Introducing Agentic AI: Its Revolutionary Potential in Pharma

Tanveer Ahmed Nasir, Vice President and General Manager, Product Management, IQVIA

Pooja Jain, Director, Product Offering and Strategy, IQVIA

The pharmaceutical industry stands at a pivotal moment in its digital transformation journey. While generative artificial intelligence (GenAI) has dominated headlines with its content creation capabilities, a more sophisticated form of AI technology, agentic AI, is emerging that promises to revolutionize how life sciences organizations approach commercial planning and execution.

BEYOND TRADITIONAL AI: THE POWER OF ORCHESTRATION

While GenAI excels at language-based tasks, it typically cannot coordinate multiple specialized functions to solve complex, multistep problems. Agentic AI, by contrast, uses AI agents—software entities that perform tasks autonomously using a range of AI-based techniques—to adeptly navigate these complexities. These capabilities are particularly crucial in commercial planning, where numerous interdependent decisions must be made across various domains.

As leaders in analytic solutions at IQVIA, we’ve observed how traditional AI systems struggle with the full scope and nuance of commercial planning. They can handle isolated tasks but lack the sophistication to manage entire workflows. Agentic AI changes this paradigm by coordinating multiple specialized agents across the entire commercial planning and execution cycle.

TRANSFORMING PLANNING CYCLES: A REVOLUTION IN EFFICIENCY

The impact of this technology on commercial planning cycles is profound. Currently, end-to-end planning and execution typically takes six months to a year and a half to complete. With agentic AI, we’re looking at compressing that timeline to just four to five months.

This acceleration comes from agentic AI’s coordinated approach across every stage of commercial planning. Let’s examine how this transforms each critical phase:

• In-budget allocation. Specialized AI agents analyze historical performance data, market conditions, and competitive landscapes to recommend optimal channel distribution. Rather than spending weeks manually analyzing spreadsheets, brand managers can now evaluate AI-generated scenarios that account for digital, face-to-face and media campaign effectiveness within a few days or less. These recommendations come with detailed rationales and projected outcomes, enabling faster, more informed decisions.
• Healthcare provider segmentation and targeting undergoes similar transformation. Traditional approaches often rely on basic demographic and prescribing data, requiring months of manual analysis. Our agentic AI system integrates multiple data streams—including behavioral patterns, patient populations, and practice characteristics—to create sophisticated, multidimensional segmentation models in days rather than months. These models continuously refine themselves based on real-world performance data, something impossible with traditional static approaches.
• Resource optimization and field force planning show perhaps the most dramatic improvements. Previously, determining optimal sales force size and distribution could take months of scenario planning. Agentic AI simultaneously evaluates thousands of variables—including territory workload, drive times, account value, and representative capabilities—to generate optimal territory structures. What’s more, these recommendations adapt in real time as market conditions change, ensuring resources remain optimally deployed throughout the year.
• Territory alignment and compensation planning,traditionally one of the most time-consuming phases, becomes remarkably more efficient. Rather than wrestling with complex spreadsheets and manual calculations, AI agents can generate balanced territories that optimize coverage while maintaining fair workload distribution. The system considers historical performance, geographic constraints, and account relationships to suggest alignments that maximize both efficiency and fairness.

THE HUMAN ELEMENT: A CRITICAL PARTNERSHIP

Let’s be clear: Agentic AI won’t completely automate commercial planning, nor should it. Rather than removing humans from the equation, we’re optimizing processes that currently require heavy manual intervention. If a task traditionally takes four months, we might reduce it to one month through agent-based automation.

This hybrid approach ensures that human expertise remains central to strategic decision-making while eliminating many of the time-consuming manual processes that currently slow down commercial planning cycles. For instance, while AI agents can rapidly analyze market data and suggest resource allocation, human strategists still make final decisions about market positioning and strategic investments.

THE BIGGEST CHALLENGE: LACK OF ADOPTION

In our experience, the biggest challenge isn’t technological—it’s organizational. We’re challenging longstanding processes and promoting more efficient and effective methods. The main hurdle is helping teams understand and embrace these changes, which can be achieved through enhanced transparency and a measurement framework.

SUCCESS METRICS THAT MATTER

With experience implementing agentic AI across various organizations, we’ve identified several critical metrics that demonstrate its transformative impact. Improved accuracy in planning decisions manifests in multiple ways: We typically see a 25% to 30% reduction in territory adjustment requests after initial alignment, indicating more stable and well-designed territories from the start. Resource utilization improvements become evident as field teams spend less time driving between accounts and more time in valuable customer interactions.

Time savings materialize across every planning stage. Budget allocation scenarios that once took weeks to develop can be generated and refined in days. Territory alignment cycles that traditionally consumed months now reach completion in weeks. And sophisticated healthcare provider segmentation and targeting can happen in near real time with enhanced personalized engagement. Perhaps most importantly, these efficiency gains don’t come at the cost of quality—in fact, we often see improved satisfaction from both field teams and management.

Cost reduction through process optimization extends beyond obvious labor savings. By more accurately predicting resource needs and optimizing deployment, organizations can right-size their field forces while maintaining or improving coverage. Additionally, better-aligned territories reduce travel expenses and improve representative retention by creating more balanced workloads.

THE FUTURE OF AGENTIC AI

What we find most exciting about agentic AI is its potential for growth. While today’s generative AI excels at language-related tasks, it’s still developing in areas requiring complex analytical thinking. As large language models evolve to handle sophisticated analytical tasks more effectively, we’ll see even greater potential for optimization.

We envision a future where thousands of specialized agents handle different aspects of commercial planning and execution. This proliferation of specialized agents, coordinated by increasingly sophisticated orchestration systems, will enable even greater efficiency gains while maintaining necessary human oversight for strategic decisions.

IMPLEMENTATION: A MEASURED STRATEGY

The “crawl, walk, run” approach we advocate begins with careful selection of initial implementation areas.

In the crawl phase, organizations typically start with one discrete planning component—often territory alignment or basic budget allocation. This allows teams to become comfortable with the technology while delivering quick wins that build confidence.

During the walk phase, we expand to include integrated planning components—for instance, combining territory alignment with call planning optimization or linking budget allocation with targeting strategies. This phase typically lasts three to six months as organizations build confidence in the system’s recommendations and refine their processes.

The run phase represents full implementation, where multiple AI agents work in concert across the entire commercial planning cycle. Here, we see the full benefits of orchestration as each component informs and optimizes the others. Organizations typically reach this stage within a year of initial implementation, though the exact timeline depends on organizational readiness and change management effectiveness.

FUTURE-PROOFING COMMERCIAL OPERATIONS

As life sciences companies navigate an increasingly complex commercial landscape, the ability to make faster, more informed decisions becomes crucial. Agentic AI represents not just an efficiency tool but a fundamental shift in how we approach commercial planning and execution. The technology’s promise lies in both its ability to accelerate existing processes and in its potential to enable entirely new approaches to commercial planning that weren’t previously possible. Organizations that embrace this transformation while maintaining a balanced approach to human expertise and automated efficiency will be best positioned for success in the evolving life sciences landscape.

Looking ahead, we believe agentic AI will become an indispensable part of commercial operations. The key to success lies not in rushing to adopt every new capability but in thoughtfully implementing these technologies in ways that enhance rather than replace human expertise. By taking a measured approach to implementation and focusing on clear business outcomes, organizations can harness the power of agentic AI to transform their commercial operations for the future.

Tanveer Ahmed Nasir, Vice President and General Manager, Product Management; Pooja Jain, Director, Product Offering and Strategy, both with IQVIA