AI Radicals

Data quality problems don't just create bad reports; they create mistrust. And once trust is gone, people stop using your systems and start building their own workarounds.

In this episode of AI Radicals, host Satyen Sangani sits down with Erin McIntosh, Vice President of Global Data Operations at CNA Insurance, to talk about what it actually takes to modernize data governance at a global commercial insurer in the age of agentic AI. Erin shares how CNA is rethinking decades-old governance playbooks, why "build vs. buy" decisions have been upended by new AI tooling, and how her team is shifting from automating decisions to actually improving them.

Erin also opens up about the hardest part of leading transformation at speed: getting an organization to trust new systems, rebuild processes from the outcome backward instead of the process forward, and move from slow, bureaucratic governance to agentically-led governance that can actually scale.

"Good data governance is actually effective. Bad data governance is actually slow and burdensome."

Listen to this episode to learn:

Why the shift from automating decisions to improving decisions is where real AI ROI comes from

Why agentic governance—not more process—is the path to finally scaling stewardship, compliance, and data quality

Why seeking perfection instead of progress is the biggest waste of time and money in AI deployments today

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“ Each person had to learn which version that they wanted to trust and which one they wanted to use based on their own experience. That became the system of finding the right pieces of information that helped their story. That's really when it clicked for me that this isn't just a data problem, and it wasn't just a reporting problem, and it wasn't just a technology problem. It was a trust problem. Once trust is gone, people don't stop working. They really just build their own version of reality.” – Erin McIntosh

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Time Stamps

*(04:00): A year of rapid transformation—modernizing BI and third-party data at CNA

*(13:52): Automating a decision vs. improving a decision—and why that distinction matters

*(20:41): Why AI's fidelity comes down to governed context

*(28:48): Building an agentically-led governance organization

*(35:02): Quick hits: AI's biggest misconceptions, wasted effort, and governance myths

*(36:26): Satyen’s takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

Connect with Erin McIntosh on LinkedIn

Learn more about CNA Insurance

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AI can write code faster than ever. But what if code is no longer the hard part?

In the premiere episode of AI Radicals, host Satyen Sangani is joined by Mark Nelson, Venture Partner at Madrona and former CEO of Tableau, to explore what AI is actually changing—and what remains fundamentally the same about building great software and great businesses.

Having led companies through the rise of databases, cloud computing, SaaS, and self-service analytics, Mark offers a rare perspective on today's AI boom. He explains why judgment and customer understanding are becoming the new competitive advantage, why enterprise buyers are shifting from AI experimentation to demanding measurable ROI, and why today's token-based pricing models may be rewarding the wrong behavior.

"Code is easy to generate. Great software isn't. The bottleneck has shifted to understanding what to build."

Listen to this episode to learn:

Why generating code is no longer the bottleneck – but building great software still is

Why enterprise AI is entering an ROI-driven phase where customers expect measurable business value

Why the next generation of AI companies will win by understanding customers, not just building better models

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“ We all come with towering strengths and our own weaknesses. Not just being a product person, not just being an engineer, not just being a salesperson, all of those skill sets. One thing I'll always say about any founder that is true is like, Do you understand your customer? Do you understand what you're solving and why? Do you really kind of first personally feel that pain? Understanding who they're building for and what problem they're solving for.” – Mark Nelson

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Time Stamps

*(02:21): Why AI is different from every technology wave before it

*(07:48): AI won't replace judgment—and that's what matters most

*(12:17): What venture investors are really looking for in AI founders

*(20:27): AI makes code cheap—but great software is still hard to build

*(30:18): Enterprise AI moves from experimentation to ROI

*(35:15): Why token-based AI pricing is due for a reckoning

*(45:19): The future of enterprise software and the next AI winners

*(54:06): Satyen’s takeaways

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://caspianstudios71626.activehosted.com/f/73

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

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Links

Connect with Mark Nelson on LinkedIn

Learn more about Madrona

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

AI Radicals is back for Season 4 — and trust in AI has never been more contested.

This season, host Satyen Sangani, CEO and co-founder of Alation, sits down with leaders, builders, and operators working at the edge of AI transformation to ask the question everyone's dancing around: can we actually trust the systems we're building? New conversations dig into data quality, governance, and the feedback loops that separate AI that works from AI that just demos well.

