Legal teams often get stuck debating whether to begin with data, process, or technology, but that debate misses the point.
Start with the outcome. If you cannot clearly define what success looks like, and how you will measure it, the rest doesn't matter.
Once that is in place, the real issues tend to surface quickly. Data gaps become obvious. Processes reveal themselves as either intentional or just inherited. Stakeholders either support change or quietly resist it. All of that needs confronting early.
Another trap is trying to automate everything. The instinct to account for every edge case runs deep in legal, but it slows progress. The fastest way to prove value is to focus on the majority of scenarios and deliver something that works well for those. Perfection can come later, if it is even needed.
Speed matters. Early value matters more.
Testing is where many initiatives fall short. If the same people who built the solution are responsible for validating it, the results will be optimistic at best. Proper testing needs independence, clear criteria, and enough time to be meaningful.
The bigger shift is already happening
Infrastructure is no longer the main concern. Cloud platforms are stable enough for most use cases. The real question is where your intelligence sits.
As AI becomes embedded in legal workflows, firms are starting to rely on external models to analyse, decide, and surface insights. In some cases, those systems are already identifying issues faster than human teams could.
That creates a new kind of dependency. When critical thinking is outsourced, control moves with it. Few firms have fully worked through what that means for their long term strategy.
The ones that do will treat this as a capability question, not just a tooling decision.
Documents are not the process
Many firms still organise their thinking around documents. That view is limiting.
Documents are outputs. The real work happens in the flow of data, decisions, and context that leads to them. When that flow changes over time, as it always does, rigid workflows struggle to keep up.
The opportunity is to move beyond linear, step by step processes and toward systems that respond to data as it changes. Systems where people, automation, and AI interact across a connected set of actions to deliver outcomes, not just documents.
That is where meaningful transformation actually happens.
This is a shortened version of an article by Ben Stoneham, originally published in The Legaltech Diaries: Vol. 11 by Legal Tech Talk. Read the full article here.
