BENGALURU: Cognizant, which expects to invest about USD 1 billion over the next three years in strengthening gen AI capabilities, says it is infusing gen AI into all its core offerings.
The company has introduced a gen AI-enabled conversational virtual assistant (VA) that’s designed to help enterprises reimagine experiences beyond chatbots. It said that by using this virtual assistant, the company's clients can boost their productivity by 25% and improve their digital score through predictive resolution and contextual knowledge search.
In an internal note to employees, Ravi Kumar S, CEO of Cognizant, said gen AI is a natural evolution of the company's work across cognitive AI, enterprise applications and data and analytics services.
The company will train 25,000 employees in gen AI and will be launching AI studios in Bengaluru, London, and San Francisco. "In addition, we’ve launched our new generative-AI storytelling hub on Cognizant.com, which positions us as the best partner to guide enterprises on their generative AI journey," Kumar said.
"Driven by our culture of innovation, embodied in our Bluebolt innovation movement that has already produced more than 3,000 gen AI ideas (and 35,000+ ideas overall), we’ve further expanded our capabilities with the Cognizant Neuro AI platform. It's designed to speed the adoption of gen AI and harness its value in a flexible, secure, scalable and responsible way. With Neuro AI, we’re helping clients advance from identifying company-specific use cases to operationalizing AI," he added in the note.
Last week, Cognizant reported $4.9 billion in revenue for the quarter that ended June 30, 2023. The CEO said, "Today, we have more than 100 active early client engagements in various stages with a focus on cognitive and generative AI, as well as hundreds more projects using AI services within the context of delivery."
Recently, the company announced that as part of its expanded partnership with Google Cloud, they have built on its generative AI technology with its own AI domain expertise to create a healthcare large language model (LLM) solution.