The adoption of AI-powered legal technology has become an inevitable milestone for corporate legal departments.

As more teams experience the power that these tools can have on their efficiency and strategic impact, uptake is steadily on the rise, with 44% of legal teams now using generative AI and 30% planning to include it in their upcoming tech implementations.

But, as with most modern technology, ensuring success when introducing AI capabilities into your legal operations isn’t just about the tools you choose – it’s about how you use them.

The value that can be extracted from any AI tool is only as good as the data that it can access. For in-house legal teams, the most accurate, secure and impactful results are achieved when AI is leveraged on top of a single, comprehensive data repository – otherwise known as a single source of truth.

In this article, we’ll explain why consolidating your data into a single source of truth is a critical step when it comes to leveraging AI – and how to keep this concept front and center of your adoption strategy.

What is a single source of truth?

There’s a wealth of information sitting beneath your legal team’s everyday workflows, from the key clauses in your contracts to the numbers that make up your legal spend. There’s a lot of potential power behind this data – but only when it’s captured and stored in a way that makes it easy to access, manage and understand.

Unfortunately, the reality of daily legal operations for many corporate teams results in data silos, with critical information spread out across email, spreadsheets and individual point solutions (such as CLMs).

Although the data is technically all there, its functional value is limited while it remains in a fragmented state. Gaining a holistic view of what’s going on across your function takes considerable manual effort, jumping between systems to pull together and organize disparate threads of data.

Thankfully, a key advantage of many legal technology solutions is their ability to pull these data threads together to create a “single source of truth”: one comprehensive data repository for all the work that falls under the remit of that solution. This central repository allows for efficient storage, organization, searchability, and sharing of all relevant information within that workflow.

With the right legal technology, this should become a symbiotic relationship: your software unifies your data, which it then leverages to deliver better outcomes for your team and drive data-driven decision making.

Why a single source of truth is a critical foundation for AI

When you start preparing your team for the shift into AI-powered legal technology, the importance of a single source of truth shifts from a “nice-to-have” asset to a critical anchor. At the same time, the introduction of AI can also make the task of building and leveraging this central repository far easier.

When it comes to adopting AI to make your legal team more efficient, the right AI powered technology should create and amplify the power of a single source of truth in three ways:

• Building your single source of truth: AI tools can help to build your central repository itself by collating and organizing your legal team’s existing data into one place – accurately and with less effort from the humans on your team.

• Enhancing core workflows: AI can then use this central bank of data to supercharge your core daily workflows, helping your legal technology deliver stronger and more efficient outcomes.

• Providing elevated insight: Finally, AI can leverage your newly formed single source of truth to surface clear reporting insights from complex datasets – information which would otherwise take a huge amount of manual work to make sense of.

By building your AI adoption strategy around a single source of truth, you can create an accurate, secure and self-sustaining data ecosystem – one that will only deepen in value as it grows.

But how do you get this crucial step right?

Building your single source of truth: Core considerations

Identify your critical data

We now know that any successful AI adoption strategy needs to be built around a central bank of data. This is something that needs to be thought about well before you actually introduce AI tools into your legal workflows.

But what do we actually mean by data, and what kinds of data do we actually want AI to capture and leverage?

For the purposes of in-house legal teams, data is all the information that sits beneath, and is generated by, your team’s daily legal workflows, from matters and contracts to intake and spend. Of course, that’s a lot of information, and some bodies of data will be of more value to your team than others – but as a general rule of thumb, the more data you have to work with when adopting AI, the better.

For your single source of truth to hold maximum value, it should ideally encompass every element of your legal work (something we’ll explore further below). But even if the scope of your data repository is narrower, it will ultimately need to capture two broad categories of data:

Operational data

This is the data that tells you how efficiently your team is operating. For example, how long does it currently take your team to review the average NDA? How many times does the contract currently go back and forth before being finalised? This data is essential if you want to understand where your team’s biggest blockers are, and where AI is going to have the biggest impact on your work.

Substantive data

This is the data generated by your legal team’s shared ways of working. From informal workflows to formal policies and playbooks, this information can help AI to understand and replicate your standard approaches to work at scale.

