The Data Storytellers Podcast

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Jul 2026

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The Data Storytellers is a leading professional community dedicated to building business influence for data and analytics leaders. Our mission is to empower and enable Data Science & Analytics professionals and organizations to actualize their full potential. In the evolving landscape of business, Data Science and Analytics departments are emerging as a business within a business, driving strategic decisions and influencing outcomes.

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July 31, 20261 hr 3 min

Agentic Workflows and Foundation Models Inside the Enterprise | Nurtekin Savas (PayPal)

Returning a year after his first appearance, Nurtekin Savas draws on his expanded risk-infrastructure remit at PayPal to examine the design of agentic workflows, enterprise foundation models, and the data and organizational conditions needed to put them to use. Nurtekin Savas, Head of Global Risk & Servicing Infrastructure, Platforms, Data & AI (VP) at PayPal, joins Laszlo Mucsi to examine how enterprise AI can become part of the way decisions are made. His emphasis is on deliberate design: choosing valuable workflows, matching models and tools to each step, and setting boundaries on what agents can do. We also explore how enterprise foundation models can help establish a shared customer representation that supports many decisions through task-specific prediction heads. Throughout the conversation, Nurtekin explains the potential to simplify pipelines and speed deployment, alongside the talent, integrated data, and changes in data-science work needed to make that architecture useful. The conversation covers: - Agentic workflows with step-specific models, tools, and risk controls - Agentic operating systems for customer intent, routing, and permissions - Shared customer representations, prediction heads, and simpler model pipelines - The talent, data integration, and role changes required for adoption This episode is part of Enterprise AI: State of Play, a practitioner-led interview series on what enterprise AI looks like on the front lines. Connect with us: Website: https://thedatastorytellers.com/ LinkedIn: https://www.linkedin.com/company/the-data-storytellers Apple Podcasts: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476 Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa YouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters: 00:00 Enterprise AI: A Year in Review 08:39 AGI, Model Progress and Token ROI 14:08 From Models to Enterprise Intelligence 20:53 Agents, Workflows and the Agentic OS 28:46 Data and AI Platforms at PayPal 32:19 How Enterprise Foundation Models Work 42:34 Adoption, Explainability and Culture 54:18 Benevolent Bandwidth: AI for Good

July 9, 202647 min

Beyond the Model: Where Enterprise AI Value Is Moving

Episode description Taylor Black returns for a mid-2026 scorecard on the predictions he and Laszlo Mucsi made in their first conversation. They examine the shift from model breakthroughs to agentic systems that perform real work: coding tools finding product-market fit, autonomous software, small teams with outsized leverage, and the application layers where enterprise value is accumulating. Enterprise AI is moving beyond the contest to build the most capable model. The advantage now lies in the systems around it: the workflows, data, evaluations, deployment infrastructure, and human judgment that turn model capability into business outcomes. Agents can execute, but they do not carry trust, liability, or responsibility; AI-native operators must redesign the work rather than simply automate the old process. The central business question is no longer who has access to the best model, but who can turnmodel capability into proprietary workflows, faster execution, and measurable operating leverage. Connect with us: Website: ⁠ https://thedatastorytellers.com/⁠ LinkedIn: ⁠ https://www.linkedin.com/company/the-data-storytellers⁠ Apple Podcast: ⁠ https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476⁠ Spotify: ⁠ https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa⁠ YouTube: ⁠ https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters: 00:00: Introduction and revisiting the 2025 AI predictions 01:39: Taylor’s work at Microsoft, the Vatican, and stepping away to reflect 04:48: Recapping part one and setting up the 2026 AI prediction scorecard 07:32: Has AI started delivering real economic value? 11:18: AI coding, developer productivity, and the rise of “dark factories” 14:24: The one-person billion-dollar company and the limits of AI employees 19:30: Why AI’s value is shifting from models to applications and workflows 24:11: Is the AI bubble disappearing, or just changing shape? 29:52: AI, employment growth, data centers, and US reindustrialization 33:23: Open-source models and the changing enterprise AI landscape 34:19: The Vatican, the Catholic Church, and the moral questions around AI 40:33: Pope Leo’s perspective on AI, power, relationships, and human flourishing 46:10: How do we measure human flourishing, and when should kids use AI?

