This build-and-own approach contrasts with rivals like Freshfields, which partnered with Anthropic to sell AI products externally to other firms, highlighting differing strategic models in the legal AI market.

Specific platform details, deployment timeline, and capabilities have not been disclosed and will be announced later.

Risks include high costs, slow internal builds, and overestimating internal capabilities, but the strategic logic favors those who control their AI infrastructure.

The Financial Times first reported details of Kirkland’s plan, underscoring the media’s role in highlighting bespoke AI strategies in law.

Kirkland & Ellis is leading a move in BigLaw to own and build its own AI platform, aiming to improve internal productivity and create a durable competitive edge through proprietary technology.

The firm will combine in-house development with licensing external AI tools, balancing internal platform work with third-party access.

Kirkland’s strong financial position supports the plan, following a record revenue year and suggesting the investment won’t heavily impact partner distributions.

The firm plans to invest hundreds of millions—over $100 million this year and a total of about $500 million over three to four years—to develop a proprietary AI stack, while still licensing some third-party tools.

Kirkland emphasizes owning the technology to control roadmap, data, and commercialization, building on past data-driven moves to spot deal trends.

Industry concerns persist about AI reliability, confidentiality, and client trust, especially after AI-generated errors in filings.

The investment is framed as an internal productivity and capability move rather than launching a client-facing product.

The ambition is to own the intelligence layer underpinning legal work, shifting competitive advantage from tools to the platform trained on decades of internal expertise.