the elite tier of the AmLaw 100 has entered a nine-figure arms race to build proprietary artificial intelligence infrastructure. For leaders of mid-market law firms, those managing 50 to 250 attorneys, the headlines are intentionally daunting.

But a measured analysis of this landscape reveals a liberating reality: BigLaw is building this infrastructure so that the mid-market does not have to. Attempting to mirror their capital expenditure is not only impossible; it is strategically flawed.

What the elite are actually building

To understand why mid-market firms should abstain from the infrastructure race, look closely at what elite firms are actually constructing. They are no longer merely purchasing software licenses; they are funding custom tech stacks, dedicated engineering teams, and deep development partnerships:

  • Kirkland & Ellis announced a $500 million investment over three to four years to build a custom proprietary AI platform, dedicating an initial $100 million tranche in 2026 alone. The initiative involves an in-house innovation team of roughly 180 people and specialized AI infrastructure directors to manage on-premise GPU clusters and fine-tune open-source models.
  • Freshfields entered a multi-year co-innovation agreement with Anthropic in April 2026 to build specialized legal applications and multi-step agentic workflows across its 33 global offices, following its 2025 alliance with Google Cloud to leverage Vertex AI for custom internal legal agents.
  • Paul, Weiss embedded its lawyers directly into the development cycle, acting as the central design partner for Harvey's "Workflow Builder" in mid-2025 to map and construct repeatable, firm-wide legal workflows.
  • Wilson Sonsini developed its proprietary "Neuron" platform, integrating AI agents to offer automated, fixed-fee commercial contracting and startup incorporation workflows.

These global firms operate at a scale where even fractional efficiency gains across thousands of attorneys yield massive aggregate returns. They must defend multi-billion-dollar revenue baselines and justify premium pricing to clients who demand institutional-grade data isolation.

The fallacy of replication

For a mid-market firm, attempting to duplicate this infrastructure is a categorical error. A firm of 100 or 200 attorneys does not have the capital to absorb a nine-figure tech budget, nor the institutional bandwidth to run a software engineering department.

More importantly, building custom foundational architecture or hosting private GPU clusters forces a law firm to behave like a technology enterprise, shifting focus away from the practice of law toward managing technology obsolescence. General-purpose models and enterprise legal AI layers are commoditizing at an exponential rate. By the time a mid-market firm could build a custom system, off-the-shelf alternatives will outperform it at a sliver of the cost. The elite firms are absorbing the massive R&D risk and the expensive early mistakes. The mid-market should let them.

The path forward: Practice Codification

So what is truly transferable to the mid-market? The real value of BigLaw's AI experimentation does not reside in the underlying compute power or proprietary code. It resides in the rigorous discipline of Practice Codification, the systematic work of deconstructing legal expertise, firm precedents, and procedural workflows into explicit, repeatable playbooks.

BigLaw spent millions learning that a raw model is structurally useless without highly structured institutional knowledge. Mid-market firms can capture the vast majority of the strategic value of AI by applying that same discipline to general-purpose, enterprise-grade tools. Instead of building a proprietary platform, mid-market leaders should focus on cleaning internal data, standardizing high-quality precedents, and deeply mapping each practice group's workflows. Ground a robust, commercially available tool in a highly codified internal methodology, and it delivers bespoke-level accuracy. The investment shifts from capital-intensive engineering to high-leverage knowledge management.

Agility is the real moat

Ultimately, the mid-market's edge over the AmLaw elite is not infrastructure; it is agility. BigLaw firms are capital ships, massive and powerful, but agonizingly slow to turn. A multi-million-dollar enterprise deployment takes years of governance, security vetting, and change management across dozens of legacy global offices.

A mid-market firm can identify a workflow, apply Practice Codification, and deploy an AI-augmented solution in a matter of weeks, pivoting as the market evolves, unburdened by legacy tech debt or sunk infrastructure costs. By focusing on workflow discipline rather than proprietary building, mid-market firms deliver the same tech-enhanced efficiency and predictable pricing their clients want, while keeping the personalized, high-touch relationships that define their position. BigLaw built the highway; the mid-market simply needs to drive on it.

Sources

  1. Kirkland & Ellis's $500M proprietary AI platform, $100M in 2026, ~180 technologists, built on input from 250 lawyers. Bloomberg Law.
  2. Freshfields' multi-year agreement with Anthropic, deploying Claude across its 33 offices (April 2026). Freshfields.
  3. Paul, Weiss as the core design partner for Harvey's Workflow Builder. Paul, Weiss.
  4. Wilson Sonsini's Neuron platform, AI-enabled, fixed-fee commercial contracting (92% standalone agent accuracy). Wilson Sonsini.
← Back to insights

Skip the arms race.

You don't need a nine-figure platform, you need your practice codified and the right tools fit to it. That's where we begin.

Schedule a discovery call