By Jeffrey Solomon, VP & GM, LegalVIEW® BillAnalyzer, Wolters Kluwer
Artificial intelligence has rapidly become a critical part of the tech stack of the modern corporate legal department (CLD). Technology companies have been at the forefront of this trend, leveraging the technology for a myriad of use cases, from outside counsel assignment to invoice review and beyond.
However, recognizing the value of AI-driven legal solutions does not mean that tech companies have an easy time implementing them.
Most software solutions are deterministic, meaning they have a clear-cut expected outcome—one that employees can count on each time they use the product. Because AI is probabilistic, there are far more grey areas. Additionally, AI gets smarter over time, thanks to built-in machine learning capabilities.
Thus, managing the transition to AI can be a delicate process for any CLD. Here are five steps to make it easier.
1. Choose the right solution
Don’t bring in AI for the sake of bringing in AI. Instead, choose a solution that aligns with your CLD’s top priorities. This will make the process of getting buy-in from senior management easier.
While many factors go into choosing the right solution, a strong foundation – AI built and trained on mountains of accurate and relevant data – is critical. Additionally, a commonly overlooked one is support. With AI, models need to be updated and calibrated on an ongoing basis. Thus, it’s particularly important to know what support will be provided by the vendor you choose. Are there data and domain experts behind the solution you’re considering—or just customer support experts? Do your due diligence, and don’t be afraid to ask these questions, as both items are critical for smooth onboarding and long-term success.
2. Set expectations
Setting reasonable expectations is particularly important for AI. Corporate attorneys are busy people, so it’s natural for them to want immediate gratification.
That is not what AI is about. While you should see early returns, AI models require calibration and get smarter through usage. It’s important to help your team understand that AI will not necessarily deliver full results right out of the box. Let them know that this is a long-term investment, and they will begin seeing the benefits down the road that will yield benefits, not next week, but in the next few months, years, and beyond.
3. Choose the right deployment model
Often, software is deployed to automate or eliminate manual processes. When this is the case, it helps to compare existing processes with those now available to you through new, AI-driven solutions. Choose a time period for which to compare the efficacy and efficiency of the existing process with the AI-supported one to see which delivers better results. It will be the latter. When employees see firsthand that AI offers better results in a more efficient way, they’re more likely to get on board.
AI can also be added to an existing process as a quality assurance layer. In simplest terms, that means part of the volume is handled by the existing process, while a slice of it—perhaps the most challenging slice—is given to the AI solution. Over time, the volume handled by AI can increase.
4. Build awareness
The best way to build awareness about your AI solution is by inviting employees into engaged discussions about the tool and giving them actual hands-on experience. Doing a pilot, for example, lets users have a dry run before the tool is put into production. Usually, seeing the benefits of the technology first-hand will help earn trust.
Another great approach for building awareness is to assign “change agents”—people who work closely with the vendor team to understand the tool and become early adopters and proponents within your team. Think of change agents as internal influencers who, having seen the efficacy of the solution, can espouse its benefits to the rest of your team. Having designated change agents to teach employees how to use the tool is a great way to spur adoption.
5. Commit to transparency
Whether you’re trying to improve cycle time or your compliance rate, be extremely transparent about your KPIs and communicate, on an ongoing basis, how effective the solution is. One great way to create transparency is to use process mining software to visualize how people are spending their time on daily tasks both before and after the AI was introduced.
Additionally, as you’re trying to get buy-in and spur adoption, it can be tempting to only talk about the AI’s strengths. This is a mistake. Be transparent about the weakness of the solution, too. By showcasing where the AI is not meeting expectations or is offering low-recommendation solutions, you can begin a discussion about both how it can evolve and how users should handle it.
Change is always hard, especially when it comes to implementing new technologies. But by following these steps, you’ll be able to build a future-ready, AI-driven CLD. To read more about how technology industry legal departments can prepare for the future, download our whitepaper The benefits of AI for corporate legal departments in the technology industry.