Successful legal tech adoption lies in effective planning

In today’s fast-paced environment, businesses are under pressure, particularly from the C-suite, to get tangible results quickly. Too often, however, in-house legal teams feel compelled to dive in and use technology without first dedicating sufficient time to determining whether the tools or platforms are actually best suited to meeting their businesses’ needs.

Last year 42% of companies sector-wide abandoned the majority of their AI initiatives before they reached production, according to analysis by S&P Global Market Intelligence. 

More often than not, the inability for projects to transition successfully from conception to widespread adoption is not down to failures inherent in the technology itself. Rather, it’s the failure by users to correctly identify and apply the right tools for the job from the outset.

In our experience, if in-house teams spent more time focused on getting processes right first, the outcomes are likely to be much better, and the benefits will be felt more quickly across their workstreams.

It’s important to think firstly about the problem or problems they are trying to solve. They should also identify where high-volume, repetitive work sit in their workstreams and the processes that underpin these tasks. Doing this groundwork first allows businesses to apply a much more targeted approach to workflow problems and ensure they select the most appropriate tech tools to resolve the problems they are facing.

For example, a legal team spending significant time reviewing non-disclosure agreements (NDAs) may benefit from AI-assisted contract review. A team struggling to respond to routine business queries might focus on AI-powered knowledge retrieval or legal front-door capabilities. The technology choice should follow the business problem, not the other way around

While procurement, budgeting and governance processes can take time, that period can be used productively to define and test practical AI use cases, evidence likely benefits, and build a stronger business case for investment.

Not every legal challenge requires a large-scale transformation programme, though. Some of the fastest returns can come from targeted use cases such as triaging requests, summarising contracts, extracting obligations, or first-pass contract risk reviews.

For fast-growing sectors replete with start-ups, or those that have experienced a large amount of consolidation, it is also likely that many organisations will need to carry out some groundwork initially to streamline and standardise contracts, agreements, templates and processes before teams can even begin to seriously contemplate technology implementation.

When the stakes are high and results are expected fast, effective planning and preparation is indispensable to reduce overwhelm and forge the best path ahead. It may seem counterintuitive, but in our experience, planning doesn’t require a long lead time and implementation can be iterative. We can guide businesses through the planning and pre-implementation phase and get a project up and running within a relatively short timeframe, whilst advising them on the necessary next steps, action points and the best delivery processes to achieve their organisation’s ultimate objectives.

As we have seen with legal tech platforms such as Leah’s – formerly ContractPodAi’s – generative AI platform for lawyers, contract lifecycle management (CLM) implementation can provide effective tools for any organisation looking to reorganise and manage their contracts more effectively.

Even when the C-suite gives budget approval to deploy certain technologies, there can also be other challenges to implementation. Like many teams in the corporate world, in-house legal departments are having to contend with headcount freezes that can make it practically more challenging to implement tech tools quickly and effectively, even if the evidence is already there that they will likely save them and their overall organisations both time and money in the long run.

One useful and practical way that in-house teams can make progress is by undertaking upskilling programmes on existing enterprise tools already at their disposal, such as Microsoft Copilot, to help them understand the capabilities of AI tools and their suitability for general productivity and legal specific tasks.

Alongside identifying suitable use cases, organisations should establish clear governance around AI usage, including data handling, human oversight and quality assurance processes.

The organisations seeing the greatest value from AI are often not those pursuing the most ambitious programmes, but those that identify clear use cases, deliver them quickly and build momentum through incremental adoption.