The messy reality of enterprise AI: Lilly Raymond on adoption, trust, and human judgment

We don’t always talk about the human side of transformation. We like the case studies. We like the ROI slides. But what happens when you bring powerful new tools to teams of experts who care deeply about quality, judgment, and craft?
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.

Key takeaways:

• Pride in craft:Why experienced teams care deeply about quality, voice, judgment, and professional standards, and how AI adoption works best when it respects that expertise.
• The power of vulnerability:How leaders can foster adoption by admitting they don’t have all the answers and learning alongside their teams.
• Improving review readiness:Why AI’s biggest impact in regulated industries may be upstream, helping teams strengthen content before it enters legal, compliance, or expert review.
• Developing future talent:How changes to entry-level work create a greater need for internships, apprenticeships, and hands-on projects that build human judgment.
• The enduring value of storytelling:Why judgment, taste, and the ability to craft a narrative remain critical skills in an AI-driven world.

Listen now to hear how leaders can guide teams through the human side of enterprise AI transformation.

Subscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.

Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.

Learn more about WRITER at writer.com. 

Transcript

SPEAKER_02 0:09

Let me let you in on a little secret. No one has as much figured out about AI as their LinkedIn post makes you think they are. We don't like to talk about the messy part of transformation. We like the case studies, we like the ROI slides, we like the little neat charts that go up and to the right. But what happens when you bring a revolutionary tool to a team of experts and they push back?

SPEAKER_01 0:41

My team and I were super excited about the possibilities, but the in-house agency was cautious. They brought in their edge cases. So, you know, they came in thinking, well, you know, the work we do is too complex. It's highly nuanced.

SPEAKER_02 0:58

That's the reality. When you're leading a marketing team through an AI transformation, you aren't just fighting legacy systems, you're fighting the fear of obsolescence. You're fighting the pride people take in their craft. I've felt it, that gnawing panic of if the machine can do this, what am I worth? I'm Alora Weaver, and this is Humans of AI, the podcast that goes behind the strategy decks and the success metrics to find the real story of what it means to lead in the age of artificial intelligence. Each episode, we bring you an unfiltered conversation between leaders who are living this transformation every single day. Today, you're going to hear a conversation with Lily Raymond, a marketing executive who has led Martech and AI transformation at some of the most recognizable financial brands in the world. And she's also something else, a professor. She teaches the next generation of marketers at university level, which means she sits at a rare intersection. She can see what experienced teams are afraid of and what the people entering the workforce are afraid of. It's a perspective very few people have. Lily sat down with Diego Lamanto, writer's CMO, and my boss. You'll hear Diego's voice throughout this episode. He's the one in the room with Lily, asking questions only a peer can ask. My job is to be your guide. I'll be connecting the dots, surfacing the lessons, hiding between the lines, and asking the questions I know a lot of us are too afraid to say out loud. Because the question at the center of the episode, it's one I think many of us are wrestling with right now. How do you transform a team that's afraid of change? Before we talk about what it means to transform a team, we need to understand the environment Lily was operating in. Because this isn't a story about a small scrappy team experimenting with a new tool. This is marketing at a scale that most of us have never had to operate at. And that scale is the reason everything that follows matters as much as it does.

SPEAKER_01 3:18

These are complex, highly regulated industries. So the scope and the scale is massive. Think about multiple business units, multiple products, multiple segments, consumer segments, institutional segments. And then marketing is really taking the brand, the messages, and really communicating the value to multiple segments across multiple channels and making sure it's all integrated and cohesive. And to be able to do that, we really need to make sure we have the technology investment and the capabilities to scale that and to orchestrate that massive scope.

SPEAKER_02 4:02

We're not talking about one brand, one product, one audience. We're talking about dozens of products across multiple, completely different customer segments delivered across every channel simultaneously. Email, web, social, paid media, in person. All of it needing to feel cohesive, all of it needing to pass compliance review. All of it personalized. The organizational infrastructure required to make that happen is staggering. And Lily's job was to build it.

SPEAKER_01 4:37

When I started three years ago, that was exactly my role. We centralized the Martech stack. So previously, the Martech stack was sitting across five different business units. And by bringing in Adobe, we centralized all of that into a single platform. And the complexity really came by connecting it with all the different data platforms in the organization to ensure that we had a unified profile of the customer.

SPEAKER_02 5:06

Five separate technology stacks, five different ways of knowing the customer. And before you could do anything creative, anything strategic, you had to solve that foundational problem first. But here's the part Lily says she loves most about this work.

SPEAKER_01 5:22

What I love about that is enabling marketers to connect with the consumer. That is what I love. It's really bringing the joy back into marketing and really helping our marketers reach the customer and really share the brand and the brand promise and the value propositions.

SPEAKER_02 5:40

Enabling people to connect. That's what this is all about underneath all the technology. But to understand why AI became so critical to Lily's world, you have to understand what a single marketing campaign involves in an organization at this scale.

SPEAKER_01 5:56

So when I think of a marketing campaign workflow, it all starts with the brief. Marketers create a brief, but then it's based on insights, right? So to really enable the marketers to create that brief, they have to pull insights, really understand the reasons to believe, the segments, what they're trying to create. So then that brief gets routed through the workflow to the designers, the copywriters. So it's either an external agency, an internal agency. They determine whether we need new content, new, you know, a new experience, new design. That gets created. Of course, the marketers and subject matter experts are there to review the output of that. Once that is reviewed and approved, then it gets routed to compliance. And then, you know, assuming it's in good order and it's approved, well, then the next step is what do you do with that? It has to get produced, developed. So is it a website experience? Is it an email campaign? But typically that brief involves so many channels. So there are multiple points of execution. And so that content, you know, has to get published on the website, it has to go on an email, it has to put on social media, there's paid media involved. And then, of course, it has to get approved, make sure it's ADA compliant and all that. And then, of course, it has to be tracked and then optimized on top of all of this. And you think of all the variants, all that content and workflow that I described has to be personalized, and there's so many variants.

SPEAKER_02 7:36

And then you do it again for every product, every segment, every business unit simultaneously. Now imagine AI arriving in the middle of all that. When Lily first introduced AI for content creation to her in-house agency, she expected excitement. The case was obvious. They needed more personalized, compliant, segmented content than their team could possibly produce. And here was a tool that could help. Instead, she got a wall of edge cases. The team wanted to prove the tool couldn't handle their work. But Lily realized something crucial. It wasn't about the technology at all.

SPEAKER_01 8:16

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 really that this isn't really about the tool, but it's really more about the helping people understand where their value sits in the work that they create.

SPEAKER_02 8:36

That's the crux of it, isn't it? When you've spent a decade perfecting a skill and a machine does it in 30 seconds, it doesn't just feel threatening. It feels like an erasure. But there's another layer to this resistance, one that's harder to admit out loud.

SPEAKER_01 8:53

I also think that sometimes resistance is really more of an embarrassment of being left behind. So I think that it looks like resistance and it looks like skepticism, but folks are worried about disclosing that, oh, they don't know how to use it.

SPEAKER_02 9:11

Diego builds off this idea.

SPEAKER_00 9:13

I think there is this vulnerability aspect where the folks who maybe aren't ahead of the curve feel like they're they don't want to be exposed. So it's better off to just kind of hide where they are as opposed to shine a light on it and be vulnerable.

SPEAKER_02 9:28

So how do you get a team of seasoned professionals to admit they don't know what they're doing and start learning again? Lily's answer? You have to go first.

SPEAKER_01 9:40

I personally reached out to our director of AI to have her teach me how to create an agent. And I shared that with the team, right? Like I'm also learning. I feel like I was behind in terms of, you know, folks were creating agents left and right, and I didn't know how to do that myself.

SPEAKER_02 9:58

I love this so much. The leader who is supposed to have all the answers publicly admits she doesn't. And in doing so, she gives everyone else permission to not have the answers either. So, what does the actual playbook look like? Lily didn't mandate AI usage. She didn't set quotas or run top-down training sessions. She created a sandbox, she pointed people at low stakes, high stress pain points, like coming up with names, which anyone who has sat in a naming session knows is somehow both trivial and paralyzing. And just let them play. And then she did something nobody expected.

SPEAKER_01 10:44

So we let them use the tool, and after a few weeks, we just took the tool away, and they asked for it back. They demanded that we bring it back, and so that was really interesting.

SPEAKER_02 10:59

Taking it away. It's the ultimate proof of value. Not a survey, not a usage report, not an executive mandate, demand. That's concrete transformation from resisting the technology to requesting it. But getting the creative team on board was only one front. In a highly regulated institution, you also have to bring legal and compliance along. And most leaders I talk to assume that's the hard part. Lily found it to be the opposite.

SPEAKER_01 11:34

The compliance teams I've been finding have really embraced AI because they were struggling with the acceleration of content creation and they don't have the capacity. They're really overcapacity. So they really need the capabilities, and they are embracing AI to help them with that bottleneck.

SPEAKER_02 11:55

Most people assume compliance slowdowns happen because compliance is inherently slow. But Lily surfaces a different explanation entirely.

SPEAKER_01 12:05

There is this perception that compliance and ADA review take a very long time. 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 content that's coming in from marketers, it used to be where it wasn't coming in in good order. So then the compliance team has to reject it, and then it goes back to the marketer who sends it back to the copywriter, right? To go change that and then it comes back in. So then you have this cycle.

SPEAKER_02 12:38

The bottleneck isn't the bureaucracy, the bottleneck is the rejection cycle. Content goes in, gets sent back, gets fixed, comes back in again, over and over. Which means the fix isn't pushing compliance to move faster. It's making sure the content that arrives at their door is actually ready. And that's exactly where AI earns its place on the compliance side of the workflow, too.

SPEAKER_01 13:04

It was also partnering with them to enable the review to happen earlier in the process. So, like during the time of content creation. So making sure that those inputs as that content was being sent to those teams for review, that it was in good shape.

SPEAKER_02 13:22

AI embedded upstream, not just at the point of creation, but baked into the handoff. So what arrives at compliance is already in good shape. And when that happens, something else opens up too.

SPEAKER_01 13:37

Then they don't have to focus on all this repetitive review, right? Of the same content over and over, but they can focus on the more complex use cases.

SPEAKER_02 13:44

That's the pattern Lily keeps returning to across every part of the workflow. AI doesn't replace the expert, it clears the cue so the expert can actually do expert stuff. Remove the repetitive, protect the judgment. And that logic only works if you look at the whole system, not just the step you happen to own.

SPEAKER_01 14:04

Because if you just look at, you know, every single step separately, it creates a bottleneck in the next step. So if you create content, then it creates a bottleneck and compliance review. You really need to look at the entire system, not every step separately.

SPEAKER_02 14:20

Now, here's where the conversation takes a turn. Because Lily doesn't just operate inside large enterprises, she also teaches. She's a digital marketing professor working with juniors and seniors who are about to enter the workforce. And what they're telling her is something every senior marketer in this audience needs to hear.

SPEAKER_01 14:43

There is a real tension. They are using AI for work, they're using it for school, they're using it in their personal life. But what they're concerned about is the future. So 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.

SPEAKER_02 15:06

The generation that grew up on screens, the generation we assume is most comfortable with AI, is the generation most alarmed by what AI-generated content is doing to their feeds. They're not afraid of the tool. They're afraid of what happens to culture when the tool gets used badly at scale. And that is a far more sophisticated conversation than most boardrooms are having.

SPEAKER_01 15:35

They are concerned about what it means for them, for their roles as marketers. And what I do teach them is we use AI in class. We use it to create marketing campaigns. But I do show them what good looks like and how to use it and how to use it responsibly. Because you have to do that because they are going to use it when they get to work.

SPEAKER_02 15:59

But there's a harder conversation underneath this one because these students aren't just worried about culture. They're worried about jobs, specifically their jobs, the entry-level roles that used to be the on-ramp to a marketing career. The ones involving research, drafting, formatting, coordinating, those are the exact tasks AI is best at right now. So if those jobs are disappearing or changing shape, how does the next generation of Lily Raymonds actually develop?

SPEAKER_01 16:34

Entry-level jobs are going to look very different. The entry-level jobs of today will not be the first or entry-level jobs of tomorrow. But it's important that the students have some AI fluency and then also pick up experience through internships, through projects, to where they can use AI to be able to apply that creativity, that analytics, the judgment. That's what is going to be important in the entry-level jobs of the future.

SPEAKER_02 17:09

After we wrapped with Lily, Diego and I spent a few minutes debriefing. And that advice about internships and real-world experience, it landed personally for both of us.

SPEAKER_00 17:20

For my son who's in college and my daughter who's going to college next year, their programs are doing this adaptation. They have to do internships. As someone who's buying into that process here, now I really understand how important that's going to be to actually entering the workforce with the experience necessary.

SPEAKER_02 17:39

At one point she said you have to know what good looks like. And I think that was also something we heard from a previous guest, Robert Rose. In order for you to be a master of your craft, you need to know what that uh litmus for quality is. And the only way you can do that is through actual experience and getting constructive critique and iterating. You have to know what good looks like. That line keeps coming back to me because it's the answer to both problems Lily's students are wrestling with. If you're worried about mediocre AI content flooding your feed, the antidote is developing the taste to know the difference. If you're worried about losing your place in the workforce, the antidote is building enough real-world experience to exercise judgment that AI can't replicate. Both answers require the same thing. Genuine exposure to the work, the messy, iterative, get it wrong and try again kind.

SPEAKER_00 18:42

What skill would you recommend they focus on developing the most then while they're in school?

SPEAKER_01 18:48

I would say storytelling. That is a skill that I think not only should they develop, but I think many people in business need, right? Because you'll need that when you're trying to create the inputs for AI. 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.

SPEAKER_02 19:10

Storytelling, not prompt engineering, not data science, storytelling. And I think there's something worth naming here because this is the same through line that runs all the way back to Lily's skeptical in-house agency. The experienced marketers who pushed back weren't afraid of losing their jobs to AI. They were afraid of losing their identity as craftspeople. The answer then and now is the same. Help people understand where their value actually sits in the judgment, in the taste, in the story only they know how to tell, and the ideas that are born from those stories.

SPEAKER_00 19:54

Putting something out in the world is more important than ever now. You know, if you're a kid who's, you know, in college and and you have an idea, I I mean, I speak as someone who hires people, love people who follow through on their ideas, even if they're not in the workforce yet and they're building stuff and they put themselves out there. That's a way to get that experience that you're not going to get necessarily from an entry-level job.

SPEAKER_02 20:19

Follow through on the idea. Put it out into the world. That's what earns the judgment. That's what builds the taste. And that message isn't just for students, it's for anyone on a team who's been sitting on the sidelines waiting for permission to try. Something else she mentioned when talking about like bringing laggards in, but I can also see this as cultivating students is this sense of being safe to fail, vulnerability, encouraging curiosity, taking risks so that way you can learn and that growth mindset. I think it's going to be incredibly valuable to cultivate for this next generation. More so than ever, because you're going to have to find new ways of solving problems. So we've covered a lot of ground. We've talked about the sheer operational complexity of marketing at enterprise scale, and why that complexity is exactly what makes AI not optional but essential. We've talked about the resistance, that's really embarrassment. About compliance teams who are secretly your biggest allies, about students who are sharper critics of AI than most executives give them credit for. And we've arrived somewhere that I think is the real point of it all. Diego asked Lily what skill becomes more valuable in the age of AI, not less. More. Her answer was one word judgment, the ability to discern. Because AI can orchestrate that entire campaign supply chain we described the brief, the copy, the compliance routing, the personalization variants, 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.

SPEAKER_01 22:08

AI can do a lot, but it can't get really close to the customer. So I think staying close to the customer and the context is the most important. And I think that is what keeps us human and differentiates a brand.

SPEAKER_02 22:24

What I keep coming back to from this conversation is something I didn't expect to take away. We came in asking how you transform a team that's afraid of change. I assumed the answer would be about strategy, about frameworks, about the right sequence of pilots and leaderboards and one-on-ones. And Lily gave us all that. But underneath it, she gave us something harder to package. The transformation started the moment she stopped performing certainty. The moment she told her team she didn't know how to build an agent either. The moment she invited them to learn with her and to fail with her, and to learn from that, and to grow together. That's not a framework, that's a choice. And it turns out it's the most important one. There's a moment in a caterpillar's metamorphosis that most people don't know about. It's inside the chrysalis. The caterpillar doesn't just grow wings, it dissolves. Completely. Its body breaks down into an undifferentiated soup of cells before it reorganizes into something new. The transformation isn't an addition, it's a surrender, and then a rebuilding from the inside out. I think about that a lot when I hear leaders talk about AI transformation, because what Lily described isn't a story about adding a tool. It's a story about letting go of who you thought you were, as a craftsperson, as a leader, as someone who had to have the answers, so that something better could take shape. That is terrifying. And it is also the only way through. Because on the other side of that, fear isn't just a more efficient version of the same work. It's the space to do work that defines a new era. Work that only we, with our expertise, our judgment, our proximity to the customer can do. And maybe more importantly, it's the space to model what that looks like for the next generation watching us figure it out. The students Lily teaches, the kids Diego is sending off to college. The entry-level marketers who need to see a leader navigate uncertainty with curiosity instead of control, so they can do the same. So here's your Monday morning action. 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? Because the caterpillar doesn't negotiate with the chrysalis, it doesn't get to skip the dissolution and go straight to the wings, neither do we. But we do get to choose whether we dissolve alone in private, pretending it isn't happening, or together with the people who are living it alongside us. That conversation is the transformation. Everything else follows from it. I'm Alora Weaver, and this is Humans of AI presented by Writer. Thank you, Lily Raymond, for sharing your story, and thank you for being here with us. Until next time.