IT companies seek new opportunities from scattered data: Cognizant generates ₹1,900 crore in business from employee emails and chats; AI lends a hand
IT company Cognizant has developed a unique AI system that identifies new revenue streams by analyzing employee emails, meetings, and chats. Through its ‘Context Engineering’ technology, the company has generated a new sales pipeline worth approximately ₹1,900 crore so far. CEO Ravi Kumar states that the company aims to raise this figure to ₹9,500 crore by the end of 2026.
This AI system captures signals from interactions between employees and clients across sales, delivery, and support departments. It identifies business opportunities that would go unnoticed through traditional methods. Naturally, employees must now be aware that the company is monitoring their emails and chats. With AI’s help, this data can be leveraged to acquire new clients and boost profits. The technology aggregates scattered information from the workforce and converts it into new business opportunities.
To ensure the project’s success, Cognizant has partnered with ‘WorkFabric,’ a startup founded by Rohan Murty—son of Infosys founder Narayana Murthy. At Cognizant, employees will now be assigned new tasks based on their actual experience rather than just their resumes. In the IT sector, the focus has shifted beyond merely increasing productivity to actively seeking revenue-generating opportunities. Companies like Meta are also training AI agents by tracking employee mouse clicks and keystrokes. Cognizant has also begun using this new technology to deploy employees onto new projects.
Securing new business before tenders are even issued; AI also monitors client budgets
– The new AI system anticipates project risks on a global scale. It suggests involving experts and initiating necessary conversations before losses occur or problems escalate. This enables Cognizant to secure new business directly from clients, even before formal market tenders are issued.
– The AI system creates a virtual model for each client account, integrating signals from departments such as sales and finance. In one instance, the system detected that a client was under pressure to cut engineering costs by 15%. The AI then advised the sales team to submit a proposal focused on improving quality assurance.
