Can unstructured, uncleaned data serve as fodder for Gen AI?

The GenAIrous Podcast

In this episode, Amit Padalkar and Deepak Sharma dive deep into the debate between industry-agnostic and domain-specific Gen AI use cases, explore whether companies should invest in developing their own large language models (LLMs), and reveal how small businesses are making bolder moves compared to large enterprises. They also highlight the rise of Gen AI sprints, discuss key metrics for tracking Gen AI initiatives, and emphasize the crucial role of a solid data foundation. Tune in to uncover the secrets to running smarter tech operations, thriving businesses, and delivering exceptional customer experiences—don’t miss out!

As Chief Client Strategy Officer at Photon, Deepak owns and drives client success, strategy consulting and the pre-sales group between US and India. He has over a decade of experience in customer success across multiple companies and industries along with deep operational expertise. He also co-leads the Gen AI strategy and academy at Photon and manages the Gen AI accelerator offering that has seen 85%+ success rate in the market. He is a regular speaker on customer success and AI. Amit Padalkar is Senior VP, Customer Success at Photon. He is a Business Development professional with experience across the high tech value chain in different segments such as Wireless, Mobility, Semiconductors, Media, Healthcare, Hospitality & Gaming. Amit is experienced at both in selling high tech engineering solutions as well as building IT businesses.

02:57 The Impact of Gen AI on Business Transformation

08:07 Enterprise Productivity and the Role of Gen AI

10:37 Measuring Progress in AI Initiatives

13:37 Evolving Skill Sets for AI Implementation

20:56 Upskilling Boards & CXOs

24:18 Hiring in the Gen AI Era

26:41 The Importance of Data Foundation in AI