The use of generative artificial intelligence (AI) is not just a thought experiment in life sciences and other aspects of healthcare. Companies have moved from experimenting to the execution stage. Today, gen AI is bringing impactful results in life sciences marketing. These companies rely on consulting firms to devise go-to-market strategies with the help of AI. It helps with the long-term vision of building meaningful relationships with customers.

Use of generative AI for life sciences marketing

There are several areas in which generative AI for marketing is used in pharma and medtech companies. Here are some of the key areas:

Concept creation

Pharma and medtech companies are using generative AI for creative concept ideation. Life sciences leaders equip marketers with the right AI tools to accelerate concept creation for new campaigns. It has been seen that AI pilots have produced quality concepts in less time, which results in faster campaign launch. In addition, it also minimized the need for multiple iterations and eliminated agency fees.

In-house content derivative generation

Derivative content generation is a big thing in the pharma and medtech sectors. Companies are looking for ways to optimize it once the new campaign is final. Agency-of-record collaborations are still preferred for initial asset production, copy refinement and creating channel specifications. However, companies are using modular content adoption and automation for derivative content generation from pillar content. It has a huge positive impact on cost optimization.

Medical-legal review process reengineering

Medical-legal review (MLR) is an important part of the medtech and pharma companies. It is slow and often confusing because it requires the involvement of various stakeholders. This results in delayed content creation for the new launch on the market. Many companies are taking an alternative route to simplify and accelerate the MLR process for low-risk content, such as clinical trial solutions, the impact of new drugs on certain diseases and more.

Insight mining

This is yet another area where generative AI is used in life sciences marketing. Organizations are focusing on integrating primary and secondary data for insight mining. They are using AI to draw relevant insights from unstructured market research data. Large language models have proved to be very helpful and provide real value. Marketers are combining unstructured and structured data to identify market gaps and hidden potential. For example, a medtech organization has combined call center data with research transcripts to empower marketers to ask the right questions from the audience to get real-time insights.

Though the use of generative AI has improved in the past couple of years, there is huge potential yet to be explored. Marketers are using AI in a limited area, which can change by introducing a systematic approach for a better adoption rate. Life sciences leaders can lead by example. They can use generative AI for the entire workflow, from start to finish, to showcase the potential of AI. It helps eliminate hesitation and makes marketers excited about using AI in all areas. 

However, the execution is not that easy. Some market leaders are concerned about adoption hurdles, operating model changes and unknown return of investment realizations. These things can increase costs initially. Systematic adoption of generative AI is the answer for gradual implementation across different marketing areas in pharma and medtech companies.