There’s no AI in team… or is there?

We’ve been using GenAI at Camino for over a year now and the transformation for the team, the business, and our clients has been incredible. The question is no longer if AI will change how we work, but how much we can harness its potential.

Harnessing the power of GenAI across our teams

One of the most exciting developments at Camino is that we’ve moved beyond using GenAI with only content in mind. We’re now integrating it across every specialty, from building decks to streamlining repetitive workflows.

A great example is our presentation-building process, especially for repetitive content like congress data. What used to be a time-consuming task—gathering content, structuring it, and adding the relevant information to a slide deck—can now be largely automated. We can generate initial drafts of PowerPoint slides at the press of a button. This doesn’t just save time; it also enhances the quality and consistency of our presentations. The AI can organise content logically, and even personalise slides for different audiences. Once generated, we can then focus our human efforts on checking it, refining the messaging, and adding the strategic insights that only experienced medical communications teams can provide.

Breaking down traditional barriers to make the most of GenAI

Whether it’s our scientific experts, client service specialists, or digital and design teams (and now developers), everyone is on the same page, working towards a common goal. We pride ourselves on a de-siloed approach at Camino, breaking down traditional barriers between teams to ensure our success. Early on, we realised that bringing together diverse viewpoints and skill sets would be essential for delivering great omnichannel strategies. Almost by accident (but with perfect timing), this mindset allowed us to integrate GenAI across the team. We were able to jump on the GenAI bandwagon early and maximise its potential.

Building a strong, knowledgeable team

Adopting AI has not been without its challenges. One of the most complex aspects of integrating GenAI into our day-to-day has been the process of training the team. Our team is filled with talented individuals, but there’s no avoiding the learning curve for GenAI tools. Adoption doesn’t happen overnight and, in my case, supporting others in using AI was harder than I anticipated.

I learned that my process-driven mindset, which helped design the tools, wasn’t necessarily shared by everyone. I had to take a hands-on approach to knowledge distribution: write everything down and work through the processes step-by-step. There’s a real art to not only showing someone how to use AI but also helping them understand when and why to use it in certain situations. This meant breaking down complex tasks into digestible pieces and running multiple demos to ensure everyone was comfortable.

Through this approach, we’ve built a culture of collective knowledge sharing. We want to ensure that no one is left behind as we scale up our AI capabilities. What’s been key to our success is the mindset we’ve fostered within the team: a proactive, experimental approach to GenAI. We now go into projects thinking, “How can we use GenAI to help?” This spirit of experimentation led us to realise, for example, that AI could redraw entire tables from PDFs—something we discovered by just trying it out and seeing that it worked. By encouraging this mindset, we’re not just training the team on how to use AI tools; we’re empowering them to explore new possibilities and innovate in their roles.

Staying ahead without being tied to one model

AI is not perfect, and we’re still piloting it in many areas. But it is getting significantly better. One of the reasons we’ve been able to adopt AI so readily is that we’re not bound by any single product. While GPT-4 and Claude are often our go-to tools, we’ve integrated multiple GenAI tools across various functions, from video-generation platforms to automation tools, depending on our needs. This flexibility ensures that we remain adaptable and responsive to both our internal processes and clients’ needs, while staying on the cutting edge of technological advancements. I’m particularly excited to test Gemini’s redrawing capabilities!

We’ve noticed that many companies are focusing on developing niche AI tools, often for specific tasks. By contrast, we’ve chosen to master broad-purpose platforms that provide value across a wider range of applications. This approach helps us avoid getting distracted by tools that only solve narrow, one-off problems, or locked into a single system that may be out of date in six months’ time. And we all feel well positioned to tackle whatever challenges the future of medical communications may bring.

Embracing the AI future as a team

As we continue to integrate GenAI into our workflows, it’s clear that the future of medical communications will be defined by collaboration, creativity, and adaptability. I’m not sure whether breaking down barriers between individuals helps us use AI effectively, or whether AI is helping us break down those barriers. Either way, we are reducing time-consuming tasks and can deliver more valuable and innovative solutions.

More than anything, the key to success in an AI-driven world isn’t just about being the fastest adopter of new tools, although that might help. It’s about fostering a culture where everyone is empowered to use those tools to their fullest potential.