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In this episode of Pharma Talks, Nataliya Andreychuk sits down with Toby Beaumont, a specialist with 20 years of commercial digital transformation behind him, seen from both the agency and the vendor side. His focus is on why pharma’s push to automate content often creates more problems than it solves.
The conversation covers the gap between efficiency and effectiveness, why AI multiplies fragmentation instead of fixing it, who should own the content design system, and what “speed of need” could mean for pharma marketing.
Nataliya opens with the pressure automation is putting on the content supply chain. Toby says the focus is almost entirely on efficiency: doing more with less and doing it faster. But when teams measure the results, the gains are often smaller than expected. More content is easy to produce, but if it isn’t more effective, what problem is being solved?
The industry, he notes, is full of isolated AI pilots. Asked whether they have moved the needle, his answer is short: “My honest view is not yet.” He believes the industry will get there, but only if it becomes more systematic first.
Toby is quick to say that “systematic” doesn’t mean slow or rigid. It means giving content an operating model: templates, claims, rules, guardrails, and metadata. The real question is what holds these parts together, and the answer today is usually nothing.
“Today in pharma, nobody really owns that whole process. Different teams are accountable for different parts of that process, and that inherently creates fragmentation.”
Many assume AI will resolve this. Toby says it does the reverse, accelerating the fragmentation instead of solving it, and Nataliya agrees that it multiplies it. He compares it to putting a faster engine in a broken car: without good tires and a good chassis working together, the engine achieves little. Nataliya adds that the fragmentation comes from people, meaning agencies and vendors, and from the many technologies used for different purposes.
The answer, according to Toby, is what he calls a content design system (CDS): the discipline and rules that bind systematic processes together, so the whole thing moves when one part speeds up. Without it, gains stall. Speeding up inbound content while review stays slow only builds a logjam.
Adoption is lagging because nobody owns it. Working out who does is, in his words, where the industry is still figuring things out. He also warns that quick wins are hard to come by here, because they rarely scale. Country maturity and other factors mean transformation moves at different speeds across an organization.
Technology adds another layer. The system driving AI is often not the one used by the rest of the business, so mixing technologies creates a new problem. Asked which content platforms support the move from systematic to automatic, Toby is candid: “Honestly, not many.” Companies still have to produce content every day, so some teams keep working in controlled, systematic environments while others experiment. The goal is a single source of truth, so that teams can use automation and still jump back into the governed process.
Nataliya asks where AI sits in all of this. Toby says it tends to sit outside the ecosystem for now, with experiments taking on their own identity and drifting away from the rest of the organization. The real test, for him, is scale, and it is also where the “evolution of the marketer” question begins. If AI frees teams for higher-value work, companies first need to know how they will redeploy those people, which he says is barely being explored yet.
That leads him to a phrase he has used on other podcasts:
“I called it the illusion of maturity, which is that because we have been using AI, because we think we’re doing things faster, we’ve created this illusion that somehow we’re actually really progressing.”
Toby describes himself as a die-hard tech fanatic, but says the industry has to be realistic about how much of what it thinks it has achieved is aspirational. He has yet to see anything truly scale, and he is confident that will change.
Nataliya asks whether the gap between AI’s instant results and a systematic approach’s slower payoff is a blocker for marketers. Toby prefers to call it an opportunity to learn. If a company adds AI and discovers its processes weren’t as optimized as it thought, that isn’t failure. Companies with an appetite for this, he says, will do best, because there is no textbook for what good looks like. The industry may need design systems, organizational change and new roles of accountability, none of which happen overnight.
Nataliya frames the North Star as relevance: messaging that helps patients understand the impact on their health, which more content alone will not deliver. Toby agrees, and returns to his central point that efficiency does not equal effectiveness. The demand, he says, is for relevant content delivered at the “speed of need,” and he offers a deliberately contentious thought experiment:
“Imagine today, if your end-to-end content production cycle took 60 days, from ideation to creation to adaptation to localization, translation, approval. Imagine if those 60 days became 60 seconds. Most people would balk at the idea, but if you break it down, maybe that’s not such a crazy idea.”
Reaching even 60 minutes, he says, would mean reimagining the lifecycle itself, with ideation and creation no longer treated as separate silos. It would let pharma respond at the moment of care, as other industries already do.
Nataliya asks what Toby would tell fellow marketers. His first piece of advice is to acknowledge the fragmentation that exists in every company, whatever its size or geography, and not to assume AI will “pave over” it. Keep experimenting and running pilots, but be clear about what you are measuring and what success looks like. Above all, ask how each pilot will scale.
He frames these less as advice than as the areas most likely to trip companies up. Get them right, and the incremental value starts to come through.
The thread running through the conversation is that AI and automation are accelerators, not fixes. Pharma needs a system underneath them first: clear ownership of a content design system, aligned technology, a single source of truth, and processes that speed up together. Toby’s optimism holds throughout. He calls this a very exciting time to be in the space, and thinks AI is “a very big opportunity time for a lot of people.”
It’s also the thinking behind Viseven’s modular content approach and the eWizard platform: bringing structure, governance, and a single source of truth to content so that automation has something solid to build on.
Enjoyed this conversation? Want to keep talking about content systems, automation, and the evolving role of the marketer? Talk to us, and let’s explore it together.
