Artificial intelligence (AI) is embedded in nearly every aspect of pharmaceutical operations. But in 2026, its role is poised to change dramatically – from delivering precise and predictive insights, to carrying out intelligent actions.
This transformation is widely referred to as “the agentic shift.” Traditional AI models excel at quickly creating insights and predictions from massive amounts of data. Agentic AI goes further, connecting multiple data sources and learning to act on them. This allows agentic AI models to perform intelligent automation and actions, delivering greater value to the pharmaceutical industry.
AI will orchestrate faster decision making and reduce manual effort to help pharma companies accelerate their performance in 2026 by shifting from an insight engine to an active participant in pharmaceutical operations.
New possibilities with AI
Agentic AI unlocks new efficiencies. In medical writing it’s being used to process and summarize unstructured documents to create submission-ready content faster. And with its ability to analyze large datasets, provide thoughtful responses, execute both routine and complex tasks and continuously learn and adapt, agentic AI can help pharma companies operate smarter and faster across the enterprise.
Three ways this AI evolution likely will reshape pharma operations in 2026 include:
1. Redefining physician engagements
As physicians gain greater access to clinical insights and AI-powered decision-support tools, their expectations for pharma engagements are shifting from transactional interactions to more consultative, value-driven relationships.
This evolution doesn’t eliminate the need for reps and Medical Science Liaisons (MSLs); it elevates their role. Field teams must now deliver deeper scientific expertise, tailored insights and personalized resources that align with each physician’s clinical context and workflow.
Agentic AI can help field teams meet these rising expectations by curating relevant data, generating dynamic content and enabling more timely and meaningful conversations. In this new landscape, effective engagement isn’t about delivering more information; it’s about delivering precise, context-aware support that earns attention and builds trust.
2. Improving omnichannel intelligence and agility
AI isn’t only enhancing how pharma reps and MSLs communicate with physicians – it’s transforming the entire omnichannel ecosystem.
Today, if a campaign is underperforming, marketing teams may need to perform complex and time-consuming data analysis to understand why. Agentic AI can help marketing teams quickly understand why certain messages aren’t landing and adjust their strategy.
AI can even create digital twins or virtual models, of physician personas. Marketers can then test messages against specific groups, allowing them to evaluate and refine communications before they reach physicians.
3. Empowering teams across the enterprise
Agentic AI enables pharma companies to deploy a digital workforce of highly knowledgeable and efficient companions to support human workers in every function. These agents have the potential to shave days, weeks or even months from processes, helping pharma companies work more efficiently and ultimately provide better outcomes to patients, faster.
For example, a lab and research agent can help clinical trial teams optimize the results of trials by tracking enrollment rates, flagging delays at sites and adjusting recruitment efforts. An HR agent can automate payroll processes. And a sales agent can evaluate variables like drive times, account value and territory workloads to optimize the size and distribution of a sales force.
AI agents custom-built for life sciences and healthcare are already available and being used by some of the world’s largest pharma companies.
What’s needed
While there’s momentum behind the pharma industry’s adoption of AI, evolving AI use cases from insights to action comes with some inherent challenges. It requires a willingness to change and the ability to steer through technical organizational and behavioral barriers.
Some components that pharma companies will need to have in place to realize the transformative promise of agentic AI include:
AI-ready data: A benefit of agentic AI is it doesn’t require full data harmonization. Agentic models can connect across disparate datasets and use frameworks like a multi-channel platform (MCP), reducing the need for exhaustive data integration.
Data does still need to be AI-ready. This involves making sure that it is in a standardized format that AI models can efficiently process, despite originating from diverse sources.
High-quality data also matters. Continuous quality assurance should pair automated tools with human oversight to help make sure any data quality issues are spotted and addressed quickly. This way, agentic AI models can understand and act on data without creating hallucinations or biases.
The processes of data cleansing, de-duplication and validation give confidence that the data is accurate, whether it came from an administrative dataset, registry, clinical trial or other source.
Additionally, the data needs to be strictly governed with privacy safeguards, to ensure the responsible and secure use of sensitive healthcare data in alignment with regulatory standards.
Clear, confident leadership: Experimentation is necessary to innovate. The companies that will find the most success with AI will be those with leaders that have the conviction to embrace AI and apply it to address strategic priorities. These leaders recognize that a period of change is a necessary part of an AI strategy that can deliver significant and sustained business value.
A change-ready culture: Change can be difficult, especially when it’s transformative. AI doesn’t just require that people use a new tool – it requires them to embrace entirely new ways of working.
However, just like racecar drivers must be willing to change their tires when they’re in the lead as part of a long-term strategy, pharma company cultures must be willing to change how they operate even when their organizations are ahead or they too risk seeing the competition pull ahead of them.
Change starts at the top. Pharma leaders must demonstrate a belief that AI-driven transformation is necessary. And they must cultivate a culture that embraces experimentation and adaptability if they want employees to view AI not as a threat but rather an enabler.
The year of intelligent action
2026 will mark the year that AI evolves from informing pharmaceutical operations to driving them. The companies that benefit most from this evolution will have confident leaders with long-term visions, ground their use of agentic AI in business priorities and have robust change-management plans. If 2025 was the year of embedding AI across pharmaceutical organizations, 2026 will be the year its role shifts from analysis to action. The organizations that embrace this shift in pharmaceutical operations early will set a new industry standard for speed, agility and impact.
Learn more about how agentic AI is transforming commercial operations in pharma.
About the author
Prashant Parab
SVP, GM – Analytics and Consulting, Commercial Solutions
Prashant heads IQVIA Consulting, Analytics & Information Management business segments globally along with Analytics CoE responsible for innovation, new product development and sales enablement. He has over 25 years of experience in Technology and Analytics leading significant technology P&L and customer delivery teams, and prides in developing innovative solutions that focus on solving clients long-standing challenges leading to measurable topline and bottom-line impact. He has set-up and scale large Analytics and Technology delivery centers to drive margin improvements and customer success.
