In this episode of AI: Machine-Made Marketing, we sit down with Simon Levitt, Global Creative Technology Director at Imagination, to explore how AI is fundamentally transforming experiential marketing — not just behind the scenes, but at the front lines of customer engagement.

Simon shares how generative and conversational AI are accelerating creative development, enabling rapid prototyping, and giving brands smarter, more contextual ways to interact with audiences. He explains why “depth, not scale” is the new frontier of personalization, and how natural-language interfaces are becoming powerful storytelling tools inside physical experiences.

From Apple Vision Pro experiments to AI-assisted pre-visualization, to combining computer vision, agents, and generative models into entirely new customer journeys, Simon pulls back the curtain on the technologies reshaping experience design. He also unpacks the challenges — hallucinations, QA, feasibility checks, production realities — and why skilled humans remain essential in the creative loop.

If you’re curious about where experiential marketing goes next, or how AI can elevate in-person brand moments in ways that were impossible just a few years ago, this conversation delivers the roadmap.

On this episode of AI: Machine-Made Marketing, we sit down with Dennis Kirschner, Co-Founder & CMO of ShowHeroes Group, for an unfiltered look at the escalating content crisis inside the walled gardens — and what it means for advertisers navigating an AI-accelerated media ecosystem.

Dennis breaks down why AI-generated content is exploding at unprecedented scale across major platforms, creating volatile new risks around brand safety, misinformation, and transparency. Instead of suggesting brands pull out of the walled gardens, he explains how to invest smarter, ask harder questions, and reclaim clarity in environments that are becoming increasingly opaque.

He also maps out what he sees as the antidote:

A multiscreen strategy anchored in premium publishers

The open web as a counterweight to fraud-ridden feeds

And AI-powered tools that elevate targeting precision, content suitability, and performance across trusted environments

Looking ahead, Dennis shares his perspective on how AI will re-balance power between the walled gardens and the open web — and what advertisers and publishers need to prepare for as machine-generated media continues to reshape attention, authenticity, and trust.

In this episode of AI: Machine-Made Marketing, we’re joined by Asha Shivaji, CEO and Co-Founder of SeeMe Index, to explore how responsible AI is changing the way brands understand and measure inclusivity. Asha shares how her team’s data-driven approach helps marketers uncover representation gaps across ads, products, and purpose—proving that inclusion isn’t just good ethics, it’s good business.

From quantifying screen-time disparities to showing how inclusive brands are growing nearly 3x faster than their peers, this conversation dives deep into the intersection of AI, culture, and commerce. Tune in to learn how brands can use AI responsibly to build trust, drive growth, and make sure everyone sees themselves in the story.

Jason Downie, Global CRO at Making Science, reveals how applied AI is transforming marketing — from hyper-personalization and creative scale to building a culture of experimentation and preparing for the next wave of multimodal search.

On this episode of AI: Machine-Made Marketing, we explore how synthetic populations—statistical reconstructions of entire societies—are reshaping the marketing landscape. Our guest, Ray Kong, Chief Marketing Officer at Arima, breaks down how Arima’s all-in-one analytics platform leverages AI to create privacy-safe, hyper-granular insights that rival traditional data collection.

Ray explains why synthetic populations are more powerful than point-in-time synthetic data, how they balance consumer privacy with advertiser performance, and why small agencies that fail to adopt AI tools risk obsolescence. From micro-targeted local marketing to predictive fraud modeling, this conversation reveals why Gartner predicts that by 2028, 80% of the Global 5000 will use synthetic data at scale.