10 Jan The State of AI for In-house Legal Teams 2026
This is according to a white paper jointly produced by Winmark and Marsden. In The State of AI for In-house Legal Teams 2026, 78% of General Counsel surveyed believed that at least half of their role will be automated in the future – yet 71% of legal teams remain currently stuck in pilot or exploratory phases. The stalling point is not access to technology – but the execution of it.
The research reveals a clear divide between legal departments that are unlocking meaningful value from AI and those investing heavily with little to show for it. Some teams report up to 70% efficiency and cost gains in targeted workflows, while others are wasting six-figure sums on tools that never meaningfully embed into day-to-day practice.
Our three key findings:
Many teams buy tools before defining the problem. Integration with existing systems is the top concern for General Counsel, yet technology is often evaluated before legal teams have clearly mapped where work actually gets stuck. The most successful departments start by identifying bottlenecks, repetitive tasks, and pain points across both legal and business stakeholders. Only then do they look to the market. Contract management consistently emerges as the strongest starting point, accounting for roughly 40% of total legal workload.
Data quality determines everything. AI does not fix messy information – it amplifies it. Case studies in the report show that organisations with clean, structured data and engineering support can build custom AI agents that dramatically reduce costs and turnaround times. Most legal teams, however, lack these resources and must rely on vendor solutions. This makes data ownership, governance, and long-term dependency critical considerations when choosing whether to build or buy.
The people question remains unresolved. General Counsel are split on whether AI will shrink legal teams or actually create new roles. The sharpest concern centres on the training of junior lawyers. If AI handles document review, research, and first drafts, how does the next generation develop legal judgement? One emerging answer is a shift toward “knowledge engineering,” where junior lawyers curate, structure, and train AI systems – but this requires new skills that law schools do not yet teach.
Despite bold automation forecasts, one finding is striking – no respondent believed that legal work will ever be 100% automated. There is broad agreement that judgement, strategy, and relationship management remain fundamentally human.
In practice, AI functions as a force multiplier. Legal teams describe handling two to three times the workload with the same headcount, not by replacing lawyers, but by removing low-value, repetitive work. Senior lawyers spend less time searching for information and more time making decisions that matter.
What actually works?
The report identifies five factors that consistently separate success from disappointment:
- Rigorous pain-point mapping before procurement.
- Structured vendor evaluation across business impact, security, user experience, and data ownership.
- Governance that enables experimentation without increasing risk.
- Baseline measurement to prove real improvement.
- Sustained change management that addresses anxiety and builds AI literacy.
AI is not a one-off technology project, it is an ongoing operational transformation. The ultimate prize is not efficiency alone. Done well, AI enables legal teams to move from reactive cost centres to proactive strategic partners – supporting faster decisions, better risk management, and business innovation.
For a full copy of the white paper, please contact us.