Want to get the honest no bs scoop of what happened at the Gartner Data & Analytics in Orlando, then this short and sweet episode is for you. This was an impromptu recording where Sanjeev Mohan and Ryan Dolley join Juan and Tim to share what they learned.

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Juan and Tim rant about whats on their mind going into Gartner Data and Analytics conference: "Context" is going to be the word of the week, The Execution Gap, Decision intelligence might be the bridge and the thing nobody's talking about yet: context lock-in.

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The Human in the Loop | Ethical AI with Di Le
ServicveNow Insights Podcast - hosted By Bobby Brill

What does it actually mean to build AI responsibly? Not the buzzword version. The real version. In our latest episode, I sat down with Di Le — AI Ethicist and Human-Centered AI Strategist at ServiceNow — and she broke it down in a way I hadn't heard before.

Most people use Ethical AI, Responsible AI, and Human-Centered AI interchangeably, and Di breaks down exactly where each one lives and how they apply to building AI that aligns with our societal values. Fairness. Transparency. Bias. Beyond evaluation and technical talking points, these are also design decisions with real consequences for real people — and operationalizing them is harder than most organizations want to admit.

One line from Di that stopped me: "People have crossed oceans and built monuments in honor of our capability to think. And I just want people to preserve that and not surrender it so freely." That's the episode in one sentence.

To learn more about Ethical AI and reseatch from Di Le and more - https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1020&context=sighci2025

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1025&context=sighci2024

https://www.youtube.com/watch?v=QhVY-85A-Wk&t=5s

ServiceNow Insights Podcast 🎧 The Human in the Loop — now available wherever you listen to podcasts.

0:00 – Introduction & Di Le's Background
1:35 – Is Ethical AI Just About Preventing Skynet?
2:22 – Responsible AI vs. Ethical AI vs. Human-Centered AI
6:34 – Why All Three Are Deeply Interconnected
8:39 – When "Amazing" Tech Goes Wrong: The Adobe Example
10:07 – Fairness, Transparency & Accountability Explained
12:06 – The Mug Factory: Understanding Bias in AI
14:52 – Transparency & Interpretability in AI Design
16:48 – Keeping Humans Genuinely in the Loop
18:06 – Accountability & Human Oversight
20:39 – Why Bias Isn't a Bug You Can Just Fix
22:30 – How ServiceNow Approaches Responsible AI
23:11 – Why Di Chose ServiceNow (The Origin Story)
27:09 – One Thing Everyone Should Do With AI 28:38 – Closing

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Most data and AI initiatives don't fail on technology — they fail on meaning. In this episode, Juan and Tim chat with Säde Haveri, who makes the case that metadata is the bridge between systems and people: the language and structures that help humans understand, trust, and use data in their daily work. Her focus isn't on building smarter pipelines, but on turning complexity into shared understanding so that data actually drives decisions and behavior change. Because if your data doesn't speak your language, it simply won't work for you.

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AI is transforming how businesses operate and how early-career talent grows. In this episode, UTG Unlocked, Mark Stockford (GVP, Global Cloud Operations) and Alyssa Gerhart (former intern, now full-time employee) share how AI is reshaping work at ServiceNow—from strategic impact to day-to-day execution. Our guest hosts Jorden Shelton and Cynthia Mathenge guide the conversation and explore real AI use cases like Unity, RAG-based duplicate detection, and intent detection, while emphasizing the importance of critical thinking and strong fundamentals.

In this episode, designed not just for recent interns, you’ll learn how AI is expanding career paths, how teams like Global Cloud Services power innovation behind the scenes, and what interns and early-career professionals can do now to grow: stay curious, use AI intentionally, seek mentors, and don’t just consume—contribute.

UTG is the engine behind the scenes here at ServiceNow — enabling innovation, maintaining production environments, supporting internal teams, and driving operational excellence. It connects strategy to execution by combining engineering, cloud operations, and technology operations to deliver stable, high-performing systems that allow the business and customers to succeed.

For more information about the Early Careers program visit - https://careers.servicenow.com/early-careers/

00:00 Welcome & What ‘UTG Unlocked’ Is All About 
02:50 Meet the Panel: Mark, Alyssa, Jorden & Cynthia 
04:29 Segment 1: How AI Is Impacting the Business (Customers vs. Employees) 
06:26 Skills That Matter in an AI-Powered Workplace 
09:52 Real AI Use Cases: Unity, Agents, and Faster Ops 
13:57 AI and Career Growth: New Roles, New Paths, Partnering with AI 
18:56 Advice for Early-Career Talent: Stay Curious, Build, Contribute 
20:41 Segment 2 Kickoff: Rapid-Fire Fun
28:50 Pulling Back the Curtain: What is GCS
30:37 GCS as a Superhero: Operating in the Shadows Like Batman 
31:35 The Hidden Work: Solving Customer-Created Problems & Root-Cause Hunting 
33:37 Alyssa’s Journey: Intern to FTE, Mentorship, and Scaling Developer Productivity 
35:38 What’s Next: Emerging Tech on the Radar (AI to Quantum Computing) 
37:15 Closing Takeaways: Keep Learning, Use AI Wisely, Ask Questions, and Give Back 
40:12 Final Words & Where to Learn More

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This is the takeaway episode with Säde Haveri where she makes the case that metadata is the bridge between systems and people. Most data and AI initiatives don't fail on technology — they fail due to the lack of meaning. If your data doesn't speak your language, it simply won't work for you.

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Juan and Tim are back for a LIVE episode with Nachiket Mehta, an experienced data leader who has lived and breathed the “shift left”. In this episode we unpack how ontology, events and culture unlock enterprise AI.

We discuss the gap between what your systems think is happening and what's actually happening on the ground and dive into real world examples: a trailer with expensive merchandise sat forgotten in a yard for weeks. $35M in delayed orders. The math added up, but nobody saw it coming. Why? Because we're obsessed with cleaning data and building dashboards, but nobody mapped the happy path vs. the exceptions actually happening on the ground. What is delivery when the customer isn't home? What's "lost in transit" versus "sitting in our own yard"?

The solution? Send your ontologist to the fulfillment center. Build tiger teams. Shift your data teams left to act like software product teams. And most importantly: connect the five why's back to your OKRs, or you're just building features nobody needs.

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This is the takeaway episode with Nachiket Mehta, an experienced data leader who has lived and breathed the “shift left”. In this episode we will unpack how ontology, events and culture unlock enterprise AI. We discuss why your ontologist needs to visit the fulfillment center, how to shift data teams from afterthought to proactive partner, and why the five why's matter more than your tech stack.

See omnystudio.com/listener for privacy information.