Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
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Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more
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VIEW ROLESIn life sciences, every second counts. So, the ability to make fast, accurate decisions can mean the difference between successful treatments and missed opportunities. Imagine the applications in pharma and MedTech for a new level of artificial intelligence that goes beyond simple assists to autonomously devise plans, set goals, and execute strategies on its own.
Get ready for agentic AI, which represents a fundamental shift in how our industry will approach commercial planning and execution. Gartner® predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously through agentic AI, up from 0% in 2024.1 This blog will explore the concept of agentic AI, its differences from predecessor technologies, and its potential to enhance and redefine how the industry operates over the next decade.
Everyone has become familiar with large-language model (LLM) generative AI models like ChatGPT or Copilot. These tools can create content, videos and images, answer questions, and even help write code. They generate this output based on specific human prompts, hence the term generative AI. However, this technology has limitations—namely, its content is limited to already existing data, which means that it cannot create new ideas or solutions. It can also hallucinate or disseminate false information.
Enter agentic AI. If generative AI is like an eager high-school intern, agentic AI is its older brother with advanced degrees and training as a professional concierge. While agentic AI applies some aspects of generative AI, its capabilities are far greater.
As an example of how those two types of AI differ, imagine you’re managing a complex clinical trial involving thousands of patients across multiple research sites. You need to ensure that patient enrollment targets are met, data collection remains compliant, and protocol deviations are minimized. If you ask generative AI for advice, it might produce a helpful checklist based on historical best practices or industry guidelines. However, it stops there — the execution is still on you.
Agentic AI takes it a step further. It doesn’t just provide recommendations and shortcuts. It takes action, like an autonomous research and lab assistant. It can monitor real-time enrollment rates, spot delays at specific sites, and reroute recruitment efforts to optimize results. It can even flag compliance issues before they occur and suggest corrective actions. In this scenario, agentic AI doesn’t just offer advice. It collaborates with you to solve problems and drive the trial forward.
Unlike generative AI, which depends solely on human input to generate output, agentic AI uses autonomous “agents” to perform tasks, make decisions, and independently interact within their environments without constant human administration.
These agents can automate routine tasks like data collection or payroll. They can also execute staggeringly complex tasks, such as interacting with diverse systems, analyzing pertinent datasets, and providing thoughtful responses and personalized solutions. Like generative AI, agentic AI can create reports about that data in simple, human language.
In short, agentic AI is an AI system that can act independently to perform tasks for a person (or another system). This type of AI has the agency to make decisions, take action, and even interact with outside environments beyond the original data.
Agentic AI has the potential to compress typical timelines for end-to-end commercial planning and execution in life sciences from 6–18 months to as little as 4–5 months. This translates into faster product launches, quicker market penetration, and significant cost savings. Acceleration of such a magnitude is made possible by agentic AI’s coordinated approach across every stage of commercial planning.
Budget allocation
Agentic AI can generate scenarios for brand managers to evaluate that account for digital, face-to-face, and media campaign effectiveness within a few days or less. Accompanied by detailed rationales and projected outcomes, these recommendations allow faster, more informed decisions than manual spreadsheet analysis.
Healthcare professional (HCP) segmentation and targeting
Agentic AI integrates multiple data streams (e.g., behavioral patterns, patient populations and practice characteristics) to create sophisticated, multi-dimensional HCP segmentation models in days rather than months. Unlike traditional static approaches, these models continuously refine themselves based on real-world performance data.
Resource optimization and field force planning
Agentic AI simultaneously evaluates thousands of variables (e.g., territory workload, drive times, account value and representative capabilities) to generate optimal sales force size and distribution. This drastically improved method optimizes resources by adjusting to changing market conditions in real time.
Territory alignment and compensation planning
Agentic AI can generate balanced territories that optimize coverage while maintaining fair workload distribution. The system suggests alignments that maximize efficiency and fairness based on historical performance, geographic constraints and account relationships.
Agentic AI works to accelerate innovation. Imagine that you’re conducting an orchestra. Each instrument has its part, perfectly timed to contribute to building toward the final crescendo. In a way, that’s what agentic AI can do. In life sciences, tasks and tools are soloists or individual agents operating under the conductor to deliver flawless commercial planning and execution.
Agentic AI is more than just automation. Each agent excels in a unique task, from budget allocation for brand managers to segmentation and targeting HCPs. Combining these moving pieces using traditional workflows takes months (sometimes years!) of manual processes, endless spreadsheets and presentations. However, agentic AI transforms this process and reduces timelines from six to eighteen months to less than two months.
Consider this. Say you’re a brand manager tasked with channeling resources across digital, face-to-face, and media campaigns. Typically, you’d be buried in manual resource allocation. Even deciding the number of HCPs to target for a specific campaign is tricky. With agentic AI, each function is automated, passing relevant insights and recommendations to the next in line. Then, these agents work as a chain, eliminating bottlenecks and ensuring you have accurate insights in real time.
The promise of agentic AI lies in its potential to enable entirely new approaches to commercial planning that were previously impossible. 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. Agentic AI is poised to become an indispensable part of commercial operations.
Embracing agentic AI for commercial planning and execution is a whole new experience that can feel both exhilarating and daunting. Unlike traditional AI, which is often narrowly focused on specific tasks, agentic AI orchestrates multiple AI “agents,” each responsible for different aspects of commercial planning, like budget allocation or segmentation.
This leap forward is an undeniable upgrade, but it’s not as simple as flipping a switch. Integrating agentic AI requires careful change management, training, and, most importantly, a willingness to shift perspective from “we’ve always done it this way” to “how can this make us better?” For companies, the key to success lies in adopting a “crawl, walk, run” strategy, easing into the technology, proving its benefits, and then ramping up to full-scale deployment. Transparency efforts and a solid measurement framework can help teams understand and embrace how new approaches drive efficiency and effectiveness. Ultimately, agentic AI will adapt to even the most reluctant tech user, making it easy for everyone to use.
While AI is becoming a significant part of modern healthcare, finding the balance between advancement and integrity is crucial. Ethics, privacy concerns and regulations must still have their place. While agentic AI can help life sciences move forward, it will never replace the human touch.
The team at IQVIA can help you find that balance. Our AI-powered suite of tools enhances speed, accuracy, coordination and scalability for every part of your life sciences enterprise. These tools are vital to achieving efficiency — without sacrificing quality.
1 Gartner Press Release, Gartner Identifies the Top 10 Strategic Technology Trends for 2025, October 21, 2024. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
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