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When it comes to building marketing that connects with people, Sharon Yates Harrison knows what she’s doing. With a background in sales and marketing, her perspective is rooted in knowing what people want on a personal scale. Now working as CMO at Gravyty, Sharon helps educational institutions strengthen their community engagement, using AI to help fundraise at scale.
Before stepping into the role of CMO at Gravyty, Sharon led marketing at Ivy.ai, a pioneer in AI-powered student engagement. Indeed, we interviewed her whilst at Ivy almost 18 months ago as part of our series “Dust and Magic”. Clearly spurred on by that success, Sharon has since become a sought-after conference speaker and guest lecturer.
That mix of experience doesn’t just show experience with the technology. It means she knows how the students, alumni and donors think, and how better to target AI-powered tools towards them.
AI isn’t about replacing human marketers, Sharon explains, it’s about elevating the things they do best. In this interview, she talks openly about AI’s ability to break down data into “deeply nuanced personas” and respond to their needs in real-time, but she’s quick to add that timing isn’t all that makes a campaign. “Just because we can automate a message doesn’t mean we should,” she says, “some moments need to come from a real person – even if that doesn’t scale.”
This balance of speed and authenticity are key to Sharon’s take on everything from ad personalisation to ethical uses of AI. Or as she puts it: “The future of marketing isn’t man vs machine – it’s man + machine.” With that mindset, Sharon Yates Harrison is uniquely placed to answer the question of just how much AI is reshaping personalisation and the role of human creativity in modern marketing.
AI isn’t just changing how we scale personalisation; it’s forcing us to redefine what personalisation actually means.
What used to pass as personalisation – adding a first name or using industry-specific language – feels inadequate now. At this stage, I draw a hard line between personalisation and individualisation. Personalisation is about relevance. Individualisation is about precision. It’s the difference between targeting a segment and understanding a person. That shift from relevance to precision is where AI can shine.
To get there, you need more than just data; you need insight. That’s where AI has been a game-changer for my teams. Our product marketers are breaking down ICPs into deeply nuanced personas, getting granular about what matters to each one. It’s not just for engagement – it accelerates funnel velocity. When you show someone you truly understand their challenges, you earn credibility. And that creates trust, which is everything in today’s buying process.
But AI is not a set-it-and-forget-it solution. I’ve seen great campaigns fall flat simply because the timing wasn’t right, even when the content was. One recent example: we launched a targeted initiative for financial aid professionals during a chaotic time in higher ed. The message was spot on, the need was real, but we were also navigating a brand transition. The campaign may still bear fruit, but it’s a reminder that AI can’t fix poor timing or the complexities of brand perception.
Where I see AI shine is in our ability to respond fast. I started my career building month-long campaigns for full-page print ads. Now, with AI, we can spot a trend, brainstorm, build a campaign, and go live in hours or days. That kind of agility used to be impossible. Today, it’s essential.
That said, AI can’t replace creative originality. It’s a phenomenal partner for brainstorming, data analysis, and iteration but human oversight is non-negotiable. I’ve seen my fair share of AI-generated content that made me cringe and, truthfully, some of it has been my own. But that’s part of the learning curve. The difference is whether you treat AI like a crutch or like a co-pilot. The best outputs still come from great inputs, and nothing replaces human creativity or a team member who knows the brand voice inside and out.
Looking ahead, I think marketing leadership will require a new kind of fluency. It won’t be enough to be creative or data-driven; you’ll need to be an orchestrator of AI systems, human talent, and market signals. The risk is that we homogenise everything into a sea of algorithm-approved content. The opportunity? We get faster and smarter than ever before.
The outcome depends on how brave and how disciplined we’re willing to be.
Authenticity doesn’t depend on who writes the message. It depends on whether the message reflects genuine understanding. And that’s where AI can shine by helping us tap into real-time insights and individual preferences. AI gives us the ability to craft communication that feels relevant, timely, and intentional.
It allows us to tailor messaging to someone’s specific stage in the journey – whether they’re a first-time visitor, long-time customer, or decision-maker on the edge of conversion. But it’s not the precision alone that makes it authentic. It’s the thought and intention behind it.
That’s why we never remove the human layer. AI often gives us the first draft, but our team brings the empathy, tone, and emotional nuance. One of the most important lessons we’ve learned is that restraint matters. Just because we can automate a message doesn’t mean we should. Some moments need to come from a real person – even if that doesn’t scale. Knowing when to make that call is what separates connection from noise.
