Gen AI for Pharma Content: Own It or Outsource It?

Opinion by Felix Evensen, Principal, Digital Engagement & CX, Arcondis

It became quite clear in 2024 that the integration of generative AI (Gen AI) across the pharma content value chain presents significant opportunities to transform content-related processes. But transformation is rarely a straight path.

As the pharma industry grapples with balancing brand promotion and delivering valuable content to healthcare professionals (HCPs) – all while adhering to strict regulatory guidelines – Gen AI tools can indeed help. However, despite the “AI-euphoria” over the past two years, reality has been more complex than anticipated. Recent analysis of Gen AI adoption in the pharma customer engagement space suggests that implementing scalable and effective solutions remains challenging.¹ However, the critical question isn’t if Gen AI should be adopted but how? Should you consider in-sourcing and owning a larger proportion of the content value chain, supported by Gen AI solutions? Or should you continue to outsource and rely on external agencies (who are already applying Gen AI – for better and for worse)?²

Let’s explore the “in-source vs outsource” challenge across the pharma content value chain, revealing opportunities and risks at every stage.

DEFINING THE PHARMA CONTENT

For the purpose of this analysis, we define the pharma content value chain as six stages (see diagram below).

While we certainly believe that Gen AI tools can be applied to and assist with Strategy and Planning, we see more immediate opportunities and applications with Production (creation), the Approval process (Medical Legal Regulatory – MLR), Distribution and Analysis. So let’s dive in, starting with a closer look at Gen AI for Content Production.

CONTENT PRODUCTION: IN-SOURCE FOR CUSTOMISATION, OUTSOURCE FOR MOMENTUM

Gen AI tools have demonstrated remarkable capabilities in content generation across text, imagery, audio, and video. And even going a step further, coding and formatting content for the designated purpose / channel. For example, specialised tools can convert Microsoft Office documents into various designated formats, such as webpage code for WordPress or email code for Salesforce Marketing Cloud. For global and local brand teams, this means faster ideation, quicker localisation, and better adherence to regulatory frameworks. The decision to internalise or externalise will define the agility of your organisation.

REVIEW AND APPROVAL: IN-SOURCE FOR EVOLUTION, OUTSOURCE FOR CAPACITY

The pharma MLR process is generally considered to be notoriously slow and labour-intensive, and is seen as the most significant bottleneck in pharma content creation. Here, Gen AI shines by automating repetitive tasks like metadata extraction, flagging compliance risks, and pre-checking content against SmPCs and past approvals. But the stakes are high; errors in compliance can lead to costly penalties and reputational damage.

CONTENT DISTRIBUTION: IN-SOURCE FOR OWNERSHIP, OUTSOURCE WHEN NEEDED

Gen AI’s ability to generate personalised content variations is well-established, making it possible to move from “one-size-fits-all” to “one-size-for-each” content strategies. Traditional AI (i.e., machine learning) can also help enhance content distribution by segmenting audiences with high precision, ensuring that the right message reaches the right person at the right time.

However, the challenge lies in aligning this level of customisation with the speed of regulatory review. Until the approval process for personalised content is streamlined, the one-size-fits-all (or many) approach will persist, especially in smaller markets with limited resources for granular targeting.

PERFORMANCE ANALYSIS: IN-SOURCE FOR COMPETITIVE EDGE, OUTSOURCE FOR CONVENIENCE

While not directly related to Gen AI, performance analysis is an area where AI – in particularly machine learning (ML) – has already made significant contributions. AI-driven tools can analyse vast datasets, providing insights into content performance and enabling continuous improvement. As more user-friendly, i.e., less “techie” analytics platforms emerge, content creators will become less dependent on data specialists, allowing for more immediate and actionable insights to inform future content strategies.

CONCLUSION: THE FUTURE OF PHARMA CONTENT IS GEN AI-DRIVEN

Gen AI solutions are starting to become an integral part of the pharma content creation value chain, improving processes from production to review, distribution, and analysis. While “pilots” and various “initiatives” are found scattered across the industry as well as on the agency side, globally scaled success stories are rare. Nevertheless, the Gen AI revolution is making it feasible to internalise work that is still largely the domain of agencies. Based on Arcondis client work, research and estimations, we believe that companies can reduce their content-related costs by as much as 40% by applying Gen AI solutions and moving most of the content value chain internally.

By building internal capabilities with vetted and approved tools, you reduce costs, increase efficiency, build up in-house skills and maintain control. Please contact me if you would like to discuss the integration of Gen AI across the pharma content value chain. Our team of customer engagement specialists and AI experts will assist you from concept-definition to implementation.