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The Adoption Path for Generative and Predictive AI with Jean Roberts, CTO of DataRobot

Jean Roberts is the field CTO of financial markets at DataRobot and shares her experience on technology adoption, transformation, and AI, both predictive and generative. She has had an unconventional career path, transitioning from investment banking to pursuing a Ph.D. in strategy and applied stats. Her journey led her through various roles in the financial sector, touching on investment banking, equity research, and data science teams, where she leveraged NLP on doctor's notes to predict stock movements. Jean emphasizes the importance of having a non-traditional background, allowing leaders to empathize with clients and build credibility.

Rob and Jean talk about the challenges of data adoption, particularly in large companies with outdated technological infrastructures. Modernizing tech stacks is crucial for making informed, data-driven decisions, but it often poses difficulties for established organizations both from a culture perspective and a technology perspective. Jean highlights the cultural shift required to convince leaders to view technology as a profit center rather than a cost center and the changes involved in implementing AI and data science solutions within organizations.

The two talk and compare the quick adoption of generative AI compared to predictive AI. Jean attributes this to the accessibility factor which has made generative AI more appealing and easier to understand, thereby making it more appealing for executives to want to integrate and adopt. However, she cautions against blindly accepting generative AI responses, stressing the need for companies to understand the technology's limitations and potential risks.

Jean helps explain the difference between predictive and generative AI, and their applications to different problems. Defining the problem and understanding whether the solution requires predictive or generative AI is crucial. Jean recommends experimenting with generative AI cautiously, comparing it to a child's birthday party at a bowling alley with bumpers to prevent undesirable outcomes.

The conversation concludes with a reflection on the personification of AI and the potential dangers of assigning human-like qualities to these tools. Jean stresses the importance of understanding the technology's limitations and encourages teams to focus on solving specific problems rather than being swayed by the hype surrounding generative AI.

Listen to the full podcast episode here:

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