Introducing the Multi-Agent AI Revolution
Agentic AI is transforming enterprise operations by introducing AI systems that are autonomous, adaptive, and capable of real-time collaboration. Instead of a monolithic AI model tackling all business problems, Agentic AI leverages specialized AI agents—each with distinct roles—that can work independently yet communicate with each other. These agents can dynamically engage with users and each other, enabling more responsive and tailored outcomes across an organization.
Cognizant, in partnership with Microsoft, is at the forefront of this innovation with its Neuro® AI Multi-Agent Accelerator and the Cognizant® Multi-Agent Services Suite. These no-code frameworks empower businesses to rapidly prototype and deploy multi-agent systems without the need for advanced technical skills. For industries like pharmaceutical marketing, where regulatory compliance, speed to market, and cross-functional collaboration are vital, these tools provide a scalable and secure way to simulate and support complex decision-making.
At the core of this approach is the idea that modern enterprises—like ecosystems—benefit from interconnected, intelligent systems that mirror the interplay between various business functions. Rather than functioning in silos, departments like market access, patient engagement, and sales strategy can now align more naturally, thanks to AI agents that synthesize data, analyze objectives, and recommend actions that consider the broader business landscape.
Observing Innovation in Action: The Cognizant-Microsoft Agentic AI Hackathon
As part of Reuters Pharma 2025, Cognizant and Microsoft hosted an exclusive hackathon on Agentic AI. The session delved into how Agentic AI can revolutionize the entire Life Sciences value chain, and gave attendees an opportunity to collaborate, innovate, and get hands-on with the latest AI tools and build their own AI agent without coding skills and using Neuro AI, a multi-agent platform designed to simulate business decision-making across departments.
Rohit Dayama, leading the Cognizant team, opened the session by setting expectations: “The idea was that you've heard so much about Agentic AI over the last two days. Today, the intent is to give you a flavour of how it would work for you.” He emphasized that while the workshop was a condensed 30-minute version of a day long event, it would provide a practical overview of AI modelling, enabling participants to experience first-hand how to interact with multi-agent systems.
Explaining the structured process, Dayama described the Neuro AI approach as a logical format beginning with problem framing and ending with scenario-based simulations. “You start with a broader context of a problem statement,” he said, “break it down into priority areas, define inputs and outcomes, and create a model based on those outcomes.” Participants worked at tables designated to specific pharma functions such as market access, marketing, patient engagement, and sales. Their task: build a launch toolkit for a novel CRISPR-based treatment for sickle cell disease, simulating the decisions needed six months before market launch.
Lotan Steinberg, a cloud solution architect at Microsoft, supported Dayama’s introduction by explaining the broader vision. “Our mission at Microsoft is to empower each organisation and each person in the world to achieve more. Today, you're going to use some of our LLM capabilities based on ChatGPT-4,” he said. He emphasized the importance of trust, security, and compliance—particularly crucial in healthcare—and explained how Microsoft’s building blocks provide the secure, scalable foundation for agent-based tools.
Using dummy data, each team engaged with the platform through a series of guided steps: defining the challenge via the “Opportunity Finder,” refining it with the “Scope Agent,” inputting parameters, generating scenarios, and tweaking those scenarios to observe outcomes. “You’ll actually see the outcome of the LLM models that you've created,” Dayama noted, encouraging participants to challenge the models’ suggestions.
Following the session, participants were invited to share their experiences. The feedback reflected both enthusiasm and critical reflection. “The tool clearly does a lot,” one participant noted. “Once you got into outcomes, you could change them and see how they looked… we tweaked things a few times. That was potentially very powerful.”
Another highlighted the intuitive impact of multi-agent collaboration: “It was like having an extra member on the team—without the FTE cost.” Participants valued the system’s speed and depth, even under a compressed timeline, though some raised concerns about the nuances of input quality. “We are not market access experts, so we were unsure how nuanced our inputs were,” said one attendee, prompting Dayama to affirm that human-AI collaboration remains essential: “Hopefully, you just wouldn’t give it to anybody to create a marketing plan.”
One participant captured the broader sentiment: “This is the future, right? The real value will come when we marry it with the business question and the business ask.” Another reflected, “It’s like having an additional brain on the team… somehow it can aid us in making decisions and ideally making our life easier.”
In summing up, Dayama underscored the transformative potential of agentic AI: “You now know that there’s a power in that AI model to give you a solution in real time… this could be a six-month project otherwise.” He concluded by pointing to deeper opportunities in Cognizant’s Innovation Labs in London and Amsterdam, where longer workshops allow organizations to fully explore agentic solutions in context.
For pharma marketers and strategists navigating a rapidly evolving digital landscape, multi-agent AI represents a significant leap forward. As the feedback from this workshop demonstrated, the technology is not only maturing—it is already capable of reshaping how product launches, patient engagement, and market access strategies are conceived and executed.
If you want to experience a hackathon or learn more about how agentic AI is transforming the complete life cycle of the life sciences industry, visit https://www.cognizant.com/emea/en/cmp/agentic-ai-in-life-sciences.