Unraveling Agentic AI in the Context of Healthcare
The healthcare ecosystem is vast and complex, involving multiple actors such as patients, pharmaceutical companies, hospitals, health plan operators, regulators, and, of course, healthcare professionals — HCPs. Among all these stakeholders, HCPs play a unique and strategic role: they are the trusted intermediaries between the industry and the patient. They recommend treatments, prescribe medications, monitor patient progress, and often directly influence treatment adherence.
For this reason, over the last few decades, the pharmaceutical and healthcare industry has been investing heavily in building and maintaining relationships with these professionals. According to data from Evaluate Pharma and McKinsey, globally, around 30% of pharmaceutical companies’ commercial budgets are allocated to HCP engagement initiatives, representing over US$ 90 billion per year — these initiatives include actions by medical representative teams, scientific congresses, in-person events, continuing medical education, and distribution of technical and scientific materials. In Brazil, large groups allocate between 15% and 25% of their marketing and relationship budgets to actions directly aimed at HCPs.
The return on these investments, although difficult to measure accurately, is of significant
strategic importance: studies indicate that up to 60% of prescription and medical
recommendation decisions can be directly influenced by interactions between companies
and healthcare professionals. In other words, the impact of these relationships is profound
— yet still underutilized in terms of scale, personalization, and intelligence.
It is in this context that Agentic AI emerges as a game-changer. By combining LLMs
(Large Language Models) with autonomous and interactive decision flows, it opens up
the possibility of scaling relationships with HCPs in a more personalized, efficient, and
data-driven way.
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