As AI evolves, we’re not trying to automate authenticity; we’re using AI to enable it. It’s a tool that helps us be more responsive, more informed, and more relevant. But the soul of the message must still come from us. The future of marketing isn’t man vs. machine – it’s man + machine, building smarter, more human connections at scale.
Authenticity doesn’t just mean “human-made” – it means intentional, aligned, and meaningful. In our world, it’s about creating content that reflects our brand values, solves real problems, and resonates emotionally with our audience. AI can support that, but it can’t lead it.
Authenticity at scale starts with the right foundation: a clear brand voice, a strong ethical framework, and a deep understanding of your audience. When those are in place, AI becomes a tool to help execute more efficiently, not a replacement for strategy or empathy. But we do have to be more disciplined. The margin of error is smaller now. A generic AI-generated post might be technically fine, but if it doesn’t feel on-brand or relevant, it risks eroding trust.
That’s why we focus less on how fast we can create content and more on whether that content actually serves a purpose. Sure, we use AI to speed up workflows and take on repetitive tasks, but the strategy, tone, and final voice always come from us. We take time to review, rewrite, and ask ourselves: does this actually reflect who we are and what our audience cares about? Authenticity might start with values, but it’s maintained through consistency, judgment, and a healthy dose of human instinct. At the end of the day, our goal isn’t just to be efficient, it’s to be real.
One of the first ethical dilemmas I faced with AI wasn’t about data, it was about credit. I used an AI tool to help brainstorm and refine a campaign idea. The final product reflected my voice, but it didn’t feel right to take full credit. That moment reshaped how I think about transparency. It’s not just about labelling something as AI-generated. It’s about being honest with yourself and your team about how ideas come to life.
For me, the biggest ethical concerns with AI are transparency and privacy. Every time I give a tool access to data – or even to my thoughts – I consider where that information might end up. Is it being used to train an open-source model? Am I uploading proprietary content that could resurface in unexpected ways? Whether it’s personal, company, or customer data, the question of consent and control is critical.
Marketers shouldn’t bear the full weight of ethical AI use, but we are often on the front lines. That makes it our responsibility to model best practices. On my team, that starts with a hard line: no sharing of company data. And before we roll out any new AI tools, we test in a sandbox and fully vet the use case. Innovation is important, but so is accountability.
Yes, AI has become a powerful tool in my creative process, particularly in content development, campaign ideation, and refining messaging, but it’s important to note that we treat AI as a collaborator, and not a creator. Humans are always at the front of marketing operations, especially when it comes to strategy, brand positioning, and the overall voice behind our messaging. AI can help us move faster and maybe expand our thinking, but it can’t replace the irreplaceable human creativity and intuition, and the lived experiences needed to make a successful marketing campaign.
An example of this can look like writing our initials messaging drafts, but leveraging an AI tool to assist in optimising tone, grammar, and clarity. This approach allows us to make sure our content aligns with our brand and our messaging, but saves us some valuable time on the editing process. Or if you consider campaign development, AI could be used to brainstorm early themes or structure some early messaging ideas. By inputting prior campaign results or outlining key audience segments, AI can surface patterns or new directions we hadn’t considered, allowing the team to iterate more effectively.
Overall, AI has made us more efficient and expansive in most cases, but a close, human eye is necessary to preserve authenticity.
The role of human marketers is entering a transformational period. As AI systems become more advanced, I would argue that human creativity, empathy, and judgment will become even more critical as AI takes on more of the operational lift. Marketers are shifting from the task doers to the strategic orchestrators. We are responsible for guiding the application of AI to align with brand strategy, tone, customer experience, execution, etc. With AI assisting in things like editing or interpreting data, humans are bringing the creativity and strategic thought that only humans can.
The modern marketer needs to understand the full breadth of AI capabilities, not to become a machine expert, but to become an effective translator between what the brand stands for and what the technology can deliver. AI may be able to produce a copy, but it’s up to the marketer to ask: is this copy on-brand? Is it meaningful? Does this drive the kind of emotional connection we want to build with our audience?
Sophisticated AI can accelerate production and increase efficiency, but it still lacks the ability to understand human behaviour, or replicate emotional context or cultural relevance. Marketers will have to evolve to become experts in asking AI the right questions, helping set the correct contacts, and ensuring that any AI-generated outputs meet brand standards. Just as importantly, they need to serve as the critical thinkers who know when to use AI and when not to. AI is a powerful tool, but not an autonomous solution.
