Multi-agent AI systems go from theory to the reality of the company, and in this episode Babak Hodjat, CTO of AI explains to Cognizant, why he believes they represent the future of business. Speaking from his AI R&D laboratory in San Francisco, Babak outlines how his team helps these systems both within cognizant and customers to build their own, break down organizations, to coordinate processes and improve decision-making.
We discuss how the arrival of optimized, open-source models such as Deepseek AI-Democratization accelerates, making it viable to run capable agents on a much smaller infrastructure. Babak explains why this is not a “sputnik moment” for AI, but a powerful industrial correction that opens the door for more detailed, cost-effective agents. This shift makes richer, scalable multi-agent networks possible, with agents who can not only perform autonomous tasks, but also communicate and work together.
Babak also introduces the Open-Sourced Neuro-AI network platform from Cognizant, designed to be model and cloud-agent and at the same time support large-scale coordination between agents. By separating the opaque AI model from the fully verifiable code layer, the platform builds up in protection for trust, data treatment and access control, whereby one of the most urgent challenges in AI acceptance.
Looks ahead, Babak predicts rapid growth in ecosystems with a multi-agent, including communication between companies and even self-inventing agent networks. He also emphasizes the importance of Open-Source cooperation in the next chapter of AI, warning that ownership approaches have concluded the risk-retarding innovation and the eroding of trust.
This is a deep but accessible conversation for anyone who is curious about how Enterprise Ai evolves from some, monolithic models to flexible, distributed systems that can adapt and scales. You can learn more about the AI work of Cognizant on Cognizant.com and follow Babak’s insights on LinkedIn.
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