If you care about making AI matter inside your company, your team, or your own career — Season 4 starts July 29, 2026.

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Sponsor

This podcast is presented by Alation.

Learn more:

* Subscribe to the newsletter: https://www.alation.com/podcast/

* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/

* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The future of business intelligence is being rewritten. Have you ever wondered how AI will unlock the power of unstructured data?
In this episode of Data Radicals, host Satyen Sangani is joined by Chris Aberger, newly-minted VP at Alation to discuss building AI-powered data workflows.
A startup pioneer, Chris explores the importance of metadata in enhancing AI applications within organizations, the significance of quick iterations, and the evolving role of AI engineers.
“ That two-step realization is what's causing a lot of this activity that we're seeing in the market, which is, I know I need to plug into databases. I'm now coming to terms with the fact that this is actually a really tough problem to get right.”
Listen to this episode to learn:
Why metadata curation and feedback loops are crucial for making AI effective
The necessity of a fast-paced, iterative approach in developing AI solutions
How to enable end-users to become builders through AI and metadata tools
Listen now: alation.com/podcast/episodes/ai-builders-metadata-chris-aberger
*Satyen’s narration was created using AI
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“People have realized that, okay, like structured data is actually like the hard problem to get right. And all these organizations' really valuable data is inside their databases in the structured formats. We have to figure out how to make this ready for the AI era. And then the kind of second level problem that people are discovering is how do I make this structured data actually work? Oh, it's metadata. And I think that realization that that kind of two-step realization is what's causing a lot of this activity that we're seeing in the market, which is, I know I need to plug into databases. I'm now coming to terms with the fact that this is actually a really tough problem to get right. In order to get it right, I need to effectively go build a data catalog or metadata provider, and therefore we're seeing a lot of activity in this space.” – Chris Aberger
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Time Stamps
*(02:04): From the Stanford AI Lab to founding Numbers Station
*(12:10): From chat with your data to act with your data: From data users to business builders
*(19:23): The value of metadata to production-ready AI
*(28:46): What are precision agentic workflows?
*(35:35): Empowering enterprise data users to build with AI
*(45:50): Satyen’s takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
* Subscribe to the newsletter: https://www.alation.com/podcast/
* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
Connect with Chris on LinkedIn

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In the luxury world where artistry is key, how is AI enabling personalization, optimization, and speed?
In this episode of Data Radicals, host Satyen Sangani is joined by Julie De Moyer, Chief Data Officer of LVMH Beauty to break down the role of data and AI in business transformation.
A seasoned strategist and leader of innovation across 15 beauty brands, Julie shares practical examples of AI application in various aspects of LVMH's operations, from product development to supply chain management.
“ The AI is often the cherry on the cake. We're moving towards those new technologies that are helping us dream even bigger.”
Listen to this episode to learn:
The importance of collaboration, change management, and consumer-centric approaches.
How to work closely with CEOs to drive meaningful data-driven decisions.
How to balance AI and human creativity within the luxury beauty industry.
Listen now: https://www.alation.com/podcast/episodes/lvmh-data-ai-strategy-julie-de-moyer
*Satyen’s narration was created using AI
**LVMH is vendor-neutral and this does not constitute an endorsement
**All views and opinions expressed by the speakers are their own
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“ If you look at the making of perfumes or the way we actually make the wines, in other industries, we would use the AI in order to help those, I would say, those scientists to go faster, to optimize their trials. It will never replace the final scent or the final product that is decided on, but it can help with the substitutions of products that might need to go out, as a result of regulatory changes. It might also help with making sure that the quality of the products last as long as possible. We really help those researcher scientists do their job better and easier.” – Julie De Moyer
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Time Stamps
*(01:34): Julie’s background: From economics student to technology leader
*(07:55): AI in action: How stakeholders collaborate
*(14:42): The role of data in luxury today (and 5 ways to apply AI in retail)
*(22:09): Leading data in a multi-brand environment
*(28:18): How to become a trusted AI leader: Key tips
*(33:40): Satyen’s takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
* Subscribe to the newsletter: https://www.alation.com/podcast/
* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
Connect with Julie on LinkedIn

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.