How Agentic AI Can Rescue Pharma's Commercial Engine
Market pressures squeezing margins
The pharmaceutical industry faces mounting economic pressure. Rising raw material costs and persistent supply chain disruptions are compressing margins while governments and payers press for lower drug prices. At the same time, an expiring-patent wave threatens roughly 300 billion dollars in potential sales by 2030, exposing many companies to steep declines in branded revenue as generics and biosimilars enter the market.
Rising development and launch costs
Bringing new drugs to market is becoming more expensive. Analysts estimate the cost per launch has been growing around 8 percent annually and reached approximately 4 billion dollars in 2022. These climbing costs increase the stakes for commercial teams, requiring more targeted, efficient approaches to maximize returns on investment for each product.
Changing care delivery and demand for personalization
Patients and clinicians now expect more personalized therapies and services. Precision drugs and targeted therapies address specific patient needs more effectively but are often complex and costly to produce, limiting their market to smaller patient populations. Commercial teams must adapt by delivering more tailored messaging and services to reach the right prescribers and care settings.
Sales and marketing must become more precise
The attention of health-care professionals is harder to gain. Estimates show that biopharma outreach reached about 45 percent of HCPs in 2024, down from 60 percent in 2022. Delivering timely, relevant communications through personalized, real-time channels is essential to rebuild trust and engagement. However, creating that level of personalization increases the volume of content and interactions that require medical, legal, and regulatory review, producing bottlenecks that can delay campaigns and cost opportunities.
What agentic AI brings to commercial pharma
Agentic AI refers to systems that can autonomously plan, execute, and iterate on multi-step tasks with minimal human supervision. In commercial pharma, these capabilities can be applied across functions:
- Content orchestration: autonomously generating tailored materials for distinct HCP segments, prioritizing items for medical, legal, and regulatory review, and routing assets to the right approvers to reduce review cycles.
- Outreach automation: coordinating multichannel, personalized touchpoints in real time and adapting messaging workflows based on HCP responses and engagement signals.
- Data-driven targeting: synthesizing disparate datasets to identify high-value prescribers, emerging therapeutic niches, and optimal messaging strategies at scale.
- Operational efficiency: automating repetitive administrative tasks, speeding up approval workflows, and reallocating human resources toward higher-value strategic work.
Potential impact and caveats
When implemented responsibly, agentic AI can help commercial organizations improve reach to HCPs, shorten time-to-market for marketing campaigns, and cut operational costs linked to manual coordination and review. But adoption requires careful governance, transparent validation, and close integration with medical, legal, and regulatory teams to ensure compliance and preserve patient safety.
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This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. AI tools that may have been used were limited to secondary production processes that passed thorough human review.