The more AI can do, the easier it is for marketers to confuse capability with value. AI can help you create more content, personalize more experiences, and reach more customers in less time. But it can also help you make promises faster than your organization can build the trust needed to deliver on them.
I recently attended a Bloomberg Tech event. I listened to leaders discuss what it takes to move AI from pilot programs into real operations. One of the conversations that stuck with me was around the amount of money companies are investing in increasingly sophisticated AI while continuing to invest in physical spaces and human connection.
At first glance, those investments seem contradictory. If technology can make an experience faster, smarter, and more personalized, why continue investing so heavily in people? The answer gets to one of marketing’s biggest challenges with AI — trust.
Speed is scalable. Trust isn’t.
AI can now complete knowledge-work tasks in minutes (sometimes seconds) that once required hours of human effort. Generate emails, summarize research, personalize a landing page, produce 10 campaign variations, and a lot more. What it can’t do is make a customer believe that the company behind those messages understands them, will keep its promises or take accountability when something goes wrong.
That part still belongs to people. A career spent largely in entertainment, sports, and experience-driven marketing taught me that attention can be created quickly. Connection takes longer.
I saw that firsthand working on KCON when the event was only in its second year. We were still earning the confidence of fans, sponsors, and exhibitors. Fans needed to trust we’d bring them the artists they wanted to see and deliver a once-in-a-lifetime experience worth their purchase. Sponsors needed to see KCON as a credible media platform capable of delivering real returns, while exhibitors needed a reason to keep coming back.
That kind of reputation is built slowly. You make a promise, deliver on it, and earn the opportunity to do it again. It’s also why I believe in-person experiences can’t be replaced. Trust grows when people can see, feel, and experience what a brand stands for.
The true challenge of AI
In my current role as global CMO, my mandate isn’t simply to produce more marketing. It’s to help a strong service company build the brand presence, partnerships, and positioning to match the business behind it.
As we worked on the brand, we kept returning to three things: brand equity, trust, and customer clarity.
That experience reinforced something I now think marketing leaders need to understand about AI: marketing doesn’t create trust on its own. Marketing makes a promise. The rest of the organization determines whether that promise survives in the real world.
AI makes it much easier to widen the distance between those two things. We can publish more thought leadership, create more personalized experiences, and automate more customer conversations. But if the experience behind those messages is inconsistent, AI only scales the inconsistency.
I think of that gap as trust debt. I’ve seen this firsthand. We can build a strong campaign around the value of global talent, but the real test begins when a prospect speaks with our team. Does the conversation feel thoughtful? Do we understand the business problem behind the staffing request? Does the service experience support what our marketing promised?
If those pieces aren’t aligned, more content won’t solve the problem. AI can help us scale promises much faster than most organizations can scale proof.
That’s why the executive question is simple: How much more value can we create without increasing our trust debt?
More touchpoints do not create more trust
AI gives you the scale to be everywhere. Customers just want you where it actually matters, and many brands will get that wrong. AI will lower production costs, enabling more emails, greater personalization, more automated conversations, and more opportunities to appear in front of the customer. But frequency isn’t a relationship.
Adobe’s 2026 research found that 45% of customers would stop interacting with a brand if they received too many promotions, even when those promotions were relevant. That means even good marketing becomes noise when a brand doesn’t know when to stop talking.
AI should earn its place by improving the customer experience, not simply by increasing how many times a brand can reach someone. The opportunity is to let technology handle work that doesn’t require human judgment, so people can spend more time solving complex problems, understanding context, making decisions, and building relationships.
That’s where I see the real value of AI in marketing: making better human interaction actually possible.
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Your dashboard is measuring the wrong thing
Most marketing dashboards only tell us how efficiently we generated an interaction. But they mostly only measure what it costs to earn attention this time.
They tell us much less about whether the experience made the next interaction easier to earn.
Look for evidence of trust, starting with your recently closed deals. How much chasing did it take to move them forward? Did prospects come back with substantive questions? Did they bring other decision-makers into the conversation? Or did your team have to keep creating every next step?
Persistence can close business. Trust reduces the amount of persistence required. When the marketing has already established credibility, the conversation gets to the actual business problem faster. When it hasn’t, sales has to spend valuable time rebuilding confidence in claims the prospect has already seen.
Another thing is to look at demand over time. If you continually need more paid media to generate the same level of interest while branded search, direct traffic, referrals, and repeat engagement remain flat, your marketing may be generating transactions without creating much accumulated preference.
None of these perfectly measures trust. But together, they answer a more useful question than clicks or conversions alone: Is our marketing making customers easier (or more expensive) to win again?
4 rules I’d put ahead of volume
If that’s the standard, then I’d put these four rules ahead of volume.
Require a reason to publish
Every piece of content should answer a real customer pain point. AI can increase production almost without limit. Customer attention cannot. People give promotional content only five seconds or less. More output isn’t useful if there was never a strong reason for the content to exist.
Start with what your company actually knows
The strongest material is often sitting inside lost deals, customer escalations, difficult questions, unusual requests. AI can help organize and surface those lessons. It can’t replace the experience that created them.
Keep someone accountable for what goes out
Automation should never make ownership ambiguous. Every customer-facing message or experience should ultimately have a person or team responsible for whether it’s accurate, useful, and consistent with what the company can actually deliver.
Pressure-test the promise
Before making a claim, prove your organization can and will deliver it during a difficult week, when people are stretched, and exceptions pile up. If you’re not 100% confident, change the marketing or fix the experience behind it.
AI handed every one of your competitors the ability to promise more, sooner, to more people. It handed none of them the ability to deliver. That’s still yours to win or lose.