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For over 20 years, Rebecca Colwell has been building her career around scaling smart marketing strategies that can actually work in practice. Now, as Senior Vice President of Product Marketing at Yext, she’s drawing on those years of experience and setting the tone for how brands can leverage AI in today’s data-driven world.
Rebecca has spent time sharpening her leadership skills across companies like Birdeye, EZ Texting, Veeva Systems and Zapproved. Now in the age of AI, those skills aren’t being left behind in favour of speed; instead they’re framing her approach to AI. “[The] role of marketers is shifting from content creator to strategic conductor,” Rebecca told us, while stressing that the core skills of marketers are becoming even more valuable.
In Rebecca’s mind, AI is less of a replacement for humans and more an amplifier for what strong marketers already do best. Rather than getting lost in the rush to generate content, she urges creative teams to think bigger. “One of the biggest mistakes marketers are making with AI is treating it purely as a productivity tool and something to help them crank out more content, faster,” she explains.
When it comes to the importance of creating trust, Rebecca is equally clear-eyed. In her experience, she says that today “authenticity isn’t claimed. It’s earned.” As such, it felt natural to start our conversation on that topic: how does Rebecca define authentic marketing in a world where AI-generated content is everywhere?
Brand authenticity at scale in the era of AI comes down to two things: how brands communicate and how they’re found.
In terms of content, the rush to scale production with generative AI has created a race to the bottom. Marketers are cranking out a glut of SEO pages, blog posts, and social copy in bulk to boost visibility but most of it lacks originality, relevance, and an authentic voice. It scales but it all sounds the same and you can spot it instantly.
Ironically, AI can help fix the mess it made. When used intentionally and more like an editor than an idea engine, it can actually sharpen a brand’s voice across teams. Brands can train a shared GPT on their brand standards and then empower everyone who creates content – ranging from social posts to customer emails – to communicate with clarity and consistency. That kind of alignment builds trust (assuming the message is worth hearing in the first place).
Another area where AI is rewriting the rules is in how people find brands through search. Unlike on Google, marketers can’t buy their way to the top of an AI search query. ChatGPT, Gemini, and other AI agents surface what feels credible and relevant to that specific user based on a variety of factors. Not all are fully known just yet but early signals show that structured data, local presence, and strong reviews all feed into those decisions. In this new landscape, authenticity isn’t claimed. It’s earned.
One of the biggest mistakes marketers are making with AI is treating it purely as a productivity tool and something to help them crank out more content, faster. That mindset misses the real shift happening right now which is that consumers are changing how they search for information.
We’re seeing a meaningful move away from traditional search engines like Google toward AI-powered tools like ChatGPT, Gemini, and Perplexity. Gartner predicts a 25% drop in search volume as customers move to chatbots and virtual agents to answer their questions and that change is blowing up the old playbook. On Google, if you can’t rank organically, you can buy your way to the top. There are metrics, bidding strategies, and years of SEO expertise baked into how brands compete for visibility.
AI search doesn’t work like that. There’s no ad unit, no analytics dashboard, and no clean path to first position. Instead of ranking based on backlinks or keyword density, AI agents surface responses they deem credible, relevant, and aligned with user intent. That makes them less of a traffic tool and more of a trust tool.
To show up, brands need to be consistent, structured, and trustworthy across every digital touchpoint. Content needs to be machine-readable and grounded in accurate, up-to-date information. In this new world, you’re not just writing for people. You’re signalling to the AI that you’re a legitimate answer to the question being asked.
AI enhances brand trust when it helps companies deliver consistent, reliable experiences. This is no easy task and for multi-location brands, one of the biggest challenges is maintaining consistency across all touchpoints: hours of operation, service details, product availability, how staff respond to reviews. When that information is scattered or inconsistent, customers lose confidence. AI can solve this by standardizing and syncing data across platforms, ensuring what a customer sees online reflects the reality on the ground.
