The basis for AI success in pharmaceutical sales - data, strategy and the right team

Having shed light on the initial euphoria and subsequent disillusionment in dealing with AI in pharmaceutical sales, we are now focussing on the fundamental building blocks for successful implementation. Our experience in recent months has shown that there are three crucial pillars: the quality of the data, a clear strategic direction and the right team.

1. the purity and availability of the data: As the saying goes, ‘Garbage in, garbage out.’ AI models are only as good as the data used to train them. In the complex environment of CRM systems in pharmaceutical sales, this means that we have to deal intensively with data quality, data integration and data harmonisation. A superficial connection to unclean or poorly structured data will inevitably lead to unreliable and unhelpful results.

2. a clear strategic focus and the definition of use cases: Before we dive into the technical details, we need to ask ourselves the fundamental question: What specific added value should the use of AI in pharmaceutical sales bring? Without clearly defined use cases based on real business challenges, we run the risk of getting lost in technology-driven projects that ultimately make no measurable contribution. Close collaboration with the specialist departments is essential here in order to identify and prioritise the relevant use cases.

3. the interdisciplinary team with the right expertise: It is not enough to form a task force of non-specialist employees. The success of AI projects in pharmaceutical sales requires an interdisciplinary team that has in-depth business knowledge and an understanding of the specific challenges of the industry as well as the necessary data expertise and technical know-how in the field of AI. Only the interplay of these different competences enables the development and implementation of solutions that generate real added value.

Another aspect that should not be neglected is the issue of data security and compliance. The highest standards must be adhered to, especially in the sensitive pharmaceutical environment. Choosing the right technology and taking data protection regulations (GDPR) into account are of crucial importance here.

In the fourth and final part of this series, we will provide specific insights into our experiences and summarise the key principles for successful AI implementation in pharmaceutical sales.