How are generative artificial intelligence (GenAI) tools being integrated into consumer product companies? Do they improve product development, marketing strategies, and customer service? How do they impact labor productivity? And what other functional enhancements can GenAI provide across an organization?
To address these and other business questions, we recently convened a roundtable of executives within the Twelfth District, with representation from a multinational consumer and professional cleaning products company, a shoe and apparel company, a global agricultural company, and a wholesale distributor of foodservices and retail products.
The executives met with Mary C. Daly, President and CEO of the San Francisco Fed, Sunayna Tuteja, Senior Vice President and System Chief Innovation Officer for the Federal Reserve System, and Kevin Ortiz, co-head of the EmergingTech Economic Research Network (EERN). Roundtable discussions like these are a centerpiece of the EERN initiative. A partnership between the SF Fed and the Federal Reserve System Innovation Office, EERN supports a better understanding of how new technologies like GenAI are shaping the economy of the future.
GenAI Adoption and Integration
Kicking off our roundtable discussion, we asked the participants how quickly or slowly GenAI is being adopted and integrated into their business. The executives reported varying speeds and stages of integration, with each noting that GenAI is functioning as an accelerant to technological change within their organizations. One executive said their company is on the faster end of GenAI adoption within their industry and is now operating twice as fast as it did two years ago. Other executives said their companies are in the early stages of adoption but are already seeing the benefits of scaling up productivity, not by reducing workforce but by augmenting tasks performed by current employees. They mentioned the importance of developing programs for training employees on how to use GenAI, noting that different roles saw varying degrees of usefulness from the tools. Most of the executives said they’re using off-the-shelf GenAI applications and some said they were also performing varying levels of data science and machine learning in-house.
Product Development Enhancements
The executives shared specific examples of how GenAI is improving product development and marketing strategies. One executive noted the time to deploy a product line had been reduced by more than half, translating to lower costs and more time for employees to interact with customers, gather information, and focus on marketing efforts. Another executive echoed similar time-savings, noting that the previous design phase involved manufacturing samples and shipping them across the world to test them. GenAI has now sped up the design feasibility process and expanded their understanding of what’s possible earlier in the process. Several executives said they are also using GenAI to gather and interpret insights from clients and customers more efficiently, which helps them identify product solutions they should develop. They noted that GenAI also helps with content personalization in marketing. One executive said they used a large language model to design a new product name that proved highly receptive with customers.
Overall Business Efficiencies
Several executives discussed operational efficiencies gained by using GenAI. One noted the benefits in financial accounting, observing that its accountant team is now more productive and efficient, making the need for additional accountants unlikely. Another executive said their information technology team and finance team are leveraging GenAI to scale tasks more effectively. An executive in the agricultural space noted their company is using AI in three key areas: (1) research and development of new crop varieties; (2) agronomy support for farmers in multiple countries; and (3) legal and intellectual property (IP) enforcement by analyzing contracts at scale. Other executives also addressed IP concerns, commenting that proprietary company information leakage is a risk they need to monitor. An executive noted that they do not conduct anything related to GenAI outside of their firewall in order to protect IP. Overall, each of the executives expressed optimism that GenAI would continue to accelerate the pace of productivity gains across their organizations.
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The views expressed here do not necessarily reflect the views of the management of the Federal Reserve Bank of San Francisco or of the Board of Governors of the Federal Reserve System.