Johnson & Johnson (J&J) has refocused its generative AI strategy, shifting from broad experimentation to a more targeted approach. Chief Information Officer Jim Swanson explained that this new strategy ensures resources are concentrated on the most valuable use cases while discontinuing projects that are redundant or ineffective.
After a year of experimentation, J&J abandoned its “thousand flowers” approach, where employees proposed nearly 900 AI use cases, many of which were ineffective. The company found that only 10% to 15% of these use cases were delivering 80% of the value. This realization led to a shift toward high-impact AI applications in areas such as drug discovery, supply chain optimization, and internal tools like an AI-driven chatbot for company policy queries.
Swanson emphasized that the new strategy reflects lessons learned from a year of experimentation and aims to prioritize scalability and business outcomes. One successful application, the “Rep Copilot,” helps sales representatives engage with healthcare professionals, and J&J is expanding this pilot across different business segments. Additionally, AI is being used to streamline employee interactions with services, reducing millions of annual inquiries.
As J&J continues refining its approach, Swanson noted that while broad experimentation helped identify valuable use cases, the key now is to focus on those that deliver tangible business results.
Source: Swifteradio.com
