This article by Jim O’Hare, VP of CLM of LegalEase Solutions, was published on June 20, 2023, on Law.com
Training AI is an aspect of implementation that vendors need to discuss more with their prospects during sales calls—and one that prospects must educate themselves better on to make more informed CLM purchase decisions.
With expectations for artificial intelligence (AI) getting ever loftier—and its cost-saving benefits becoming ever more attractive—contract lifecycle management (CLM) vendors are touting their AI capabilities in sales demos to prospective clients. They often claim their AI modules are ready to go out of the gate to serve a client’s specific needs.
Redlining on the fly? All set on that front—with preferred clause playbook creation capabilities included. Data extraction from active contracts? At the snap of a finger. Streamlined obligations management? Easy-peasy.
These tools can be game-changing for a law firm or in-house department—if the AI knows what to look for. Getting an AIup to speed involves an extensive machine learning (ML) regimen with trained professionals that teaches the AI to look for contractual green and red flags the corporation prioritizes. As no two organizations are alike in their requirements, this becomes a highly nuanced and time-consuming exercise. It is an aspect of implementation that vendors need to discuss more with their prospects during sales calls—and one that prospects must educate themselves better on to make more informed CLM purchase decisions.
Fortunately, vendors and prospects can take several steps to resolve these ML misunderstandings over the sales process. Some suggestions are provided below on how vendors, law firms, and in-house legal departments can achieve this goal.
Modifying vendor sales presentations around AI capabilities
While CLM software clients must temper their AI expectations, vendors can help them make more informed decisions at the start of the sales process. How? By better tailoring their presentations to the specific needs of inquiring customers.
Regardless of the vendor, most sales teams follow similar sales presentations when showcasing a CLM program’s AI module. Representatives will often run templatized master service agreements (MSAs), non-disclosure agreements(NDAs) and rote contracts through the AI module. The technology then swiftly and neatly organizes and executes redlines, clause playbooks and more off of the vendor’s arbitrary standards—much to the delight of prospects.
As helpful as these straightforward demos can be in showcasing what is possible, vendors can foster client trust and confidence further by introducing the AI module to a prospect’s routine documents. Therefore, vendor representatives should request sample documents from the client’s software selection committee before a product demo to achieve this.
The purpose of any sales presentation—for CLM software or other legal tech platforms—is to show clients that a given solution can help them manage their business problems. After the vendor reviews a prospective purchaser’s MSAs, NDAs and other documents, its sales team can adequately process them into the CLM system, update the AI module, and walk the client’s representatives through the process they did to get there. The result? A more cohesive and realistic presentation that shows what the CLM AI module can do and how it can help the prospect’s stakeholders.
That said, vendors can still use mock paperwork during sales; they just need to limit this to initial calls. In the introductory presentations that kick off the sales process, vendors can run their CLM AI modules through mock paperwork to offer broad strokes of their software’s built-in capabilities and high-level discussions over how their proprietary software can tackle more complicated issues. But for a customer to truly understand how a vendor’s AI capabilities can improve and fit into their CLM ecosystem, the vendor has to take that additional step in subsequent presentations to show how their CLM’s AI can meet a client’s objectives.
Steps law firms and companies can take to bring CLM AI modules up to speed
Potential CLM software customers must also better prepare themselves for a hands-on, all-encompassing software hunt. Too many companies overlook the steps necessary to ensure their CLM software purchase process—and ensuing deployment—proceeds smoothly.
Before a company decides on a CLM investment, its stakeholders and software purchasing committee must enter every meeting with a clear understanding of what they want their next CLM to accomplish, AI capabilities included. From this vision, stakeholders must craft questions that can help them confirm whether the CLM’s AI/ML components will help usher in the necessary advancements and solutions to their lifecycle management bottlenecks, redlining needs and other issues.
If followed, this step can save prospects valuable time as they sift through their CLM options. During sales presentations, prospects can leverage internal research and discussions they have already performed to prepare guidelines and requirements for a vendor’s review. They can also ask how a vendor’s AI can respond to specific use cases and scenarios.
This preparation also helps a CLM vendor assess whether the prospect would be a proper fit, or if their requirements would not line up with the module’s actual capabilities. Vendors could adjust their guidance and pitches to better cover the prospect’s priorities, recalibrate unrealistic expectations and troubleshoot alternative paths for meeting particular objectives. By putting in the necessary legwork early on, prospects and vendors can grow and evolve together in creating solutions and plans that better accommodate the business needs of prospects.
Fine-tuning ML initiatives to ensure the AI module meets an individual company’s objectives
These principles and considerations also carry into CLM deployments—especially the ML processes that help Ais deliver the white-glove experience customers desire. Clear communication is critical to successful, long-term CLM software adoption. Transparency and proper expectation-setting practices can avoid unwelcome surprises—all while helping prospects conceptualize what they must commit to in getting a vendor’s AI module up to speed with stakeholder preferences.
To accomplish this, vendors and prospects must build on the parameters established during the sales cycle. When prospect teams convene with the vendor, they must come prepared with complete project and design requirements for the vendor to review. From there, the vendor should advise decision-makers on applicable gaps between their expectations and what the AI module could realistically deliver, and clarify the parameters around what the vendor’s AI capabilities can offer.
For the vendor, this process may not result in a fluid presentation and sales process, and may force them to work harder to secure commitments. For the client, the consultation journey could upend their beliefs on what they can accomplish with their next CLM platforms and open their eyes to the challenges ahead. However, all parties involved must put these possibilities to the wayside; the benefits of ensuring all parties are on the same page will only facilitate better buy-ins, level-headed expectations and improved customer feedback throughout the implementation and deployment processes.
The importance of cohesion and preparation in bridging AI-related misunderstandings
While the CLM AI modules of tomorrow will likely expand upon current capabilities a hundred-fold (if not more), it is vital for today’s CLM customers to fully understand the AI functionalities they plan to invest in today. Without full knowledge of what they are buying, prospective customers are only setting themselves up for failure. Vendors must shepherd this process carefully, and do whatever they can to help prospects predict how specific CLM software will fulfill particular needs.
Customers and vendors must put in additional work to ensure they are as transparent and straightforward as possible with their CLM objectives and capabilities. Only by doing this can customers realize the full benefits of existing CLM software and set themselves and their vendor relationships up for success.
Jim O’Hare is Vice President of CLM Services at LegalEase Solutions LLC. He shares his 22 years of hands-on experience in helping organizations understand how CLM best integrates into their enterprise and assisting stakeholders struggling with CLM vendor implementations.
Reprinted with permission from the June 20, 2023 edition of “LegalTech News” © 2023 ALM Media Properties, LLC. All rights reserved. Further duplication without permission is prohibited. ALMReprints.com – 877-257-3382 – firstname.lastname@example.org.