Multi-agent AI systems are moving from theory to enterprise reality, and in this episode, Babak Hodjat, CTO of AI at Cognizant, explains why he believes they represent the future of business. Speaking from his AI R&D lab in San Francisco, Babak outlines how his team is both deploying these systems inside Cognizant and helping clients build their own, breaking down organisational silos, coordinating processes, and improving decision-making.

We discuss how the arrival of optimized, open-source models like DeepSeek is accelerating AI democratization, making it viable to run capable agents on far smaller infrastructure. Babak explains why this is not a "Sputnik moment" for AI, but a powerful industry correction that opens the door for more granular, cost-effective agents. This shift is enabling richer, more scalable multi-agent networks, with agents that can not only perform autonomous tasks but also communicate and collaborate with each other.

Babak also introduces Cognizant's open-sourced Neuro-AI Network platform, designed to be model and cloud agnostic while supporting large-scale coordination between agents. By separating the opaque AI model from the fully controllable code layer, the platform builds in safeguards for trust, data handling, and access control, addressing one of the most pressing challenges in AI adoption.

Looking ahead, Babak predicts rapid growth in multi-agent ecosystems, including inter-company agent communication and even self-evolving agent networks. He also stresses the importance of open-source collaboration in AI's next chapter, warning that closed, proprietary approaches risk slowing innovation and eroding trust.

This is a deep yet accessible conversation for anyone curious about how enterprise AI is evolving from single, monolithic models to flexible, distributed systems that can adapt and scale. You can learn more about Cognizant's AI work at cognizant.com and follow Babak's insights on LinkedIn.