PODCASTS

Why Flawless Foundational Data is the key to AI
long term success and sustainability

This podcast episode features a discussion between Chris Detzel, Director of Customer Engagement and Community at Reltio,  Manish Sood, the CEO and founder of Reltio, and Sharath Katipally, a former chief data officer at J.P. Morgan who previously worked at Amazon and SoftBank.

Sharath's Career Path:

  • Started in data due to visa limitations, but found passion in the field.
  • Worked in consulting, boutique firms, and large organizations like HSBC, Brightstar, Amazon, and J.P. Morgan.
  • Gained diverse experience in financial services, retail, and tech.

Key Differences Between Companies:

  • Amazon: High-touch, low-margin B2C business with rapid iteration and tech focus.
  • J.P. Morgan: High-touch, high-value B2B business with slower pace and focus on regulatory compliance.
  • Data Structure: Tech companies tend to be decentralized, while traditional institutions are more centralized.

Challenges as a Data Leader:

  • Balancing regulatory compliance with innovation, especially in AI.
  • Bridging the gap between tech-savvy and data-savvy leaders.
  • Ensuring the quality and accuracy of foundational data for reliable AI outcomes.

Predictions for the Future:

  • Data and AI will become inseparable functions.
  • The focus will shift from the "four V's" (volume, variety, velocity, veracity) to the "four P's" (prediction, precision, productivity, personalization).
  • AI success will depend heavily on accurate and well-curated foundational data.
  • Continuous improvement, experimentation, and a culture of innovation will be crucial.

Sharath's Advice:

  • Combine data and AI strategies for optimal results.
  • Invest in modern data compliance and tool stack companies.
  • Focus on data product innovation and rapid prototyping.
  • Foster a culture of experimentation and justify its importance to stakeholders.

Overall in this podcast Sharath's career, leveraging data and AI strategically, issues to expect with AI adoption, and an AI startup he is advising. The key theme is the critical importance of high quality, trustworthy data as a foundation.