AI is not your healthcare marketing strategy

There is a lot AI can do in marketing now.

It can synthesize research, generate campaign ideas, analyze customer feedback, create content variations, personalize communications, and optimize workflows.

For healthcare companies trying to grow while controlling costs, this is a significant opportunity.

The productivity gains are real. McKinsey's 2026 research found that 90% of CMOs were experimenting with AI use cases. And yet, very few organizations have successfully scaled AI and captured value across their marketing workflows.

I think that gap is worth paying attention to.

Because while AI can make marketing faster and more efficient, it doesn't replace the need for marketing.

Companies still need to understand their customers, decide which markets to pursue, position their products, build trust, create demand, support sales, and figure out where to invest.

AI can help us do all of those things better. But someone still has to decide what we're trying to accomplish in the first place.

More marketing isn't necessarily better marketing

It's easy to see why companies start with productivity.

A task that once took five hours can now take one. A marketer who created three campaign concepts can explore 20. A team that spent days reviewing customer interviews can use AI to identify patterns in hours.

That's incredibly valuable.

But as teams use AI to drive efficiency, I think it's important to keep coming back to one question:

What are we actually trying to make more efficient?

AI might help a team produce content faster, but content volume may not be the problem.

If the product is poorly positioned, the organization is talking to the wrong buyer, or sales and marketing disagree on the value proposition, producing more content isn't going to solve it.

In fact, AI may simply help you solve the wrong problem faster.

That's why I don't think the interesting question is whether AI should replace marketers. It's how we use AI to make marketing better.

That matters even more in healthcare

Healthcare marketers are rarely communicating a simple product to a single buyer.

A B2B healthcare purchase may involve clinical, operations, IT, security, finance, procurement, compliance, and executive stakeholders. Each comes to the decision with different priorities and questions.

Good healthcare marketing has to understand those differences and make the value clear without losing the core story.

AI can help us analyze those audiences and develop messaging for them. But it doesn't remove the need to understand why a message will matter to a clinician versus a CFO, or why something that resonates with an executive sponsor might create concerns for IT.

There are also claims, evidence, data, and trust to consider.

The FTC's Health Products Compliance Guidance, for example, addresses both express and implied claims. What an audience reasonably takes away from a message matters, not just whether the words themselves are technically accurate.

So while AI may generate a factually correct sentence, someone still needs to ask: What does this imply? What evidence supports it? Are we promising more than the data supports?

The faster we can create marketing, the more important those checks become.

So where should AI fit?

I don't think there will be a permanent line between human work and AI work. The technology is changing too quickly for that.

But right now, I find it useful to think about the work in three parts.

AI accelerates. It can help with research, analysis, production, testing, personalization, optimization, and workflow execution. If technology can remove hours of low-value manual work, we should use it.

Marketers interpret. We still need people to understand buyer behavior, customer language, market signals, performance, competitive movement, and context. Finding a pattern isn't the same as knowing what to do about it.

Leaders decide. Someone still has to choose where to compete, who to prioritize, how to position the company, what deserves investment, and when the strategy needs to change.

Those lines will move. What matters is that we're using AI to improve the quality and speed of the work, not outsourcing the thinking behind it.

Don't start with headcount. Start with value.

If AI gives a marketing team back 20% of its time, the most interesting question to me isn't how quickly we can remove that capacity.

It's what we could do with it.

Could marketers talk to more customers? Spend more time with sales? Improve positioning? Run more experiments? Better understand why deals are being lost? Think more strategically about the market?

That is where I think the AI conversation gets much more interesting.

Efficiency doesn't automatically translate into growth. We still have to decide where that new capacity will create the most value.

So before reducing marketing capacity, I'd ask:

• Is execution actually our biggest problem?
• Are we measuring activity or business value?
• Who owns the judgment behind AI-generated work?
• Do we have an AI strategy, or simply access to AI tools?
• And what are we going to do with the capacity AI gives back?

AI is changing healthcare marketing. It should.

But it doesn't eliminate the need to understand the market, the customer, or the business. And it doesn't replace the need to make good marketing decisions.

The opportunity isn't to replace marketing with AI. It's to give great marketers more leverage to do what they do best.

Human-led, with AI superpowers.

That's the kind of healthcare marketing organization I believe we should be building.