GenAI in biopharma marketing: Key decisions for charting your journey

Generative AI (GenAI) has enormous potential for assisting biopharma marketing teams. Faced with rising demand for relevant, personalized content across multiple digital channels, marketers can use GenAI tools to deliver more content, faster and more efficiently than before. Though the large language models (LLMs) that power these tools are still developing, marketers can benefit from numerous use cases now—from content personalization and automated translation to customer service and compliance auditing.

But biopharma marketers shouldn’t dive into GenAI hastily. Making some key decisions first can help ensure that your marketing team makes the most GenAI while avoiding pitfalls.

Reviewing technical options, evaluating providers, assessing skill requirements, considering usage policies, and setting performance metrics can set you on the right path for GenAI implementation.

Marketing teams have multiple options for how to implement GenAI models. You could deploy existing models as they are. Doing so is the fastest way to incorporate GenAI into workflows and start realizing benefits. Or you could boost the capabilities of existing models - such as ChatGPT or Google Gemini - for your own use cases.

If your organization has deep AI and machine learning skills, you might be able to build and operate your own model, using your own data. Building a new AI model can provide a significant competitive advantage: The content that your marketing team produces will be unique to your organization. This approach, however, can be complex and time consuming.

There are several organizations that provide models. The first step in selecting a provider is to decide which use cases are most important to you. Where are your greatest inefficiencies and pain points? Where might AI save your marketing team the most time and deliver the most powerful impact? You can then evaluate providers’ models for their support of those use cases. You might decide to diversify, using models from multiple providers to avoid vendor lock-in.

Depending on your decision about buying, boosting, or building, your organization might need employees with technology skills. Marketers should work with IT teams to decide whether to train existing staff, hire new full-time employees, or work with an external consulting firm to fill gaps.

It might be tempting to apply GenAI to a wide range of marketing tasks, but these tools still have some important limitations. For example, they occasionally “hallucinate,” generating content that sounds good but isn’t accurate. Consequently, GenAI should only be used to create content that humans can carefully review.

Before implementing models, your marketing team should establish policies on using GenAI. You might decide, for example, to use GenAI to generate social media posts or variations of ad headlines but not write full blog articles or white papers. Your leadership team will then need to educate all marketers to make sure they follow these policies.

Implementing GenAI can require a significant investment—and no doubt your leadership team will want to see strong returns. To measure ROI, you should set quantitative performance goals and then determine the best ways to minimize costs while achieving those goals. In some cases, you might find that owning your own AI models will deliver the best ROI—even if that ownership is the most costly approach for introducing this technology into your organization.

To maximize the value of GenAI, you need to integrate it with a digital experience platform (DXP). Exploring your platform options should be part of your GenAI planning.

The right DXP can make GenAI capabilities available alongside your content creation tools within a single, unified workflow. You can enter prompts, use stored information to improve the accuracy of results, review all AI-generated content, and transfer content to the right place, all without having to switch interfaces. A composable, AI-ready platform will help you focus on the most impactful use cases for your organization and start delivering value rapidly.

Ready to learn more about using GenAI in biopharma marketing? Read the white paper.