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Walk into any legal team meeting today and the conversation will almost certainly turn to AI. Clients are asking about it from the very first conversation, and lawyers are increasingly expected to explain not only their legal reasoning, but also the tools behind their work. Yet despite the explosion of legal tech solutions, many teams are facing a paradox: more tools, but not necessarily better outcomes.
The challenge is not a lack of technology, but a lack of operational clarity. The greater risk today is no longer falling behind in innovation, but adopting it faster than organisations can fully understand and integrate it into the way they operate.
Resilience in legal operations is often misunderstood as speed or adaptability. In reality, it is something more fundamental. It is the ability to absorb change without losing control of processes, of data, and ultimately, of outcomes. In a context where expectations are constantly evolving, being resilient means being able to clearly explain not just what technology you use, but how and why you use it. That is what clients are really trying to understand.
Beyond the Tool List
One of the most common pitfalls, both internally and in client conversations, is focusing too much on the technology itself. Questions like “How are you using AI?” or “What tools do you have?” are now standard. But too often, the response becomes a list of platforms and solutions, as if the tools alone were the value. In reality, they are not.
Technology does not fix broken processes. It scales them. Automating inefficiency only accelerates confusion. What truly matters is understanding where technology fits within a workflow, which processes it supports, which tasks it enhances, and how quality and control are maintained throughout. Technology, on its own, means very little. It only becomes valuable when it is embedded in a clear, structured way of working.
The Generative AI Effect
The rise of generative AI has further accelerated this dynamic. It has made powerful capabilities accessible to almost anyone, from lawyers and clients to junior professionals, and has significantly raised expectations. However, accessibility without structure rarely leads to meaningful impact. Providing access to AI without defining how it should be used, in which contexts, and with what level of supervision often creates inconsistency rather than efficiency.
A practical example illustrates this clearly.
A General Counsel at a large corporation needed to urgently verify a complex agreement. She asked an AI tool the whether a specific clause had any unintended consequences elsewhere in the document. After 15 minutes, the tool responded: the clause was fine and did not affect other parts of the agreement.
But then doubt appeared. What if the AI was wrong? The GC reviewed the entire document manually again. The result? No real time saved. Just duplicated effort.
This is a classic process problem. The review workflow was not adapted to working with AI. The GC approached the tool as if it were another lawyer, expecting a final, reliable answer. In reality, the task should have been broken into smaller, verifiable steps - a mini-process that allows for incremental validation instead of redoing the entire analysis from scratch. When AI outputs require full human review, much of the anticipated efficiency gain is lost.
AI does not replace processes. It depends on them. Without clearly defined workflows, it becomes just another layer of complexity rather than a true driver of transformation. AI without structured inputs and reliable data cannot truly learn. It can only approximate. This is why so many early implementations fail to deliver consistent value.
Data: The Foundation That Makes It All Work
At the core of this challenge lies data. Behind every effective use of AI, there is structured, reliable, and intentionally managed data. In many legal environments, data is still treated as a byproduct of work rather than a strategic asset. In practice, this often means that no one really owns the data - and what no one owns, no one improves. Fragmented data leads to fragmented insights; inconsistent inputs lead to unreliable outputs. This is why AI maturity cannot exist without data maturity.
Take contract review as a practical example. Applying AI without standardised clauses, historical benchmarks, or structured repositories will inevitably produce inconsistent and difficult-to-trust results. Technology can amplify value, but only if that value already exists in the underlying data and processes.
A second example shows how easily things can go wrong.
Lawyers in a large in-house legal team connected their shared network drive to an AI chat tool, expecting better results. They had heard that AI performs best when it has access to internal documents.
The outcome was the opposite. The answers became less reliable, and new types of errors started appearing. The reason was simple. The drive contained not only high-quality documents, but also drafts, incomplete files, commented versions, and materials that were never meant to serve as reference points. From the AI’s perspective, a flawed document has the same weight as a perfect one.
Without curation, context and labelling, more data does not mean better answers – it means more noise. This is where the old principle still applies: garbage in, garbage out.
The Hidden Cost of Innovation: Digital Clutter
At the same time, the rapid growth of available tools is creating a different kind of challenge. Each new solution promises efficiency and transformation, but without a clear strategy, the result is often fragmentation: disconnected systems, overlapping functionalities, and additional manual work required to bridge the gaps. Tool adoption without integration becomes digital clutter, not progress.
This also explains why a common client question, “Why doesn’t AI just do everything?”, still does not have a simple answer. The reality is that legal teamsare still in a phase of experimentation. KPIs and value metrics are still being defined, and no single solution can address all legal needs. What the market offers today are powerful capabilities, not complete and universal answers.
Start with the Process, Not the Platform
A more sustainable approach starts not with technology, but with the process. Understanding how the work actually happens, who does what, when, and why, is the first step. From there, processes can be simplified by removing redundancies, clarifying ownership, and streamlining decision-making. Only then does technology truly add value, by supporting and scaling what already works. In many cases, significant improvements can be achieved even before any technology is introduced. When it is finally applied, the results are far more consistent and measurable.
People at the Centre of Change
This transformation is not only about systems. It is about people. Lawyers today are operating in a rapidly evolving environment where client expectations are changing and the nature of legal work itself is being reshaped. In this context, both lawyers and clients need guidance, not just tools. The objective is not simply to reduce time spent on low-value tasks, but to rethink how work is structured, enabling better collaboration across seniority levels, supporting junior lawyers in developing new capabilities, and ensuring that efficiency gains do not come at the expense of quality.
AI plays an important role in this evolution, but only as part of a broader, intentional redesign of how legal work is delivered. The goal is not fewer lawyers; it is better, more focused legal work.
Building on Strong Foundations
At CMS, this is the approach we take. We do not start with technology. We start with the process. Only after understanding and improving how workflows operate do we introduce AI and digital tools, carefully selecting and integrating them into a coherent system. This allows us to enhance legal expertise rather than replace it, ensure consistency and quality, provide transparency to clients, and build scalable, resilient operational models. In many cases, the right solution is not a single tool, but a combination of technologies working together within a well-designed framework.
In a world of constant technological change, resilience is becoming the true differentiator. It is not defined by how many tools we adopt or how quickly we implement AI, but by our ability to remain in control of how work is done, how data is managed, and how value is delivered. Technology will continue to evolve, and client expectations will continue to grow. But only those who build on strong foundations, clear processes, structured data, and intentional design, will be able to adapt without losing direction.
Because in the end, resilience, not technology, is what will define the future of legal operations.
