VentureBeat Transform event this year put the spotlight on generative AI, a technology that has been causing significant shifts and generating both excitement and concern. During the event, top experts from various industries shared their experiences and discussed how they are leveraging generative models, such as ChatGPT, to enhance efficiency and customer experience. This technology is rapidly becoming accessible in many domains, enabling more individuals to utilize it in their everyday lives.
At the Women in AI breakfast panel, JoAnn Stonier, Chief Data Officer at Mastercard, compared the pace of generative AI to the Oscar-winning movie “Everything Everywhere All at Once,” emphasizing its rapid advancement. However, the panelists acknowledged the need to ensure that everyone can benefit from this technology. They stressed the importance of democratization and the inclusion of diverse perspectives to achieve equitable results.
Uljan Sharka, CEO of iGenius, highlighted the significance of adopting a human-centered approach in developing generative AI products. While current efforts mainly focus on technology, model size, and data size, Sharka emphasized the need to prioritize human needs. He emphasized that designing for human experience is crucial to ensure widespread adoption of this technology and avoid repeating past failures in adoption.
The Role of Data in Generative AI
Generative models heavily rely on abundant and high-quality training data. Ashok Srivastava, Senior Vice President and Chief Data Officer at Intuit, highlighted two essential aspects of a strong data foundation: clean data at scale and real-time data at scale. Intuit, a company that has long incorporated machine learning into its products, leverages generative AI through its operating system, GenOS. This system utilizes generative AI to deliver personalized experiences to customers. However, Srivastava emphasized that classic machine learning models still play a significant role alongside LLMs in their operations.
Mark Tack, CMO at TreasureData, and Gail Muldoon, Data Scientist at Stellantis, discussed the use of generative AI to accelerate personalization and gain deeper customer insights. Tack cautioned against falling into the trap of “shiny object syndrome,” emphasizing the need for clear objectives, strategies, and metrics before integrating AI. He advised organizations to slow down and establish a strong foundation to avoid potential harm.
Stellantis, the world’s third-largest automobile company, utilizes generative AI to transition to a full-online shopping experience. Muldoon explained how Treasure Data’s Customer Data Cloud facilitated anticipating customers’ shopping interests, enabling personalized product suggestions and a better understanding of customer preferences.
The Potential of Generative AI in Enterprise
While enterprises are still exploring the optimal use of generative AI, efficient access to information stands out as one of the immediate benefits. Sarah Hoffman, VP of AI and ML at Fidelity, discussed how gen AI is reshaping collaboration and defining workflows. For instance, interfaces that utilize text boxes instead of overwhelming web pages with multiple tabs enhance collaboration and streamline processes.
Generative AI also holds promise in fostering creativity, particularly in brainstorming sessions. The technology can be a valuable tool, enabling individuals to explore new ideas without concerns about hallucinations or impracticality. Steve Wood, SVP of Product and Platform at Slack, emphasized the role of LLMs in democratizing automation within organizations. Wood advocated for expanding access to automation and empowering individuals across the organization to build and automate processes, even if they are not perfect.
By integrating the knowledge stored in LLMs with the conversations on Slack channels, bespoke business intelligence can be unlocked for the users of the collaboration tool. Wood highlighted the existing productivity gains through such tools and emphasized the need to allow them to be discovered and utilized to their full potential.
Generative AI is revolutionizing industries across various domains. As this technology becomes more accessible, the focus shifts towards democratization, human-centered design, and leveraging high-quality data. Enterprises are beginning to realize the potential of generative AI in enhancing efficiency, personalization, and collaboration. By embracing this transformative technology, organizations can unlock new possibilities and stay ahead in an increasingly AI-driven world.
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