June 25, 20261 hr 23 min

Semantic Leverage | Albert Mangahas (Roo)

In this episode of The Data Storytellers Podcast, we speak with Albert Mangahas, a data and analytics leader now at Roo. Albert shares how his path from industrial engineering and SQL led him into data leadership roles across PwC, Green Dot, Facebook, Turo, and now Roo. We explore how trust in data became a foundation of Albert’s career, how marketplaces like Turo balance supply, demand, safety, and user experience, and what it takes to scale data teams through rapid growth and crisis. Albert also discusses his time at Facebook, how Turo navigated the pandemic, and why the real opportunity with AI may be less about replacing people and more about scaling better business insight. Connect with us: Website: https://thedatastorytellers.com/ LinkedIn: https://www.linkedin.com/company/the-data-storytellers Apple Podcast: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476 Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa YouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters: 00:00: Introduction and Albert’s first time in Vancouver 01:50: From computer science to industrial engineering 03:50: The SQL class that sparked Albert’s interest in data 06:04: PwC, auditing, and building trust in data 13:36: Moving into retail fintech at Green Dot 17:28: Mobile banking, underbanked customers, and Instant Pay 20:11: From BI reporting to analytics, finance, and FP&A 21:57: Joining Turo and taking on analytics, FP&A, and fundraising 26:43: The Turo business model and the case for peer-to-peer car sharing 34:39: How two-sided marketplaces balance supply and demand 40:14: Trust, safety, insurance, and managing marketplace risk 45:53: Facebook, Cambridge Analytica, and data transparency 48:42: Leadership, influence, and measuring complex platform problems 57:46: Why Albert returned to Turo 58:57: COVID, travel shutdowns, and wartime data leadership 1:06:15: Profitability, supply growth, and marketplace resilience 1:09:07: AI, trust, and the future of business decision-making

June 11, 20261 hr 24 min

Why Your Model Gets it Wrong | Dejan Mitkovski (BetMGM)

In this episode of The Data Storytellers Podcast, we speak with Dejan Mitkovski, a data and technology leader whose career has spanned Microsoft, Amazon, Google, FanDuel, and BetMGM. Dejan reflects on the last 25 years of digital transformation, from the early days of relational databases and BI tools to the rise of big data, data science, machine learning, and AI. We explore how data leadership has evolved from reporting to prediction, why legacy organizations struggle to adopt new technologies, and how leaders can prove value through small, practical tests. Dejan also discusses the difference between traditional machine learning and AI, the importance of data quality and governance, and why curiosity, discomfort, and people leadership remain central to building successful data organizations. Connect with us: Website: https://thedatastorytellers.com/ LinkedIn: https://www.linkedin.com/company/the-data-storytellers Apple Podcast: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476 Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa YouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters: 00:00: Introduction and Dejan’s return to Vancouver 03:43: The 25-year arc of data, digital transformation, and AI 04:26: Early influences, science, and choosing a different career path 09:40: First exposure to analytics and the move into Microsoft 12:20: Relational databases, Hadoop, and the early digital era 16:07: Stitching data together, personalization, and the rise of BI 20:38: Big data, data science, and the shift from reporting to prediction 29:35: Amazon, mentorship, forecasting, and thinking like an owner 37:02: Google, legacy industries, and the challenge of changing how companies work 42:35: Proving value through small tests and cultural adoption 50:45: Machine learning, measurement, and what makes AI different 59:41: FanDuel, data products, governance, and scaling a data organization 1:10:51: ChatGPT, generative AI, and the limits of messy data 1:18:18: BetMGM, AI enablement, and lessons for data leaders 1:21:58: Curiosity, discomfort, and the human side of leadership

January 5, 202650 min

What "Data-Driven" Actually Means | Anthony Jackel (Ferrara)

What separates analytics teams that get a seat at the table from those stuck in the reporting queue? Anthony Jackel, Senior Director of Business Intelligence & Analytics at Ferrara , has spent his career answering that question, from Kraft to one of America's largest candy companies. In this conversation, we explore: What "data-driven enterprise" actually means The shift from data providers to decision enablers Why user-centered design matters as much for dashboards as it does for iPhones How to build analytics products that drive action, not just curiosity The mindset shift that earns analytics a seat at the table Connect with us: Website: https://thedatastorytellers.com/ LinkedIn: https://www.linkedin.com/company/the-data-storytellers Apple Podcast: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476 Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa YouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters: 00:00 – Introduction to Anthony Jackel and his role at Ferrara 03:35 – Building Ferrara’s analytics team from scratch 07:42 – The problem with dashboards and low-value data work 11:50 – Connecting analytics to business decisions and revenue 16:25 – The importance of commercial empathy for data leaders 20:18 – Getting out of the service provider mindset 25:04 – Translating technical insights for non-technical audiences 28:45 – Why building trust is more important than being right 33:29 – Lessons from finance that shaped his analytics approach 37:12 – Coaching and developing high-performing analytics talent 41:05 – The challenge of balancing curiosity with execution 45:18 – Internal marketing and the power of repeatable wins 49:56 – Final advice for future analytics leaders 📍 Chapter Timestamps (Finalized for 50:13 runtime)

