Making a business case for AI

Once you’ve chosen your product and vendor, you’re almost at the most exciting stage of your AI adoption journey – but you’ll likely need internal buy-in to get your new investment over the line.

While many vendors promote AI capabilities, there remains a lot of uncertainty in the market around cost, pricing models, final feature experience, and long-term quantifiable benefits – particularly when it comes to the latest GenAI tools.

Investing in legal tech often requires a business case to help influence stakeholders on why the product you’ve chosen is the best option and, ultimately, to get sign-off for your investment. If you’re paying extra for built-in AI, you may well need to make a specific business case for that, too.

Key considerations

Putting together a business case for AI is, for the most part, not materially different to doing for your primary legal tech (especially if you’re purchasing an embedded AI-powered solution). However, AI brings with it a few additional considerations.

Here’s some tips for putting together a robust business case:

1. Clearly identify your current situation, outline your team’s pain points, and communicate the positive impact of your proposed AI solution within the context of your larger business strategy.
2. Draw on metrics and statistics to highlight how AI is going to unlock additional capacity within your team and demonstrate potential ROI. You can use tools like the legal efficiency and savings calculator to quantify the time and money currently spent on manual tasks by your legal team.
3. Clearly connect your business case to larger business goals. Don’t forget to call out the benefits of risk reduction, time back for higher value work, better compliance, scale, and employee satisfaction. These are important considerations for any technology business case, and AI is no exception.
4. Lean on your prospective vendor for business case templates and support with ROI projections. They should be able to help represent value, and share statistics which support your ROI projections. These will become more common for new GenAI capabilities over time, but may already exist when it comes to long-standing legal tech with AI capabilities.
5. If you are called upon to justify the specific benefit or ROI of investing in a standalone AI tool (or add-on feature) especially one which leverages GenAI, here are a few things to consider:
   • GenAI is still in its early stages, so quantifying ROI and impact is challenging. This will become easier over time as adoption rates, studies, and references grow.
   • GenAI requires a higher tolerance for indirect, future financial investment criteria versus immediate ROI. This is for two reasons: adoption may be staged with more users and use cases emerging over time; and value is most likely to come from benefits which accrue financial gains over time, such as productivity, cycle times, faster upskilling, and higher employee retention rates.

Remember, AI is just another way to deliver on your overall legal tech goals – so focus on the fact that AI capabilities will amplify the capacity of your legal tech to achieve these outcomes and maximize overall ROI.

The AI adoption process 

Congratulations! You’ve found the perfect AI solution for your legal team – and you’ve got it over the line. You’ll want to start getting value out of your new investment as soon as possible, but don’t try to do everything at once. 

If you’ve chosen a product with scope for multiple use cases, consider how you might adopt these sequentially for results which best serve your business case. 

Remember, the relationship between your legal tech and its AI capabilities is symbiotic – by using AI strategically to build up your unified source of truth first, you’ll strengthen its capacity to optimize your core workflows – which, in turn, will build the evidence you need to progress to more advanced use cases.

Here’s an example of how you might approach scaled adoption in three stages using specific AI-powered tools: