When AI scales what's already broken: Lisa Gately, Principal Analyst at Forrester

Lisa Gately spent more than 20 years building content systems inside tech companies before she crossed over to study those systems as a Principal Analyst at Forrester. After hundreds of conversations with marketing leaders, she found something uncomfortable: content problems are rarely about content. They're organizational problems that show up in the content first.

As a featured guest on this episode of Humans of AI, Lisa reveals what‌ separates teams thriving in the AI era from those spiraling into scatter. The answer isn't more tools or bigger budgets. It's three things marketers have known for years and the hard organizational work of prioritizing them.

We also dig into the visibility vacuum: a world where buyers form opinions through AI-generated answers without ever visiting your site. And the Ferrari problem: what happens when your CIO hands every employee the same general-purpose AI and expects marketing to maintain brand differentiation with it.

Hosted by Alaura Weaver.

Listen to find out:

• Why the keyword-first content model was already broken before AI arrived
• What "the visibility vacuum" means for your brand strategy
• The single most important relationship every marketing leader needs to maintain right now
• Your Monday Morning Action: one thing you can do this week to start building content that only you could create

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 0:05

I remember talking to a communications leader who said in her team she had a lot of people who were divided about the use of AI, and she wanted to inspire everybody, so she encouraged them to all expense their own generative AI tool of choice. There are other people that they may go off and use their tools of choice, but you're really seeing that scattering into working as individuals. That to me signified this is just as scattered as the content world could be.

SPEAKER_03 0:31

That story happened inside a single marketing team, one manager with good intentions and a generous offer. And what it produced was a dozen people pulled in 12 different directions, each with their own AI, their own prompts, their own version of the brand voice. Nobody coordinating. Nobody asking, what happens to the work after the content gets made? I'm Alora Weaver, and this is Humans of AI. Lisa Gately spent more than 20 years building content systems inside tech companies before she crossed over to study those systems as a principal analyst at Forrester. She has watched this scatter play out hundreds of times in content teams.

SPEAKER_02 1:21

What I realized is that content problems are rarely about content. It's really an organization problem or something to do with your operations or decision making. It's just showing up in your content first.

SPEAKER_03 1:35

Before Lisa was an analyst studying what works and what breaks in enterprise content teams, she was inside the machine herself. And she describes a pattern that most marketers recognize the second she names it.

SPEAKER_02 1:48

You go through a big cycle of new messaging work and realize how much some of this was about what our organization wanted to say. It was about our own priorities.

SPEAKER_03 1:59

How many times have you built a content calendar around what leadership needed to announce instead of what your buyers needed to understand? It's the organizational equivalent of a birthday card that's really good about how good you are at making birthday cards. The recipient is technically on the front, but the whole thing is about you.

SPEAKER_02 2:23

We always justified it too. We would write to keywords, or we would justify this short-term effort would help us with something.

SPEAKER_03 2:29

Write for the keyword, ship for the quarter, justify it with a metric. That's the operating logic of the modern content function. And for a while that logic held. We mistook how much we were producing for how fast we were moving. Then the machines arrived. And the machines can do that faster than we can, at a fraction of the cost. 24 hours a day. He's watched this moment arrive from the inside of a company building AI for marketers.

SPEAKER_01 3:01

I think we've all had that feeling of shipping something that isn't really differentiated. Like everyone's done it in their career. Shipping something because you need to be out there and have air cover on the topic, but it doesn't feel great because it's stuff that anyone else can say.

SPEAKER_03 3:19

So if the machines have taken over production volume, and they have, what exactly is left? What is the job of a marketer in a world where infinite content is the new table stakes? Lisa started asking a version of that question years before generative AI even arrived. Lisa started her career because she loved words. Journalism school, editorial roles, the gap between what organizations want to say and what audiences actually need to hear. That tension is what got her up in the morning. She wasn't escaping that tension when she left the practitioner side to become an analyst. She was chasing it at greater scale.

SPEAKER_02 4:04

You know, it drew me in because I wanted to study more of transformation at scale. You know one company's reality really well. And it's really hard going through it. You feel like, are we really unique? Do other people have this figured out? And so that was some of my curiosity was I wondered about how do other people navigate some of this? And I started thinking about maybe somebody out there has it figured out. If I just see enough patterns, I'll figure it out. Hundreds and hundreds of conversations later, everybody has strengths, everybody has blind spots. We're all dealing with some constraints or trade-offs, but nobody has the answer.

SPEAKER_03 4:41

Nobody has the answer. That might feel like a discouraging thing to learn after hundreds of conversations, but it isn't. What Lisa actually found was something more useful than a universal solution. Everybody has an answer. But it's specific to them, their customers, their category, their proof, their constraints. You can't copy it. You can't reverse engineer it. You have to build it from what is actually true about your organization. Out of all those hundreds of conversations, Lisa found three things that consistently separated the organizations that weren't winning and the ones that were. Not new ideas, not secret frameworks, things marketers have known for years, which is she'll tell you exactly the problem.

SPEAKER_02 5:34

Yeah, those aren't new ideas. I know sometimes talking with clients, I can see the look on people's faces. And so they are perennial challenges. And I see that because it requires prioritization. You're making a commitment on each of those, you're able to live with some trade-offs of not doing other things. Topical authority. That's selecting topics that your audience cares about, and then you're sorting out what your company wants to be known for and what do you have to say on this topic? You really need to know your audience well. And so some of that pulls people out of that self-centered, you know, shipping the org chart kind of thought. If you're working with your expert, it relies on some relationships. And a lot of that, we are so speedy thinking about what marketing is going to do next. There are different perceptions across different teams. And so I would say many times you're relying on people who are out, if they're with your customers or running the business, their perception is they may not understand what's going to be done with their contribution. They start to feel like maybe they're in fact some of these review processes, it's very subjective. It really matters what third parties say about you. Marketers have always been working with the media or industry analysts and more recent years, review sites, and that takes longer-term effort. So again, it's prioritizing that rather than getting caught up in the short-term thinking or the reactiveness.

SPEAKER_03 6:56

Notice what every one of those requires. Topical authority means getting into a real argument inside your organization about what you've actually earned the right to say. Not what you want to say, not what would be convenient to say, but what your specific experience and customer proof can back up. Expert drew in content means convincing people who have actual day jobs, who are running your products, sitting across from your customers, to slow down long enough to share what they know, to trust you with it, and to survive a review process they find baffling. And independent validation means building relationships with analysts, journalists, and reviewers over months and years. Relationships that can't be faked, that can't be rushed. None of that is a prompt. None of that is a workflow. That's a set of human negotiations that has to happen before a single word gets written.

SPEAKER_01 7:58

I try to think about what is it that we have a right to be an authoritative voice in, more so than everyone else. When we start to narrow down on our ICP or the use cases that we're great at or the unique problems we've helped our customers solve, now we get into a much more authoritative stance that we really do have the right more so than anyone else to talk about these things.

SPEAKER_03 8:24

Because the question isn't what can you say? In the AI era, you can say anything. The question is what you've earned the authority to say. That distinction is the difference between content that compounds and content that vanishes. Here's the part where the abstract becomes concrete. You can do the work, you can build topical authority, you can produce expert-driven content, earn third-party validation, maintain brand consistency, and your buyers may never directly encounter any of it.

SPEAKER_02 9:01

Forrester calls it the visibility vacuum. Buyers are using AI at every stage of the buying process. And when going into answer engines or AI-powered search, they're able to get answers they don't need to click through. AI is becoming more of the interpreter of your brand.

SPEAKER_03 9:18

Your buyer already has formed an opinion of your company before they've read a word of your latest campaign. That opinion was synthesized by an AI that ingested your own content, your earned coverage, your customer reviews, your competitor comparisons. Everything it could find. Are you on it? Diego saw the evidence of this before he had a name for it.

SPEAKER_01 9:47

My direct traffic is going up, and I don't know where it's coming from because there's no click. They're just coming to our site after, and they've heard about us through a chat interaction.

SPEAKER_03 9:59

This is not a crisis that better keywords will fix. The systems that decide your brand's position in an AI-generated answer aren't waiting for your next blog post. They're synthesizing your entire presence, published and earned, and rendering a verdict. The question isn't how to game that system. The question is whether you've built enough signals of authority, owned content, earned coverage, proof that when the system synthesizes an answer, your name ends up on the short list. So, what do marketers who are actually thriving right now have in common? Lisa ran the data, she did the interviews, and here's what she found out.

SPEAKER_02 10:40

They're very curious. They're open to the learning, and it is part of the team culture. It's not just experimenting for the sake of it, but there's some discipline to it though. And I would say that's really a team that's not chasing every new tool. They're understanding how the work is changing. And they had a good handle on some of the operations before. They really are normalizing learning in public.

SPEAKER_03 11:01

Not the ones with the biggest AI budgets, not the ones who moved fastest, the ones with discipline. The ones who, when they handed a tool to their team, also asked, what problem are we solving? What does success look like? What are we willing to stop doing?

SPEAKER_02 11:19

You, the human, should decide what exists in the first place, and you should decide what's valuable.

SPEAKER_03 11:25

You should decide what's valuable. Not the algorithm alone, not the keyword ranking in isolation, not the brief without the context that only you carry about your audience, your proof, what you've actually earned the credibility to say. That's not a soft skill. It's the only skill the machines can't replicate because it requires knowing something real and having the judgment to act on it.

SPEAKER_00 11:52

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SPEAKER_03 12:35

That picture of a thriving team, curious, disciplined, normalizing learning in public, sounds achievable. And it is. But there's a force working against it in almost every enterprise right now. And it isn't coming from a competitor. It's internal.

SPEAKER_02 12:53

Companies now are issuing, I'll call it horizontal tools because they're very accessible. Corporate is giving them to everyone, this perception that it's useful. It's not about generating more. You can give every employee every function more power to be productive, meaning you can do things you couldn't before, you could do more of it volume-wise. But now you've introduced some issues with quality and governance and the approval processes.

SPEAKER_03 13:18

The CIO bought a corporate license for a general-purpose AI. It arrived in everyone's inbox. And suddenly, marketing is supposed to maintain brand differentiation using the same tool that accounting uses to write memos. A marketer Lisa spoke with described the moment her leadership had to reckon with this. How many AI tools is your marketing team using right now? Not the approved ones. All of them. Do you know? Does your CIO, because the sprawl isn't just a cost problem, it's a brand consistency problem. It's a compliance problem. It's a we shipped 14 versions of our value proposition last quarter and none of them matched problem. And yet, the answer is not to lock everything down. Remember the communications leader from the top of this episode, the one who let everyone pick their own tool? That was scatter born from too much freedom. The CIO mandate is scatter born from too much control. Different course, same result. Lisa has watched what happens when leadership tries to solve governance by removing agency. The scatter doesn't disappear, it just goes underground. Diego Lamanto puts the structural issue plainly, and it reframes the entire AI tooling conversation.

SPEAKER_01 14:47

Marketing is not a series of individuals doing a bunch of different things and then just putting it out there. You're unifying around your brand, your story, your narrative, and your campaigns. And those are multiplayer, and it's really important that the marketing team is operating in synchronicity across your AI tools.

SPEAKER_03 15:10

Not just a collaboration, shared operational reality. Ten people working on 10 different deliverables, all drawing from the same understanding of who the audience is, what the brand stands for, what the company has earned the right to say. Content problems are rarely about content. They're organizational problems that show up in the content. Hand everyone a disconnected AI tool, and you amplify the organization's dysfunction at machine speed. Lisa frames the fix. The goal isn't less AI. The goal is AI that makes the team smarter, not noisier. Lisa's single most actionable piece of advice from this entire conversation isn't a framework or a tool. It's a relationship.

SPEAKER_02 16:19

Keep up your relationships with your CIO and CFO because you really have to maintain this relationship and explain why marketing has specific requirements, why there's great potential for marketers to help lead and be part of your company's transformation.

SPEAKER_03 16:35

That relationship isn't built in the meeting where IT hands down the tool mandate. It's built in the months before that meeting, when you show up with a business case for what marketing actually needs to drive growth. Not efficiency, not cost reduction, growth. And what it will cost the business if the infrastructure can't support it. You can't retrofit that argument after the license is purchased. You have to make it first. For most of marketing's history, the campaign was the unit of measurement. You planned, you built, you launched, you waited, you collected signal. Three, six weeks later, you apply your learnings to the next campaign. That cycle had a name, the waterfall. And for a long time it worked. The market moved at roughly the same pace you did.

SPEAKER_02 17:28

For a lot of marketing's history, we're used to operating in campaigns where you plan it, you build a lot of things, you execute or launch it, you measure it, move on. Today, with the buyer behavior, with AI systems, that long range of how you are found to how people form and continue their perceptions and preference, with the way that competitive dynamics are going to be changing constantly, it's really going to push you. How do you continuously improve, adapt? There used to be such lag time for teams in deciding what we would do once.

SPEAKER_01 17:59

It's that lag time, right? So I think we're used to this waterfall way of doing marketing. It's like I build a campaign, I put it out there, I wait a little while, I get some feedback and signal, I, you know, three weeks, six weeks later, I launch an another campaign with my learnings.

SPEAKER_03 18:16

The problem isn't that the waterfall was lazy. The problem is that buyers stopped waiting. Their perceptions are forming in real time inside AI systems before you've finished your post-mortem, which means the gap between signal and response. That six-week lag is now where your competitive position lives or dies. What replaces it has three parts.

SPEAKER_01 18:40

We're saying agents that are looking for signals. What's happening with competitors? What's happening in the market? What kind of data are you getting in your product usage, right? And literally from the campaigns themselves. What are we seeing in terms of performance?

SPEAKER_02 18:54

Do you have some visibility to these? I'll call them signals that as a team. And I would even look at good good teamwork would be you have somebody who'll help you tell people what it means. Don't leave everybody to interpret the dashboard solo and assume that everybody walks away with the same interpretation about what are we going to create, what are we going to improve, what do we stop doing now? We're closing that lag time.

SPEAKER_01 19:17

The third thing, and this is where actually the biggest challenge is, is then deploying continuously, right? Because you're signaling, you're perceiving, you're deciding, and then you need to act. And I see right now the bottleneck is some of the legacy platforms we have were not designed, they were designed around the waterfall process, not designed about a continuous adaptation. We've re-architected our site so that we can be more adaptive and we can launch things faster than the old way.

SPEAKER_03 19:48

Sense, decide, deploy. That's the new operating loop. But here's what makes it possible in an enterprise and what makes it fall apart without it. The guardrails have to be built before the loop runs. Because if the standards for quality, brand voice, and compliance aren't encoded into the system, closing the lag time just means shipping the wrong things faster. The organizations winning at this aren't the ones who removed the approval process. They're the ones who moved it upstream, into the platform, into the prompt, into the architecture, so that when humans show up in the loop, they're making judgment calls, not spelling checks. What we are building toward, if we do this right, is not a faster version of what we had before. It's something that actually earns its place. Content grounded in topical authority, systems built for synchronicity, tools governed by the standards that let experts do what only experts can do. All of that machinery exists in service of one person.

SPEAKER_01 20:58

What are they trying to accomplish? You have people at the end of this funnel that are engaging with you for a reason, and we can't lose sight of that. They're not just there to receive content, they're there to try to solve a problem.

SPEAKER_03 21:14

Your Monday morning action. Find one piece of approved content from the last six months that you know in your gut, your organization had no specific right to publish. Something that could have been written by any competitor. Pull it. Not as a punishment, as the beginning of a different question. What could we have said here that only we could say? Who on our team actually lives inside that problem with our customers? What do we know that the AI doesn't? Start there. Build outward. Thank you to Lisa Gately for sharing your story. I'm Alora Weaver. This is Humans of AI. Humans of AI is presented by Writer. Our hosts are me, Alora Weaver, Director of Enterprise Content, and Diego Lumanto, Chief Marketing Officer. Our producer is Alana Nevins. Our graphic designer is Mila Odor. Our social media manager is Tasha Thakar. Our video editor is Jamie Watkins. If this episode got you thinking about things in a new way, please share it with a friend, leave a review, and subscribe to hear more stories of humans working at the crossroads of technology and business.