AI in Retail: Relevance at Scale and Incremental Growth

Can ChatGPT Ads Beat Search? What Marketers Need to Know Now

As advertising begins to enter ChatGPT, marketers face a new question: how should they think about AI conversations as a place for discovery, influence, and performance? In this episode of The AI Advertising Podcast, host Diego Pineda explores what ChatGPT ads are, what marketers know so far, and how brands should approach this emerging channel. You’ll hear from: Yang Han, Co-founder and CTO at StackAdapt, who explains why advertising in LLMs may compete more with search than social, how conversational AI can reveal deeper intent, and why marketers should start testing now to understand where ChatGPT fits into their broader strategy. Michael Shang, SVP of Advertising Technologies at StackAdapt, who shares why this matters as a platform shift, how ChatGPT could become a powerful new intent signal for advertisers, and why early learning may be one of the biggest advantages in the market right now.

How AI is Reinventing Healthcare Marketing

Healthcare marketing is “hard mode”: strict privacy rules, heavy regulation, and measurement limitations that make the usual ad-tech playbook fall apart. This episode explores how AI is changing the way healthcare and pharmaceutical brands reach both patients and healthcare professionals—while balancing relevance with privacy and staying compliant. You’ll hear from: 1. Jerrad Rickard, Senior Director & Product Leader at IQVIA Digital. 2. Jasmaan Panesar, Senior Manager, Verticals & Performance at StackAdapt. Disclaimer: The views and opinions expressed in this podcast are those of the speakers and are for informational purposes only. This content does not constitute legal advice, and listeners should consult their own legal counsel regarding any specific legal or regulatory questions. StackAdapt does not access or store patient-level data and operates exclusively using privacy-aware, de-identified audience signals activated through vetted data partners.

AI Targeting for Sports Fans Ahead of the 2026 Soccer World Cup

The 2026 FIFA World Cup will be the biggest ever—48 teams, 104 matches—and it’s the ultimate test of reaching the right fans at scale without creepy tracking. This episode breaks down how AI-driven contextual targeting separates intent (not just interest) to reach both hardcore soccer fans (tactics, lineups, odds, analysis) and culture/moment fans (national pride, watch parties, travel, lifestyle/celebrity), with different creative, timing, and KPIs. Guest: Martin Perelmuter, Regional Agency Development Manager (LATAM) at StackAdapt.

AI in Retail: Relevance at Scale and Incremental Growth

As AI reshapes retail advertising with real-time optimization, faster creative testing, and new ways to reach shoppers across CTV, the open web, and commerce environments—one big question remains: Can AI actually deliver relevance at scale and prove what’s truly incremental? In this episode, we dive into that question with a leader on the front lines of commerce and programmatic: * Dana Karlin, Head of Commerce, StackAdapt

AI, Automation, and the Real Edge in Marketing Ops

AI in marketing automation has reached an inflection point. The tools are powerful, budgets are rising, and AI now touches everything from campaign planning to personalization. But outcomes are still inconsistent. In this episode, Diego Pineda sits down with Chris Bentley (Director, Marketing Operations and Analytics at StackAdapt) and Wayne Coburn (Director of Product at StackAdapt) to unpack why. The core insight is simple: AI advantage no longer comes from features alone. Performance now comes from consolidation, integration, and activating AI as a shared intelligence layer across fewer, more powerful systems—so journeys connect, learnings compound, and waste drops. We also dig into a structural problem highlighted by StackAdapt research: 66% of marketers say up to 30% of programmatic budget is wasted due to siloed or fragmented execution. Adoption has moved faster than coordination—and that gap creates “automation debt.”