Transforming life sciences workflows with agentic AI

Many clinical and commercial workflows in life sciences remain manual, fragmented and slow — creating friction as demands for speed and precision increase.

Agentic AI introduces a different model: Embedding intelligence directly into workflows, not just into analysis. This shift enables teams to move from incremental efficiency gains to fundamentally new ways of executing work across the lifecycle.

A unified approach across the entire lifecycle

One of the defining advantages of agentic AI is its ability to operate across the full life sciences lifecycle, from early clinical development through commercial engagement:

• In clinical development, agents can support activities such as protocol analysis, data management and document generation. These trial activities have traditionally been time‑intensive and highly manual. Agentic capabilities can help accelerate this work, reducing operational burden.
• In real‑world evidence and medical affairs, agents can streamline literature review, extract and analyze data, and support research workflows — driving faster access to insights that inform both scientific and business decisions.
• On the commercial side, agentic systems can support earlier decisions such as geographic opportunity, channel strategy and pricing scenarios by market, while also enabling patient segmentation, field engagement and data-driven marketing.

Taken together, these advanced capabilities reflect a broader shift: AI is becoming a unifying layer that connects data, decisions and execution across the enterprise.

Two examples illustrate the advantages that agentic AI can bring to life sciences.

Content generation: Shortening timelines and increasing efficiency

The impact of agentic AI becomes most visible when applied to high-friction workflows.

Consider document generation in clinical trials, such as informed consent forms:

• Traditionally, this process requires intensive manual review of protocols and supporting documents.
• Teams extract relevant information, draft content and iterate across reviews — often over the course of several weeks.

Within an agentic workflow:

• Specialized agents extract data from protocols and investigator brochures.
• A draft ICF is generated and structured automatically, with templates populated as part of the process.
• Outputs are evaluated within a coordinated system that includes human in the loop oversight.

This goes beyond gains in speed. It represents a fundamental shift in how work is structured and completed — moving from linear, manual processes to intelligent, orchestrated systems.

Complex site identification: Improving both speed and quality in decision-making

Site identification for clinical trials is another workflow well suited to agentic AI:

• Identifying sites requires balancing multiple factors, including patient eligibility, geography and operational feasibility.
• While this process has seen efficiency gains through automation and connected data, generating and iterating on the site list still takes substantial time and resources.

Agentic AI simplifies and strengthens site selection by:

• Analyzing protocols to identify suitable trial sites across countries globally.
• Deploying multi agent workflows to evaluate criteria and generate transparent, explainable recommendations.
• Enabling collaboration around scoring and inspection, allowing experts to refine and validate identified sites within the workflow.

Although agentic AI improves efficiency, the greater value lies in better decision intelligence and transparent weighting of stakeholder priorities. Rapid scenario evaluation that combines data driven insights with human expertise enables more informed, confident choices.

Enabling enterprise-scale transformation with IQVIA.ai

To realize the full potential of agentic AI, life sciences organizations need more than individual tools they need a unified platform that connects data, intelligence and execution.

Recently launched at NVIDIA GTC 2026 in San Jose, California, IQVIA.ai is designed to meet this need as a unified agentic AI experience purpose built for life sciences.

IQVIA.ai provides a single, secure access point where customers can deploy, manage and scale commercially available IQVIA powered AI tools, agents, insights and workflows across the enterprise.

The platform enables organizations to:

• Orchestrate tasks and insights across the full lifecycle, from clinical development through commercial execution.
• Combine a conversational interface with an extensible catalog of intelligent agents.
• Integrate AI directly into workflows through agentic orchestration capabilities.

As agent counts grow, orchestration and system design become increasingly important. IQVIA will continue to build and deploy hundreds of agents across the lifecycle, supported by ongoing collaboration with NVIDIA to advance AI infrastructure, performance and validation.

In parallel, IQVIA continues embedding agentic systems directly into the workflows we use to deliver clinical trials, in order to accelerate timelines, improve quality and predictability, reduce operational burden and enable smarter, data-driven decisions across trial design, start-up, conduct and close-out.

Moving from experimentation to impact

Life sciences organizations now have an opportunity to move beyond experimentation and embed agentic AI directly into how work gets done. By bringing intelligence into clinical and commercial workflows, teams can execute faster, with greater precision and at greater scale. Platforms like IQVIA.ai provide a trusted foundation for this transformation, enabling organizations to move with confidence as they operationalize AI at scale — turning potential into measurable enterprise impact.