By Soumoshree Mukherjee
Editor’s note: This article is based on insights from a podcast series. The views expressed in the podcast reflect the speakers’ perspectives and do not necessarily represent those of this publication. Readers are encouraged to explore the full podcast for additional context.
In a wide-ranging conversation on the future of artificial intelligence, Dr. Bijoy Sagar, Chief Information Technology and Digital Transformation Officer at Bayer, laid out in the CAIO Connect podcast, hosted by Sanjay Puri, how the company is adopting an “AI-first” approach to reimagine the pharmaceutical and agricultural sectors. His message was clear: innovation must be pursued responsibly, with an eye on both productivity and ethics.
“I am incredibly motivated by our mission, health for all, hunger for none. If you are any human being on this planet, those are two things you can’t do without. That propels the basic purpose of your life forward,” Sagar believes that pharma and agriculture are driven by the need for innovation and the abundance of data available.
Sagar noted, “to have people live healthy lives, to have them achieve sustenance in the best healthful way… these are two industries which are highly propelled by innovation. You’re meeting unmet needs. So in any areas where the biggest driver is innovation, technology is a natural bedfellow to that mission.” By integrating AI into workflows, Bayer aims to eliminate friction points between human interactions and technology, creating what he called “frictionless integration” across sectors.
Sagar emphasized the transformative role of generative AI. “I think Gen.AI is really about personal productivity. And agentic AI is about organizational productivity,” he said.
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While generative AI fosters bottom-up creativity and innovation, agentic AI takes a more structured, top-down approach to align with business goals. This hybrid balance, he argued, is essential for long-term adoption and success.
“We have helped people think through what they want to use. We have built guardrails around it. And then we do encourage experimentation. within that framework,” Sagar stressed saying frameworks and guardrails are crucial.
He believes that experimentation within guided parameters is essential for driving innovation effectively, “you can still let people innovate and create agents within some framework, but I also believe it’s really important to set organizational principles and large organizational goals to drive that conversation rather than just randomly build a lot of agents because you would lose the potential of organizational productivity that way.”
He distinguished between outputs and outcomes, urging companies to design AI agents responsibly to support efficiency without losing sight of ethical objectives.
Sagar also reflected on the shifting landscape of software. The model for accessing software is evolving, moving beyond traditional interfaces to more flexible, autonomous methods. In tightly regulated industries like pharma, however, balancing innovation with compliance remains a non-negotiable challenge.
He shared, “you have to have a starting point, which is universal, not predefined, but accessible so it serves you the right thing as you need but gives you some amount of autonomy then to select the next prompts and next steps but still stays within the constraints of how the model should behave.”
Looking ahead, Sagar pointed to emerging technologies such as quantum computing and synthetic data, “this could be a quantum topic and standard AI topic… you can do a tremendous amount of modeling already without making that about human data.”
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He mentioned, “we can’t do this computationally yet, but with quantum we’ll be able to do this. When quantum computing gets to a certain point, we should be able to do protein folding… you can do things you absolutely cannot do today with conventional tech.” But he cautioned against over-reliance on synthetic data, recommending a “hybrid approach utilizing both synthetic and real data.”
Equity and inclusivity also formed a central theme. “AI divide can really divide people even further. And I really genuinely believe that we have to build models and we have to build these solutions in a way that benefits the largest amount of humanity possible. And that’s the only way we’re going to solve many of our problems,” Sagar warned.
He highlighted the digital divide as a critical barrier, particularly for vulnerable populations, “It’s not health for some people and hunger for a few people. It’s actually health for all, hunger for none. And that sort of inclusivity, I believe in.”
Sagar also underscored the human side of transformation. “We’re really transforming the way companies work, behave, sell, innovate. As employees work with each other, work with agents. This is not a transformation of technology. It is really a transformation of the company and the people. Technology is a driver to that change,” he said.
For him, the success of AI adoption lies not only in technology but also in fostering humility, adaptability, and a meaningful mission to attract talent, “I am very confident of the fact that this is a people transformation, this is a company transformation, and like any other transformation of that magnitude, this has to be driven across the board that way.”
Through this conversation, Sagar painted a picture of an AI-driven future, one where innovation is inseparable from responsibility, and where technology serves the dual goals of efficiency and equity.