The benefits of artificial intelligence to meeting planners have become evident very quickly. The proof: It’s taken less than six months for the ChatGPT tool to help planners spend only a few minutes on creating catchy session titles and descriptions, finding relevant speakers, creating targeted marketing messages, and more.
Given that the holy grail for associations is to be the source of year-round learning and networking opportunities for their professional communities, one of the latest A.I-powered offerings holds big potential because it is aimed directly at that goal.
At Wall Street firm Goldman Sachs, an internal incubator program for start-up ideas has created an A.I.-based product called Louisa. According to this CNBC article, it’s a networking platform for employees or professional-community members that creates detailed user profiles from the organization’s database as well as LinkedIn and other outside databases. From there, Louisa, recently spun off as an independent company, identifies job- and topic-related commonalities between people, and then draws on millions of published articles to proactively connect people who might benefit from knowing each other and interacting on a topic.
Rohan Doctor, CEO of Louisa, says that professional-service firms like Goldman Sachs rely on the expertise and contacts of their employees, but there’s a limit to how many colleagues anyone can know through their own efforts. “This is costing companies billions of dollars in terms of missed opportunities, disconnected colleagues, and fractured client experiences,” he said in the CNBC article. Doctor has already signed up a few clients besides Goldman Sachs to use the tool.
If associations could use a product such as Louisa to find topics of interest to individual members and routinely connect members to each other based on mutual interest, the value of associations both to members’ immediate work and their long-term careers would rise greatly. And as the A.I space becomes more competitive, the cost of such an application could become feasible for associations before long.