Jill Roughan on AI and scientific accuracy in life science marketing

I came into marketing from science, not the other way around. I started my career as an emergency medical technician, spent years working in immunology research, and eventually moved into product and digital marketing for life science companies.

That background shaped how I built Sciencia Consulting. We work exclusively with life science organizations, where explaining the science accurately is just as important as making it accessible and commercially relevant.

What makes us different is that we understand the research, the technology, and the business side. Our work goes well beyond content or marketing campaigns. We’ve helped companies build entire digital marketing departments, coordinate complex product launches, improve their search visibility, and get their omnichannel operations working more efficiently.

We also don’t just hand clients a strategy and leave them to figure it out. We work alongside their teams to put the right people, technologies, and processes in place and help make it all work.

Most of our new business comes through referrals and inbound inquiries generated by our SEO and GEO efforts. We’ve invested in our own online visibility, just as we advise our clients to do, and it’s an important part of how companies discover us. Referrals are equally valuable, particularly in life sciences, where trust and industry knowledge carry a lot of weight.

If I could change one thing, I’d like more conversations to happen earlier in a company’s growth journey. Often, businesses start looking for marketing support when they already have a specific problem to solve. I’d love to connect with more companies when they’re planning a product launch, entering a new market, or deciding how to build or expand their digital marketing capabilities. That’s when we can help shape the direction, rather than come in later to solve problems that could have been avoided.

We’ve incorporated AI into the earlier stages of content development, particularly ideation, outlining, and organizing information. It can save considerable time, especially when you’re working with large amounts of technical material.

But we’ve also spent a lot of time testing where these tools fall short. In one of our recent research projects, our team evaluated ChatGPT, Claude, Gemini, and Grok across 28 life science content tasks, looking at scientific accuracy, strategic usefulness, and editorial quality.

One area we don’t believe should be handed over to AI is final scientific interpretation and review. A piece of content can read beautifully and still contain a scientific error or an unsupported claim. In pharmaceutical and biotech marketing, that’s a much bigger problem than a poorly written sentence.

The broader lesson applies well beyond content. AI can make marketing operations more efficient, but we still need experienced people making decisions about strategy, regulatory requirements, and what makes sense for the business.

One of the biggest changes is that companies have more ways to research potential partners before making contact. Traditional search remains important, but AI platforms are becoming another place where buyers research services, compare expertise, and evaluate potential providers.

We’ve invested in our own SEO and GEO, and we apply the same principles when helping clients improve their visibility through website optimization, technical search, and AI search strategies.

What’s interesting is that we can now measure visibility across AI platforms as well as track referral traffic and conversions from sources such as ChatGPT. That gives us a better understanding of how AI search contributes to business discovery, rather than simply whether a brand appears in an AI-generated answer.

My first piece of advice would be to stop looking at AI as something you need to adopt everywhere and start looking at where it can genuinely improve your marketing operations. Whether you’re preparing for a product launch, managing campaigns across multiple channels, or working with complex scientific content, identify the tasks that take up the most time and test where AI can help. We’ve done this ourselves, and one thing we’ve learned is that different tools perform very differently depending on the task.

I’d also pay close attention to how your audience is finding information. SEO remains important, but so does how your company, products, and scientific expertise appear in AI-generated answers. Making your content accurate, accessible, and discoverable across both traditional and AI search should be a priority.

What I’d ignore is the pressure to automate everything or constantly chase the newest AI tool. In life sciences, scientific accuracy, regulatory considerations, and sound strategic judgment still need experienced people behind them. There’s little value in doing something faster if you’re compromising the quality of the work.