Introduction
Change management has long been part of corporate life. Every department experiences it, whether in finance, HR, or legal. Typically, it comes into play when a new tool is introduced or a new way of working is rolled out. AI change management, however, is different.
For legal teams, AI has already transformed daily work. Research is faster, drafting is more efficient, and contract review is quicker. Yet many teams still struggle to fully adopt these tools. This is often attributed to a lack of digital readiness, but in practice, the problem is more frequently the absence of a structured AI change management strategy.
The gap matters. AI adoption is not a one-time event. The tools available today will continue to evolve, and legal teams that fail to invest in AI change management now risk facing the same adoption challenges with every new wave of technology.
AI is moving fast. People need support to move with it.
Why traditional change management models fail with AI
One of the most established change management methodologies is the “waterfall approach.” It follows a linear structure, where each phase of a project is planned in advance and must be completed before moving to the next. This model provides clarity and predictability for stakeholders, but its rigidity often slows execution and limits adaptability.
Agile change management emerged in the 2000s as a response to these limitations. Built around iterations and frequent feedback loops, often through sprints, it enables faster implementation and continuous adjustment. While more flexible than waterfall, agile change management can still move too quickly for users to fully absorb change.
AI technology exposes the limits of both models. Unlike traditional software, AI evolves continuously. New features, new use cases, and new workflows appear at a rapid pace. As a result, users develop an ongoing, dynamic relationship with AI-powered tools rather than progressing through a finite adoption cycle.
Gartner notes that AI change management efforts often become overly process-driven. Success is measured by task completion rather than user confidence, and training focuses on features instead of human judgement. This approach can be counterproductive, increasing resistance to change and accelerating AI fatigue.
So, how can legal teams truly adopt AI when it is constantly evolving? When mastering one capability immediately leads to the next, change itself becomes the real challenge.
Human focused AI change management for legal teams
Effective AI change management for legal teams starts with a shift in perspective. Success cannot be measured solely by systems, outputs, or efficiency gains. People must be placed at the centre of the change.
Many organizations rely on process-centric metrics to assess AI adoption, such as:
These indicators are useful, but they fail to capture how employees actually experience change.* Human-focused AI change management looks beyond performance metrics to understand confidence, trust, and judgment in daily work.
Focus on legal responsibilities, not abstract metrics
When in-house legal teams understand how an AI powered solution supports their actual responsibilities rather than abstract efficiency promises, adoption becomes more likely.
This approach also requires highlighting the true value of AI technology. True value lies in the concrete impact AI has on legal work, and more specifically, in the strategic and business outcomes it enables. There is a meaningful difference between saying that AI allows contracts to be processed in half the time and explaining that this time saved can be used to track contract performance, identify potential savings, prevent unwanted automatic renewals, and ultimately support better financial decisions. By showing how adopting these solutions strengthens the legal team’s governance and strategic role, end users are more likely to engage with change in an open-minded way.
Focus on realistic outputs, not over-promising
Change is already demanding. Introducing multiple changes at once only amplifies the challenge. Rolling out too many capabilities and objectives too quickly is counterproductive and often leads to AI fatigue.
AI fatigue refers to the negative response employees develop toward AI-driven change. According to Gartner², by 2028 more than half of global enterprises are expected to view AI fatigue as the primary obstacle to achieving the anticipated return on AI initiatives. Focusing on realistic outputs, whether in terms of goals, capabilities, or features helps legal teams engage more confidently with change. Realistic objectives must go hand in hand with a transparency, including openly acknowledging the risks and uncertainty associated with implementation AI-powered solutions.
3 AI change management principles for legal teams
Build internal legal ownership
AI adoption cannot be managed solely by IT or innovation teams. Legal departments need clear internal ownership of AI change management to ensure alignment with legal realities and priorities.
A dedicated internal legal team or designated legal professional helps connect strategy with day-to-day legal work. The role assesses readiness, prioritizes relevant use cases, supports adoption, and gathers continuous feedback. Most importantly, it creates continuity over time.
AI change management for legal teams is not a project with a defined end date. The technology is constantly evolving, making this an ongoing capability rather than a one-off initiative. When legal professionals see peers actively shaping the adoption journey, confidence grows and resistance naturally decreases.
Communicate with clarity
AI change management for legal teams therefore requires more than isolated announcements or one-off updates. Communicating with clarity also involves transparency, as previously outlined in the article.
Clear and transparent communication explains what is changing, why it matters, and how it affects daily legal work. It also sets expectations by clarifying what will not change yet. These boundaries help reduce uncertainty and build trust.
Consistent communication makes change more predictable and this predictability strengthens AI change management. Fo legal teams, it translates into a sustainable, long term adoption of AI powered tools and features.
Adapt to different profiles
Legal teams are not homogeneous. Responsibilities differ from one role to another, but a broader factor that truly sets profiles apart: levels of digital readiness, which can vary widely.
Effective AI change management for legal teams acknowledges this diversity. Adoption roadmaps should reflect different starting points and needs. Some professionals require foundational understanding, while others benefit from more advanced or specialized use cases.
The adaptive approach helps end users feel seen and heard. Change becomes centered on how people experience it, rather than solely on how well they can use a tool. AI change management becomes more effective when learning paths, expectations, and support are tailored to distinct user profiles.
Change management is the key
AI adoption in legal departments is not primarily a technology challenge. It is a human challenge.
Legal teams that focus only on tools risk restarting the adoption conversation with every innovation cycle. Those that invest in AI change management for legal teams build something far more valuable: adaptability.
AI will continue to evolve. The legal teams that thrive will not be the ones with the most features, but the ones with the strongest AI change management for legal teams.
Sources
1. Gartner, Mitigate AI Fatigue With Human-Centric Change Management (ID G00836125 ), on demand only
2. Gartner, Essential KPIs for AI change management (ID G00799581), on demand only
Meet Legal AI – Lini
Lini is the AI engine that powers every dimension of legal work. Trained to think like a legal expert, Lini understands the nuances of governance, compliance, risk and reasons with context, not assumptions.
