Pharmaceutical companies are significantly enhancing their pharmacovigilance capabilities through the adoption of agentic AI, reclaiming up to 40% of operational capacity. This advancement comes amid a growing need to manage extensive volumes of patient data, product information, and safety reports. Traditional methods, which often leave valuable insights buried in unstructured documents, are giving way to intelligent automation technologies that ensure critical information is no longer overlooked.
The current landscape of pharmacovigilance demands comprehensive transparency regarding every medically relevant detail, regardless of its source. As regulatory agencies require detailed data to assess drug safety and efficacy, the ability to efficiently collate and analyze information is paramount.
Transforming Data Management
Life sciences organizations are increasingly turning to intelligent automation to close gaps in data reporting. According to a report by McKinsey, 32% of life sciences firms plan to invest over $5 million in generative AI this year, a notable increase from 20% in 2024. This investment reflects a broader commitment to digital transformation, with companies allocating approximately $5 for change management for every $1 spent on technology.
The introduction of AI-powered systems has transformed how pharmacovigilance teams operate. These systems automate the extraction and organization of medically relevant data, enabling safety teams to convert fragmented, unstructured information into structured, analyzable insights. By identifying hidden contextual clues—such as changes in mobility or dosage errors—AI tools streamline the review process, allowing teams to focus on high-level analysis.
For instance, previous manual methods required human teams to sift through call logs and documents. Now, advanced AI can efficiently detect subtle risk factors and expedite report generation. This shift not only enhances reporting accuracy but also consolidates clinical data from various sources into comprehensive safety records.
The Emergence of Agentic AI
The rise of agentic AI marks a significant evolution in pharmacovigilance. Designed to manage specialized workflows with minimal supervision, this technology adapts in real time and has the potential to release between 25–40% of human capacity, enhancing operational efficiency by 3.4–5.4 percentage points in the coming years.
Agentic AI goes beyond simple data capture; it fosters interoperability across teams and systems. These intelligent agents monitor call transcripts, emails, and safety databases, flagging high-risk cases for immediate review. This real-time knowledge flow accelerates reporting timelines, ensuring urgent signals receive prompt attention.
The integration of agentic AI does not replace human expertise but rather amplifies it. By automating routine tasks, safety teams can dedicate more time to meaningful analysis and decision-making.
As organizations embed AI and automation into their pharmacovigilance processes, they face the challenge of fostering a culture that prioritizes data integrity and transparency. Successful programs start with unified data architectures that connect various systems, ensuring that AI models are explainable and meet regulatory standards for clarity and traceability.
In conclusion, intelligent collaboration lies at the heart of the future of safety reporting. As AI technologies mature and budgets for automation rise, pharmacovigilance teams must focus on how to implement these tools responsibly. The goal is to transform pharmacovigilance into a proactive discipline rooted in transparency, trust, and shared intelligence, ultimately improving patient safety outcomes.
About Deepanshu Saini: As the Director of Program Management at IQVIA, Deepanshu oversees large-scale transformation projects, including the implementation of Vigilance Detect, IQVIA’s AI-powered pharmacovigilance technology, for key clients.