AI also creates new ways to listen. By analysing reviews, social media posts, survey responses, and chat transcripts at scale, brands can extract real insight into where the customer experience is strong and where it’s falling short. That’s particularly powerful for distributed teams. Corporate teams can identify patterns across regions or locations, then share back learnings and best practices to improve the customer experience system-wide. That kind of closed-loop feedback makes the brand feel responsive and aligned, which strengthens trust.
But AI can also break trust fast. When customers get vague, inaccurate, or generic answers—especially in AI-generated responses—it damages credibility. And if it’s clear the brand isn’t monitoring those touchpoints or correcting misinformation, customers won’t give them a second chance. Trust isn’t just earned through what you say. It’s earned by getting the details right.
As AI systems become more sophisticated, the role of human marketers is shifting from content creator to strategic conductor. The core skills that set marketers apart aren’t disappearing. They’re becoming more valuable. What’s changing is how those skills are applied.
Knowing how to prompt AI effectively is becoming a defining form of leadership and strategic thinking. It’s not just about asking the right question. It’s about understanding what outcome you want, how the model interprets context, and how to guide it toward something useful. In that sense, AI is training us as much as we’re training it. The marketers who thrive won’t be the ones who resist AI, but the ones who know how to wield it.
This shift elevates the role of marketers. Rather than spending time rewriting product descriptions or fine-tuning headlines, marketers can focus on higher-leverage activities: sharpening positioning, refining the customer journey, and ensuring the brand shows up consistently across every AI surface. You become the last mile of judgment—the person who knows what should be said, not just what could be generated.
In short: the future isn’t human or machine. It’s human through machine. And the marketers who learn to lead with AI — who treat prompting as a core skill, not a novelty — will drive the most impact.
AI is changing the personalisation equation and shifting the balance of power. Consumers are placing surprising trust in AI search platforms like ChatGPT and Gemini, which now generate highly tailored responses based on individual preferences and past interactions. These tools have memory. I don’t need to remind ChatGPT that I hate olives; it remembers. That kind of frictionless personalisation is powerful.
But here’s the catch: as a brand, we don’t see any of that. We have no visibility into those preferences, no data to retarget, no insights to act on directly. And as a consumer, I think that’s a good thing. It’s a clear departure from the control marketers had on platforms like Google, where data flowed back into targeting strategies. In the world of AI search, that loop is closed.
So how do brands personalise without violating trust? By being radically clear. When consumers ask hyper-specific questions such as “Where can I find a child-friendly vegan restaurant near me?” or “Which advisor at this firm specialises in first-time investors?” your data needs to answer. That means exposing detailed, structured information about your offerings, locations, professionals, and services in a way AI agents can understand and evaluate. Organising data into connected, centralised knowledge graphs – structured networks that link facts about your business and make them machine-readable- will be a key differentiator for brands as AI-driven search and customer interaction becomes the norm.
In this new era, personalisation isn’t about tracking. It’s about being easy to match with.
The biggest shift in digital marketing over the next 3–5 years will be the migration from traditional search engines like Google to AI-native platforms like ChatGPT, Gemini, and Perplexity. Consumers aren’t typing in keywords anymore. Instead, they’re asking complex, conversational questions and expecting intelligent answers. That changes everything.
There’s no playbook for AI search. No ad auction. No analytics dashboard. No way to buy your way to the top. To rank, your brand needs to be the most relevant and trustworthy match for a specific query. That starts with having consistent, structured data across every platform, from service details and product specs to bios, reviews, and location info. Brands that invest here will pull ahead.
Second, AI is flooding the internet with repetitive, derivative content. Blogs and social feeds are saturated with sameness. To stand out, brands need to create content that’s hyper-specific, grounded in real expertise, and connected to what customers actually care about.
And third, AI agents are becoming the front door to your digital presence. They’ll decide whether your site even gets seen. If your content can’t be read, understood, and trusted by AI, it’s effectively invisible.
The brands that win in this new era won’t be the loudest. They’ll be the most structured, the most relevant, and the easiest to recognise as a good answer.
