Seán Carroll talks to us about his work leading the life sciences content team at Accenture Song and how generative AI is changing the content strategy space.
Seán Carroll is a content strategist currently leading the life sciences content team at Accenture Song, Accenture’s tech-powered creative group. In this role, he says he mostly advises global pharma companies on their content strategy and creation, with the help of Accenture colleagues around the world.
Carroll has 15 years of experience working in life sciences agencies based in the UK and Denmark, and has been working at Accenture for five years.
“A lot of our work at the moment is around helping clients understand the role content plays in their CX [customer experience] and omnichannel strategies, with a focus on personalisation and modular content strategy.”
From your experience as a life sciences content lead, what are some of the biggest challenges you’ve faced in creating content for global pharma clients?
Pharma is (for good reasons) a very heavily regulated industry, so the speed at which we can create and disseminate content has always been a challenge.
Regulations can also differ greatly from country to country, so for global teams it is a challenge to meet the differing content needs of all the local markets around the world.
And personalisation is high on the agenda at the moment but brings its own challenges – personalised content often means more content to create for teams that are already struggling to move at the pace they need to stay relevant with healthcare professionals.
Lastly, ensuring that the human element comes through in our content. Much of our content is based on scientific or medical information but how can we ensure that the human and emotional side of the story comes through too.
How do you balance the need for personalised content with the broader regulatory and compliance requirements in the life sciences industry?
This is one of the biggest challenges that our clients face at the moment. There is such a vast amount of new medical data produced every day and healthcare professionals often struggle to find the time to keep up to date. So, providing personalised and relevant content is top of the agenda for the industry.
But the content creation and approval process in our industry is slow so trying to produce more personalised content has been a big challenge.
Our clients are looking at different content strategies to try to overcome this including taking a modular approach to content creation. And generative AI is likely to have a big role to play in the coming years in years to support personalisation.
How do you currently leverage technology and AI tools in your content creation process and what are the biggest benefits around these tools?
Generative AI is obviously the hot topic for all of our clients at the moment, but most of them are still quite early in the process of figuring out how to integrate it into their global ways of working.
The two types of benefits that we are expecting to see quickly are generative AI augmenting existing content creation processes to make them faster and more efficient; and generative AI giving teams the capacity to create new content types or personalise content.
Other than generative AI, we have been working a lot with Figma as a way to collaborate with designers and work with tools that support a modular content approach.
How do you go about addressing concerns about generative AI’s limitations when it comes to using it for content creation, in terms of accuracy, biases or plagiarism?
This is particularly important for our pharma clients where accuracy of medical content is crucial. For now, we focus on two elements to help address those concerns.
The first is around educating our clients about expectations for generative AI in the content creation process – today generative AI can help us get to a first draft much quicker but we should not expect it to be 100pc perfect.
The second is around ensuring that the content creation processes continue to have a human in the loop to review and check for accuracy and bias.
Has the growth of generative AI changed the skillset you need to do your job?
I’ve definitely had to do a lot of learning on the topic – there is so much hype, it’s been important to increase my knowledge so that I can understand what generative AI can and can’t do, where are the limitations and biases etc.
Understanding where it can automate task, where it can augment and where it has no role to play has helped us figure out how to integrate it into content strategy and content creation processes.
But I think that the core skills of a content strategist remain the same – generative AI just gives us another tool to play with.
Looking ahead, how do you foresee the role of content strategists evolving in the next few years with advancements in AI and technology?
I think that the tools, technology and processes that we use will be different and the opportunities much bigger, but the core of the job will stay the stay the same: understanding our customers and creating personalised, relevant and engaging content for them.
Advancements in generative AI will give us the ability to make much more content, more quickly. So good content strategy will be even more important than ever to help cut through the noise and reaching healthcare professional with relevant and engaging content.
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