Data and AI Exchange (DAX) by Unolabs

Data and AI Exchange (DAX) by Unolabs
Podcast Description
Welcome to Data and AI Exchange (DAX) by UnoLabs – the podcast for bold conversations in AI, data science, and enterprise tech. Hosted by Akshay Raj and Prateek Tandon, we explore the real stories, use cases, and controversies behind AI’s rise — from prompt engineering and agentic AI to ethical dilemmas and automation trends.
Expect:
– Deep-dive episodes (2x/month)
– Expert interviews and hot takes
– Enterprise use cases and career insights
– Shorts that simplify complex topics
Podcast Insights
Content Themes
The podcast focuses on contemporary themes in AI, data science, and enterprise technology, exploring use cases and ethical dilemmas; highlighted episodes include discussions on Vibe-Coding in banking, the implications of AI agents in workplace efficiency, and the evolution of roles due to agentic AI.

Welcome to Data and AI Exchange (DAX) by UnoLabs – the podcast for bold conversations in AI, data science, and enterprise tech. Hosted by Akshay Raj and Prateek Tandon, we explore the real stories, use cases, and controversies behind AI’s rise — from prompt engineering and agentic AI to ethical dilemmas and automation trends.
Expect:
– Deep-dive episodes (2x/month)
– Expert interviews and hot takes
– Enterprise use cases and career insights
– Shorts that simplify complex topics
#agenticai #manager #podcast #salesforceEvery boardroom is asking the same question today: “Are we really ready for AI?”In this episode of Data & AI Exchange, we sit down with Hitesh Seth — Chief Architect at Salesforce and a veteran of large-scale Data & AI platforms — to explore what true AI readiness means beyond hype and pilot projects.From financial services to healthcare, Hitesh has helped global enterprises design AI roadmaps, integrate data platforms, and build production-grade AI systems. Here, he shares how leaders can assess data maturity, governance, culture, and talent before scaling AI.What You’ll Learn: – Early signals of an AI-ready organization – How to separate AI theater from real business value – Why strong data foundations & governance are critical – Balancing quick wins vs. long-term AI bets – The non-negotiable roles & teams needed for success – How to measure ROI, fail fast, and pivot effectively – Why a growth mindset is key for leaders in the AI era00:00 – Opening & Introductions01:30 – Early Signals of AI Readiness03:00 – Digital Transformation as a Readiness Indicator04:30 – Data Journeys & Maturity Levels05:40 – AI Theater vs. Real Business Value07:30 – Predictive vs. Generative AI in Enterprises08:30 – What a Solid Data Foundation Looks Like10:30 – Governance & Data Ownership11:40 – Red Flags in Data Quality & Governance13:20 – Quick Wins vs. Strategic Bets15:00 – Talent, Leadership & Change Management16:00 – Before Approving AI Pilots: Tech, APIs & Security18:00 – Efficiency vs. Growth: The Business Value Test19:40 – Building Teams: Upskilling vs. Hiring Externally21:00 – Why Architects Are Critical in AI Readiness22:30 – Non-Negotiable Roles: Data Engineers, MLOps & Governance24:00 – Measuring ROI & Knowing When to Pivot25:30 – Fail Fast, Learn Faster: Lessons from Pilots26:30 – Growth Mindset & Continuous Reinvention27:10 – Closing Thoughts & Takeaways

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