How Agentic AI is Reclaiming 40% of Pharmacovigilance Capacity

Deepanshu Saini, Director of Program Management at IQVIA

Pharmaceutical companies are tasked with managing vast volumes of patient data, product information and safety reports. Yet, much of this valuable intelligence remains buried in transcripts, call recordings or unstructured documents. Regulators depend on this information to understand the full story of a drug when identifying potential risks and evaluating the safety and efficacy of treatments.

Modern pharmacovigilance demands more than compliance checklists. Today’s pharmacovigilance requires complete transparency on every medically relevant detail, no matter where that data originates.

From data fragmentation to digital cohesion

To close these gaps in how information is reported, life sciences organizations are increasingly adopting intelligent automation. Simultaneously, advances in artificial intelligence, natural language processing and data orchestration tools are mitigating the rate of information slippage found in the manual review process. 

Automation that extracts and organizes medically relevant data enables safety teams to convert fragmented, unstructured information into structured, analyzable insights. Traditionally, human-based teams would comb through call logs and documents. Today, AI-powered systems can identify hidden contextual clues, such as changes in mobility, dosage errors or device malfunctions, and route them into structured fields for the team’s review.

According to McKinsey, 32% of life sciences organizations plan to invest over $5 million in generative AI this year, up from 20% in 2024. The significant investment surge goes beyond automation. Rather, it is an investment into continuing digital transformation. For every $1 spent on technology, organizations allocate roughly $5 to change management and capability-building. 

Life sciences organizations are building their budgets around holistic redesigns instead of point-solution adoption.

Intelligent automation in action

Modern AI systems are transforming how pharmacovigilance teams detect, document and report adverse events. By automating and extracting unstructured data, these tools help ensure that all clinically relevant information is captured accurately and efficiently. Organizations adopting intelligent automation can:

Organize fields of data: From patient demographics to reporter details and event descriptions, all tools extract and structure information from transcripts and clinical notes. Identify subtle risk factors: Advanced intelligence and automation tools can uncover hidden data points, such as dosage irregularities or symptom patterns, issues that the typical manual review might overlook. Accelerate report generation: While legacy processes sufficed in the past, modern systems are designed to eliminate time-consuming manual tasks, so experts can focus on contextual analysis and regulatory interpretation.Enhance reporting accuracy and speed: Clinical data is often housed across numerous databases, complicating the submission and review process. With AI and automation, data can be consolidated across disparate systems into a comprehensive safety record.

The solution is not to replace human expertise but to amplify it by freeing experts to focus on higher-level analysis and decision-making.

The rise of agentic AI in life sciences

Within the rapid adoption of AI, there is a subsequent wave of advancement. Agentic AI is tasked with handling specialized workflows with minimal supervision. It continuously learns and adapts in real time, and research indicates it could release 25–40% of human capacity while increasing operational efficiency by 3.4–5.4 percentage points over the next few years.

From an automation standpoint, agentic AI surpasses the basic capture and organization of information. It is suited for advancing interoperability by coordinating across teams and their systems. These agents are specifically generated to monitor call transcripts, emails and safety databases in real time, flagging high-risk cases and routing them directly to reviewers. This continuous flow of knowledge accelerates reporting timelines and ensures the most urgent signals receive immediate attention. 

For safety teams, Agentic AI represents the next step in industry maturity, evolving into one where automation not only supports workflows but intelligently orchestrates them. Through this orchestration, teams can shift their focus from administrative tasks to meaningful intervention and analysis.  

Building a foundation for continuous compliance

The process of embedding AI and automation into pharmacovigilance is more than simply adopting a program and turning the key. It requires a culture that values data integrity and transparency. The programs that achieve success are the ones that start with unified data architectures that connect CRM, call center and document management systems. These programs prioritize explainable AI models that demonstrate how every conclusion is reached and meet regulatory expectations for clarity and traceability. Through the establishment of robust governance frameworks, automated tools are held to the same scrutiny supported by quality checks and audit trails as human reviewers. 

Intelligent collaboration is the future

As budgets for AI and additional technology stacks see exponential gain and systems mature, the question for pharmacovigilance teams is no longer whether to automate, but how to do so responsibly. Intelligent automation already processes safety data at an unprecedented scale. The opportunity at hand now is for teams to spend more time on analysis, context clues and patient safety.

The future of safety reporting is based on intelligent collaboration. It is one with machine precision designed to augment human discernment to deliver faster, more reliable outcomes. Automation doesn’t just close reporting gaps, it transforms pharmacovigilance into a proactive, learning discipline built on transparency, trust and shared intelligence.

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About Deepanshu Saini

As Director of Program Management at IQVIA, Deepanshu oversees large-scale transformation projects for the implementation of Vigilance Detect, IQVIA’s AI-powered pharmacovigilance technology & its associated services for key clients.