November 19, 20251 hr 14 min

Why Most AI Use Cases Miss the Point | Taylor Black (Microsoft)

What happens when a technology starts to look, sound, and reason like us? Taylor Black, Director of the AI Ventures Ecosystem in the CTO’s Office at Microsoft, has spent his career at the intersection of data, venture building, and emerging technology. From bootstrapping a SaaS company to helping shape early stage AI innovation inside one of the world’s largest technology organizations, Taylor brings a rare long term perspective on what AI is, and what it is not. In this conversation, we explore how today’s AI moment compares to past technological revolutions, why most current AI applications are still low hanging fruit, and where the real economic and organizational disruption is likely to come from next. We discuss the limits of automation, the rise of agentic systems, the moral responsibility of those building AI, and why the hardest work ahead is not technical, but cultural. This is a wide ranging discussion on AI, human work, governance, and the difference between making hard things easier versus making impossible things merely difficult. Connect with us: Website: https://thedatastorytellers.com/ LinkedIn: https://www.linkedin.com/company/the-data-storytellers Apple Podcasts: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476 Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa YouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters 00:00 – Introducing Taylor Black and his role at Microsoft 04:00 – From bootstrapped SaaS founder to data driven decision making 10:30 – Learning to translate technical insight into business value 16:30 – Venture studios, zero to one work, and entering Microsoft 23:30 – How ChatGPT changed perception inside large organizations 28:00 – The steam engine analogy and why infrastructure matters 33:30 – AI, work, and why modern jobs already felt broken 40:00 – Presence, remote work, and the limits of digital collaboration 46:00 – AI optimism, AI fear, and misunderstanding the technology 52:00 – What large language models actually are and are not 58:30 – Governance, moral responsibility, and who shapes AI 1:05:30 – Agentic systems, job disruption, and what comes next

November 12, 20251 hr 6 min

AI Optimism vs. Evidence in Late 2025 | Ylan Kazi (Blue Cross Blue Shield North Dakota)

In this episode of The Data Storytellers Podcast, we sit down with Ylan Kazi, Chief Data & AI Officer at Blue Cross Blue Shield of North Dakota, to cut through the noise around enterprise AI. Ylan explains why early machine learning hype never matched operational reality, how LLMs changed the game once they became accessible to anyone, and why most AI failures stem from cultural friction rather than technical limitations. He breaks down the gap between expectations and actual ROI, the overlooked complexity behind agentic AI, and the fundamental difference between inserting AI into old workflows and redesigning processes to be AI native. We also explore the economic and societal contours of the current AI cycle, including energy constraints, the cultural backlash against AI generated content, and why exponential progress looks slow until it doesn’t. Ylan shares what the coming micro bubbles might look like, how labor markets are shifting, and why new technology forces each of us to examine the meaning of human work. We end with a look at his AI Edge newsletter and what he is tracking as this transformation accelerates. Chapters: 00:00 Introductions and Ylan’s early AI skepticism 04:30 Traditional AI vs generative AI and why prompting skill matters 08:00 Why enterprise ROI lags and why most failures are cultural 12:00 The economics of LLMs, energy constraints, and infrastructure realities 18:00 Agentic AI, undocumented processes, and why value requires redesign 25:00 Automation, talent pipelines, and shifts in labor markets 34:00 Cultural reactions to AI content and the value of human creation 45:00 The case for micro bubbles and faster boom bust cycles 57:00 Ylan’s newsletter, what he is writing about, and closing thoughts

October 2, 202543 min

The Hard Truths of Enterprise AI Adoption | Jodi Blomberg (Cox Automotive)

