Author: Scott Litman, Capacity SVP & Formerly Founder of Lucy
In the two years since ChatGPT’s public debut, the conversation around knowledge management has intensified dramatically. Most recently I was at an AI summit featuring leaders from OpenAI, Anthropic, and other innovators. As these industry leaders talked about the practical applications of AI in business, the most frequent reference made was for the use of AI to save time by enabling employees with the right data at the right time.
Yet for Research and Insights leaders, this is hardly new territory.
Visionaries like Stephan Gans at PepsiCo have long championed the need to democratize data—ensuring that professionals across their organizations can access critical information as quickly as possible many years before the current wave of Generative AI brought these conversations into the mainstream.
Why Research and Insights Pioneered the Movement
Research and Insights teams sit at a unique crossroads within organizations. They are custodians of vast repositories of customer insights, market trends, and internal learnings—supporting stakeholders from product development to marketing to executive leadership.
The volume of this data is massive: hundreds of sources, countless formats, and volumes of information far beyond what any single person could possibly digest. Yet these teams are tasked with making sense of it all—curating, contextualizing, and activating knowledge to drive smarter decisions.
It’s no surprise that industries like Consumer Packaged Goods and Retail were among the first to seek new approaches. These sectors are drinking from a firehose of data about consumers and trends. Identifying critical insights to act on—and doing so quickly—has a huge impact on business performance. To meet this challenge, it became critical to have the best tools to help manage this.
From Early Innovation to Industry Evolution
Over the past eight years, solutions like Capacity’s Answer Engine (formerly named Lucy and now in its fourth generation) have emerged in response to this demand. Companies including PepsiCo, Church & Dwight, Colgate, GSK, Johnsonville, Kimberly-Clark, Kraft Heinz, Mars, Mondelez, P&G, Best Buy, Kroger, Target, Walmart, and many others have invested in knowledge management platforms—sometimes through Capacity, sometimes through other providers—as they realized the competitive advantage these tools offered.
While most of the Fortune 500 Retail and CPG companies have at least experimented with—if not fully deployed—enterprise AI solutions, a broader set of industries with similar challenges now stand to benefit. They’ll gain from the years of investment in the space, from products that have significantly evolved, and from the ability to harness the latest advancements from foundational AI companies—giving platforms like Capacity’s Answer Engine powerful new capabilities.
Looking Ahead
Research and Insights will continue to lead the way, but the frontier is expanding. As AI tools become more sophisticated and accessible, industries beyond CPG and Retail are recognizing the value of connecting fragmented knowledge at scale.
The opportunity ahead is clear: to leverage nearly a decade of applied AI learning to turn organizational knowledge into a true strategic asset—one that empowers every employee to move faster, make better decisions, and drive greater impact.