For example, your team may have a consistent list of edits that are always made to commercial contracts. If an AI redlining tool has access to this data, it can replicate this approach as a first pass.

For any AI tool to truly have an impact within your function, it will need comprehensive access to this information. If you try to implement AI tools without a reliable, secure and fast way to feed them this critical data, the technology won’t have much to work with – and you’ll have a much harder time obtaining valuable outputs.

Understand where your data is stored

In order to understand how to practically go about implementing an AI tool, you’ll also need to think carefully about where your data is currently stored. Here are the two most likely scenarios:

Email and spreadsheets

If you’re not currently using any dedicated legal technology, the chances are that your legal team’s data is spread across various sources, including email, documents and spreadsheets.

Before even thinking about bringing AI into the picture, your priority should be to shift out of these modes of data storage and into a purpose-built legal tech solution which can help you build out your central source of truth.

Depending on your team’s priorities, this might look like investing in an individual tool like a CLM – but you’re starting from a blank canvas, so this is also the perfect time to think longer term and invest in a comprehensive legal technology solution which will build a stronger data foundation for AI.

Point solutions

If you’re currently using legal tech for one or more of your legal workflows (such as a CLM, document management system or e-billing software) the chances are that your data is already a bit more structured. You probably have at least one “mini” source of truth to work with – so one option is to start by exploring options from your vendor to add AI capabilities into the mix now.

However, as long as you stay within point solutions, your data will still be fragmented across your workflows. You’ll still have to jump between systems to get true oversight of how your team is working, and any AI tools that you invest in will not be powered by a truly unified single source of truth.

Whatever the current state of your data storage, it’s well worth considering whether now is the time to invest in more comprehensive legal technology to ensure that your future AI capabilities are built on the strongest possible foundations.

Consider a consolidated solution

We’ve established that AI is only as powerful as the datasets it has to draw from – and the most powerful data repository is one that encompasses as much of your legal work as possible.

While you can still get a lot of value out of AI using “mini” sources of truth within your contracts, matters, or spend, a truly unified single source of truth is a far more powerful engine for AI.

For example:

• An AI-powered search tool can be used within a CLM to identify key dates, clauses and contract terms. However, if that same AI tool has access to all of your wider matters, it can deliver far more contextual information which is relevant but not visible within the contract itself (for example, details or amendments which are sitting in other documents or emails).

• An AI-powered analytics tool focused on intake or e-billing can give insight into how well your team is tracking against KPIs within those individual workflows. But the insights provided by AI will be far more valuable when they include all of the wider contextual information that they relate to across wider contracts and matters.

To be sure that your AI tools are working from a truly unified single source of truth, consider investing in a comprehensive solution which manages your contracts, matters and spend in one place – like a legal workspace.

Choose embedded AI

For legal teams, it’s critical that AI tools are safe, secure, and give accurate results. These outcomes are far easier to achieve when AI is fully integrated into the system that holds your single source of truth. This way, there’s no need to manually pull together the data that AI needs to do its job.

What’s more, when AI capabilities are embedded in the tools you work in every day, they’re more likely to be adopted by your team as a natural way to speed up the workflows you’re already tackling.

When you go to market for AI, you should therefore look for tools which come as an embedded feature of a dedicated legal tech product – not as a separate add-on.

Not only does embedded AI create superior workflow efficiencies, but having this capability seamlessly integrated into your legal tech also ensures accurate output, ensures responsible use by preserving your data within one secure system, and supports easier adoption.

Ready to build your single source of truth?

Whether you’re ready to start working with AI now, or are planning to do so in the future, a solid data foundation will set you on the path to success.

To get the best out of AI, you need a truly unified single source of truth. That means opting for embedded tools which come as part of a dedicated legal technology solution – and the more workflow data your AI tools have access to, the more you’ll see strong results.

To learn more about how the LawVu legal workspace delivers secure, accurate and reliable AI capabilities built on a comprehensive source of truth, check out our complete guide to AI adoption – or book a personalized demo here.