Make AI Work More Than 5% of the Time
Key Takeaways:- Learn why most generative AI projects fail—and how to make yours succeed.
- Understand how to assess risk, reward, and ROI in AI initiatives.
- Discover best practices for delivering AI projects that reach production and create value.
Description
Despite the hype around generative AI, most projects never reach production. A recent MIT report found that 95% of AI initiatives fail to deliver tangible results—often due to unclear ROI, misaligned expectations, or poor integration. The good news? You can beat the odds with the right approach to strategy, governance, and delivery.
In this panel interview, a group of AI researchers and industry practitioners, will discuss what separates successful AI implementations from the 95% that never make it. You’ll learn how to evaluate risk and reward, measure ROI effectively, and adopt practices that increase your organization’s AI success rate.
Presenter Bio
Lexi is building Lanai, an empowerment platform for human-Gen AI collaboration. She has two decades experience in technology leadership. Lexi ran for United States Senate Candidate for the State of California in 2023-24. Previously, she was Executive In Residence at General Catalyse, Chief Operating Officer at Gusto, and VP of Global Programmatic Platforms at Google.
Jim is a leading technology strategist and serial entrepreneur. At hybrid cloud platform Nasuni, his work focuses on the development and implementation of the company’s Data Intelligence and AI strategies. His most recent startup, data management company Storage Made Easy, was acquired by Nasuni. Jim also writes for the AI think tank Senior Executive.
Rajeev runs AI-assisted RevOps Platform MediaMint. He has three decades of experience as a technology executive, across machine learning and AI, technology, and media. Previously, Rajeev was CEO at user experience platform Headspin, and a Group Technology Officer at Accenture.
Jon runs the machine learning and AI team at materials science company Albert Invent. His work involves constructing large scale cloud data science architectures and generative modeling. Previously, Jon was Director of Vision Technologies at edge voice control company Sensory and Principal Data Scientist at identity management platform TruU.