AI Strategy for Legal Services

The operating model question, central team, embedded, or hybrid, determines more about your outcomes than any tooling decision you will make.

In legal services, privilege and confidentiality mean data handling is scrutinised more than model performance. That single fact reshapes how ai strategy has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is matter summarisation, usually integrated against e-discovery platforms. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

Multi-model by default, so a provider outage is a routing decision rather than an incident. We hand over with runbooks, tests and a team that knows how it works, not a dependency.