How Law Firms are Upping Their Business Game with AI

Ray Meiring
Written by Ray Meiring / Jul 19, 2021

I lead QorusDocs’ award-winning team of professional problem solvers to create the absolute best customer experience possible. My background in software development and starting new business ventures gives me the ability to oversee projects at every level.

Interest in Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) is on the rise, especially when it comes to streamlining and automating proposal and RFP response management. With an increase in RFP requests, business development teams at law firms are turning to automation tools to help bridge the gap between the greater number of opportunities and lower win rates.  

Unfortunately, many modern law firms’ business development teams don’t have the capacity to grow their headcount and are limited by remote working realities. To keep pace with the constant flow of RFP requests, legal firms need tools that will pick up the slack and automate processes at the same time—and they need to understand how to leverage these tools to close more deals. 

QorusDocs CEO, Ray Meiring, recently published a series of articles themed around “AI in proposal management” in ALM’s Law Journal Newsletter (LJN) which focused on marketing the law firm, as well as general security and technology topics. In his latest installment, Ray shares a series of practical AI takeaways for law firms’ business development and proposal teams: 

Law Firm Marketers: Leveraging AI for Results 

AI is about eliminating mundane tasks, augmenting human touch points, and amplifying human ingenuity. This applies equally to content, documents, and workflows utilized by legal marketers and business developers. The goal is to embed innovations like AI, ML, and NLP into everyday tasks around the proposal management and RFP function to the point that they become ubiquitous. 

As mentioned in a Legaltech News “Predictions in AI” article in January, AI will continue to embed itself into daily work; law firm marketing and business development are no exceptions. It will help teams win deals by learning ‘what content is winning content.’ When pitching clients, AI will recommend the best content for a specific pitch. AI will increasingly help law firms to automate RFP responses and will take care of some of the manual work of tagging content so it can be found later. 

AI can help as part of automating the RFP response process. The technology that underpins this automation will help address higher volumes. Additionally, AI can be leveraged to help recommend responses and, in many instances, also help increase future RFP win rates. The system will train itself over time. 

Intelligent proposal management systems use NLP to answer questions that often appear within RFPs. Combined with NLP, AI reads specific questions and selects appropriate answers based on what is needed for specific sections of a proposal or RFP. Each answer is scored based on how appropriate the content is when mapped to the questions. The AI system will learn and improve over time, even when a manual answer or addition is more appropriate. This alleviates the need to run painstaking content searches or scour individual databases to assemble responses. 

Digging Deeper 

Innovative law firms are starting to use AI to pick up elements of their pitch data and then use AI tools to prevent users from having to actually take the steps of searching. Rather, the system recommends: “Hey, you should use these five buyers and these six experience records in your pitch because they are relevant to what you’re pitching and, based on past performance, they are helping win deals.” The data points are there: who won this pitch, who lost that pitch. As a result, AI can be used to build a really strong recommendations engine. 

Although enterprise search is still the norm when it comes to finding content, with these intelligent systems, the first step is not that you need to search, rather that AI will recommend the track to pursue. So, you eliminate the search, and use searching almost as the exception rather than the rule. The first step is: “Here are the buyers you should use,” based on AI-powered recommendations. Users can, of course, still employ search tools, but these should be secondary, almost used in a back-up capacity. 

Predictive Pitching 

The other area that technologists are working on is predicting what the likelihood of winning an RFP is. This can be vital. Putting a professional RFP response together for high stakes legal work could cost $100,000. It can be immensely expensive to respond to an RFP because of the cost of the hours of the people involved and other resources, so you don’t want to spend those hundred thousand dollars if you’re not going to win that deal. 

Predictive analytics can make determinations, such as, “The probability of winning based on all of these factors is X.” It’s all about collecting various factors and doing predictive analytics in order to say, “What should you pitch? Or what shouldn’t you pitch?” In this scenario, knowledge is definitely power. It’s about recommending the right content at the right point in the sales cycle and recommending the personalization of the content. These inputs and uses are driving the machine learning to recommend more accurate content and, over time, winning content. 

AI: No Silver Bullet 

One of the most productive (and realistic) ways to embrace AI is to view it for what it is: an enabler and facilitator, a silent contributor—not a silver bullet that will solve all problems. 

As an attorney or firm client, you shouldn’t actively know that you’re dealing with AI; as it silently does the “heavy lifting” in the background, you know it’s helping you make better decisions, helping you do things faster. Business development and proposal teams at law firms should be saying, “My technology is the same, but now (and thanks to AI and ML running in the back), instead of me having to do 20 clicks to find something, the system is coming back and saying, ‘Well, here are the things that you should have right now.’” And the system knows this because it’s crunched so much data in the background, based on patterns and history, that it can make data-driven recommendations. 

To learn how to win more business by leveraging AI to automate and accelerate your RPF response process, request a demo of QorusDocs AI-enabled proposal management platform.