In this episode of The Data Storytellers Podcast , we speak with Jodi Blomberg , VP of AI and Machine Learning at Cox Automotive. Jodi shares her experience leading AI transformation at scale in a highly regulated, legacy-rich environment. We explore how to balance long-term R&D with immediate impact, why trust and humility are critical in AI leadership, and how to move from proofs of concept to deployed products that make a real difference. Jodi also discusses the cultural and operational shifts required to truly embed AI in the enterprise and her own career journey from econometrics to machine learning. Connect with us: Website: https://thedatastorytellers.com/ LinkedIn: https://www.linkedin.com/company/the-data-storytellers Apple Podcast: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476 Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa YouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters: 00:00 – Introduction and Jodi Blomberg’s role at Cox Automotive 02:44 – The mission of the AI and Machine Learning team 06:12 – Where AI is driving value in automotive ecosystems 10:25 – Lessons learned leading data teams in legacy orgs 14:01 – Balancing long-term R&D with business impact 18:17 – Why successful AI teams don’t chase shiny objects 22:39 – The cultural change required for enterprise AI 26:15 – From proof of concept to production in a regulated space 30:34 – Jodi’s career path from econometrics to applied AI 35:48 – The role of humility and empathy in AI leadership 40:09 – Bringing executive stakeholders on the journey

September 4, 20251 hr 13 min

The AI Leadership Playbook for Global Enterprises | Elena Alikhachkina

In this episode of The Data Storytellers Podcast , we speak with Elena Alikhachkina , Chief Data and AI Officer at TE Connectivity. With a background spanning Pfizer, Johnson & Johnson, Nestlé, and now one of the world’s largest industrial tech companies, Elena shares what it takes to lead AI transformation across global, complex organizations. We talk about the realities of operationalizing data and AI in manufacturing, the soft skills required to drive trust and adoption, and how to move from use cases to enterprise value. Elena also reflects on how she built her career across industries, why curiosity is her superpower, and how data leaders can move from technical execution to strategic leadership. Connect with us: Website: https://thedatastorytellers.com/ LinkedIn: https://www.linkedin.com/company/the-data-storytellers Apple Podcast: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476 Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xa YouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmA Chapters: 00:00 – Introduction and Elena’s current role at TE Connectivity 02:41 – Why AI transformation is a leadership challenge, not a tech one 06:50 – How to build trust across functions when driving change 10:22 – The power of storytelling in operational environments 14:36 – Creating a data strategy that scales globally 18:58 – Why speed alone is not a data strategy 23:11 – Aligning AI with core business priorities 27:04 – Moving from isolated use cases to enterprise-wide value 31:17 – Lessons from Nestlé and Johnson & Johnson 36:03 – Defining value clearly in industrial use cases 40:40 – The evolution of the Chief Data and AI Officer role 44:12 – Building multidisciplinary teams that earn business trust 49:18 – Advice for data leaders entering legacy-heavy environments 53:46 – Why curiosity, empathy, and resilience matter most 58:03 – How Elena built her career across industries and functions 1:03:40 – What’s next in data and AI at TE Connectivity 1:08:12 – Closing thoughts on leadership, impact, and lifelong learning

August 21, 202556 min

How Agentic AI Will Reshape Customer Experience | Rangan Gangavaram (Verizon)

In this episode of The Data Storytellers Podcast , we speak with Rangan Gangavaram , Senior Director of Analytics & Insights at Verizon, about the promise and pitfalls of agentic AI. Rangan shares why agentic AI is more than just another automation wave, how it differs from RPA, and why its reasoning capabilities could redefine customer interactions. We discuss the decision frameworks enterprises need to adopt, the importance of stakeholder-driven adoption, and how AI transformations resemble the digital era more than traditional data initiatives. Rangan also reflects on his career journey from engineering to analytics leadership and the pivotal role of storytelling in driving AI adoption. Connect with us:Website: https://thedatastorytellers.com/LinkedIn: https://www.linkedin.com/company/the-data-storytellersApple Podcast: https://podcasts.apple.com/gb/podcast/the-data-storytellers-podcast/id1493766476Spotify: https://open.spotify.com/show/2N0vZtHZHgod4Tll2LX2xaYouTube: https://www.youtube.com/channel/UCz9e56lhYUfORiOHMiLlPmAChapters: 00:00 – Introduction and reconnecting after past conversations 01:15 – Why agentic AI is the real deal for enterprises 04:32 – Comparing agentic AI to RPA and automation 07:55 – The multiplier effect of AI-driven reasoning 12:41 – Do today’s AI models really reason? 17:14 – Understanding the driver behind customer problems 19:03 – Key risks and pitfalls in deploying agentic AI 25:12 – Why stakeholder buy-in is essential for adoption 28:40 – AI strategy as part of a holistic transformation 32:58 – How AI transformation mirrors the digital revolution 36:46 – Managing cost concerns for AI at scale 40:33 – Rangan’s career path into data and analytics 46:12 – The importance of storytelling in analytics leadership 52:10 – Advice for aspiring professionals in data and AI 54:40 – Closing reflections and future collaboration