In this episode of Humans of AI, host Alaura Weaver and WRITER CMO Diego Lomanto sit down with Lilly Raymond, a marketing executive who has led MarTech and AI transformation across major financial services brands. Lilly shares a practical perspective on leading marketing teams through AI adoption in complex, highly regulated environments.
We explore the tension between pride in craft and the need to build new ways of working, and how leaders can navigate workflow, governance, and change management in regulated industries. Lilly discusses why AI’s greatest impact may come from being embedded earlier in the process, helping teams improve the quality, consistency, substantiation, and readiness of content before it reaches legal, compliance, or expert review.
Plus, as a university professor, Lilly shares a unique perspective on what the next generation of marketers is telling us about AI, authenticity, and the skills that will matter most as entry-level work evolves.
Listen now to hear how leaders can guide teams through the human side of enterprise AI transformation.
When we talk about resistance to AI, we often treat the workforce as a monolith. But Lilly’s experience reveals two distinct cohorts facing entirely different challenges — established marketers whose pride in craft deserves to be respected as organizations introduce new AI-enabled ways of working, and the emerging talent facing a structural training and career path crisis.
For established marketers, the hesitation is rooted in pride. The good kind of pride that comes with years of honing one’s craft and developing one’s expertise.
When Lilly’s team introduced AI to their in-house agency, they were cautious. The team arrived with real questions — about nuance, about judgment, about the work that had always required a human in the room.
But as Lilly observed, “It wasn’t resistance that we were experiencing, but it was really the pride that they took in their craft. And what clicked for me was that this isn’t really about the tool, but it’s more about helping people understand where their value sits in the work that they create.”
“…What clicked for me was that this isn’t really about the tool, but it’s more about helping people understand where their value sits in the work that they create.”
When you’ve spent a decade perfecting a skill, and a machine does it in 30 seconds, it feels like an erasure. As Lilly noted, resistance also often masks embarrassment and fear of being left behind. People worry about disclosing that they don’t know how to use the new technology.
Lilly’s solution was simple but profound — she went first. She publicly admitted she didn’t know how to build an agent and asked for help. By not performing certainty, she gave her team permission to learn and fail alongside her. She let them use the tool, and after a few weeks, she took it away. The result? They demanded it back. That’s a concrete transformation — from resisting the technology to requesting it.
In highly regulated industries, it’s a common assumption that legal and compliance will be the biggest roadblocks to AI adoption. Lilly found the exact opposite.
“There is this perception that compliance and ADA review take a very long time,” Lilly explained. “And it’s not really because compliance takes a long time. It’s because they’re flooded with all this content and there’s a high rejection rate.”
The opportunity isn’t pushing compliance to move faster. It’s embedding AI earlier in the process — improving the quality, consistency, and readiness of content before it reaches legal, compliance, or expert review. When content arrives in good shape, the rejection cycle shrinks on its own, and compliance teams can focus on the complex judgment calls that actually require their expertise.
The AI isn’t magically compliant on its own. It’s compliant because the compliance rules and brand standards get encoded into the AI’s inputs and guardrails during the creation phase. As our Brand Integrity guide emphasizes, the key is to “encode your standards — voice, terminology, visual rules, strategic guardrails — directly into the AI infrastructure.” By partnering with compliance to enable review earlier in the process, AI clears the queue so the experts can focus on complex use cases rather than repetitive reviews.
As a university professor, Lilly also sees how the next generation of marketers is reacting to AI. Surprisingly, the generation that grew up on screens is the one most alarmed by what AI-generated content is doing to their feeds.
“They are seeing this mediocre content show up in their social media feeds. And they know it’s AI-authored. And they’re really looking for the authenticity,” Lilly shared.
According to the 2026 AI Adoption in the Enterprise survey by WRITER and Workplace Intelligence, 44% of Gen Z employees report actively resisting their company’s AI strategy. This isn’t a philosophical protest — it’s a signal that something in the adoption approach has broken down. Gen Z occupies the exact entry-level roles that AI is currently compressing. When executives deploy AI purely for efficiency without redefining what junior talent will actually do, disengagement becomes a predictable response to an unaddressed career concern. The survey backs this up — a staggering 80% of Gen Z employees report trusting AI more than their own managers. The challenge isn’t just pride. It’s a fundamental failure of leadership to align AI adoption with career development.
So, what skills will matter most in an AI-driven future? According to Lilly, it’s not prompt engineering or data science. It’s storytelling.
“Being able to determine what is a story that you want to tell or what is a narrative that you want to tell is just going to help AI do a better job,” she said.
AI can orchestrate the entire campaign supply chain, but it cannot decide which version of the story is true to the brand. It cannot decide what matters to the person on the other side. Judgment, taste, and the ability to craft a narrative are what will keep us human — and differentiate our brands.
But how do we train that judgment if AI is taking over the foundational work? This is a critical question for the industry. As Diego Lomanto noted in the episode, the traditional entry-level roles that served as the training ground for young marketers are being compressed. The solution, Lilly suggests, lies in a shift toward internships and hands-on projects where students can use their skills combined with AI to apply creativity, analytics, and judgment in real-world scenarios. The industry must adapt its training models to ensure the next generation has the opportunity to develop the very judgment that AI cannot replace.
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Gather your team and name the things that are dissolving. The things AI is taking away. The first draft that used to be yours. The research pass that used to take three hours. The image edit that used to require a specialist. Name it directly. And then — this is the part that requires courage — tell them what you personally find hard about letting it go. Not as a speech. As an honest admission.
Then ask the room one question — what becomes possible for us if we’re no longer the people who do that?
Listen to the full episode of Humans of AI to hear more of Lilly’s insights on leading through transformation.