As part of our ongoing Legal Ops Accelerate series, Wolters Kluwer’s ELM Solutions presented a webinar entitled “Putting AI to work in your legal department”, in which our technology and process experts talked about how AI-driven legal bill review can help improve legal operations.
Legal bill review is a time-consuming process for legal professionals and keeps them from the higher-value work that puts their knowledge and expertise to better use. This, combined with the huge amount of historical billing data that is available, make bill review a perfect application for artificial intelligence, which can help to raise cost savings and billing guideline compliance significantly while increasing efficiency.
All of which presents an important question: How do you choose the right AI provider? To help answer that question, the following are three of the key areas of expertise to look for in any vendor you consider partnering with on AI-enabled bill review.
We often hear that AI is only as strong as the data behind it. Why is that? Because AI relies on big data to generate accurate and helpful output. In a sense, data is like the alphabet and AI is like a child learning a language. No one can learn English, for example, if they are only taught half of the alphabet. By providing AI with a large volume of data to “train” on, it can learn about the patterns you’ve established in your bill review practices. Without a very large data set, it wouldn’t have enough information to correctly identify the right action to take on incoming line items it reviews.
Beyond the volume, the quality of data is also critical. The data itself must be correct, of course, but it also has to be mapped and structured correctly. That work is done by people who should have legal expertise and familiarity with handling matters and invoices. This is why working with a provider who has domain expertise is so important. An AI tool built and managed by a team without that expertise and experience is unlikely to meet your expectations.
A proven track record of successful AI offerings and implementations is also extremely important for a vendor to have. AI technology is a fast-evolving field in which highly trained experts are needed to create useful solutions. These specialists must spend a great deal of time working with the domain experts mentioned above to understand not just the specific tasks the AI will carry out, but the entire bill review process and the legal department context.
This combination of domain and technology expertise allows a provider of AI-driven bill review to understand both the goals of a legal department’s bill-review program and the innovative ways that technology can help meet them. In addition, this relationship must be ongoing because AI isn’t like other types of software that a company builds once, and it works consistently over time.
Change management is the cornerstone that helps organizations ensure that an updated, AI-enabled bill review program generates the results they are seeking. Bill review is a core workflow that involves multiple team members daily, directly impacts on-time payments to law firms, and ensures the reliability of data on which important decisions are based. Therefore, the risk associated with new processes can be high if your vendor does not have the change management expertise to guide you through the transition to a new way of working.
Internal and external stakeholders at all levels must understand the motivation for the changes and what to expect at every step. Communications to these team members must be frequent, clear, and timely, with an understanding that some team members may be reluctant and need reassurance that people will still be a critical part of the process. Some flexibility must be built into plans so that any necessary adjustments can be made, ensuring the improved processes work well for everyone.
For more details, watch the recording of Putting AI to work in your legal department. And visit the Legal Ops Accelerate page to view additional webinar recordings and see what else is coming up in the series.