Wipro’s artificial intelligence initiatives have increased productivity equivalent to the output of around 20,000 employees, with the company redeploying the capacity created by these gains within the organisation, according to Chief Technology Officer Sandhya Arun.
The development highlights how AI adoption is beginning to reshape workforce models across India’s information technology services industry. Rather than directly replacing employees with AI systems, Wipro is using the additional capacity created through AI-driven productivity improvements to move employees to other projects and roles.
Wipro, which had about 243,000 employees as of June, is moving towards what Arun described as a “human-AI operating model.” Under this approach, employees are expected to work alongside AI systems and agents, with technology being used to increase individual productivity and enable workers to take on different responsibilities.
“It could be the same engineer managing a bunch of agents, deployed on other projects or being trained for some other role. It doesn’t necessarily mean person-to-person replacement by an agent,” Arun said.
As part of its AI strategy, Wipro has trained more than 100,000 employees in advanced AI-related skills and certifications. The company is also expanding its forward-deployed engineering workforce, although Arun did not provide a specific target for the number of engineers it plans to deploy in this model.
Forward-deployed engineers are increasingly becoming part of the strategy of major Indian IT services companies as businesses look to accelerate AI adoption among clients. Tata Consultancy Services has said it plans to build a team of up to 8,900 forward-deployed engineers, while Infosys plans to have about 6,000 over the next few years. Wipro’s forward-deployed workforce is expected to be broadly in line with its peers, according to Arun.
However, Arun said the industry should look beyond the number of engineers working with AI systems and focus on whether employees have the skills required to work effectively with increasingly capable AI tools and agents. This reflects a broader shift in how companies are assessing the value of AI within their operations.
“The shift has to be from productivity to outcomes,” Arun said. She argued that AI should ultimately be evaluated based on whether it improves customer experience, creates new revenue opportunities and helps businesses achieve their broader goals.
The development comes as India’s $315 billion software services industry continues to adjust to the growing use of AI in software development, hiring and client contracts. Major IT companies are increasingly investing in AI training and infrastructure while changing how employees are deployed across projects.
Wipro’s progress in AI productivity, however, has not yet translated into the same level of AI commercialisation seen among some of its larger peers. Reuters reported that Wipro is the only company among India’s top four IT firms that does not disclose AI-specific revenue.
According to Manoj Chandra Jha, principal analyst at Nord-IQ Research, Wipro remains in an earlier, cost-absorbing phase of AI monetisation compared with some of its peers. He said the key test will be whether the company’s AI-related deals eventually translate into revenue growth and margin recovery.
Jha added that Wipro’s investment intensity in AI training and ecosystem partnerships is comparable with companies including TCS, Infosys and HCLTech, although the company currently trails its peers in terms of commercialisation maturity.
For Wipro, the productivity gains equivalent to 20,000 employees therefore represent a shift in how existing workforce capacity can be deployed rather than a straightforward reduction in headcount. The company’s focus on AI training, human-AI collaboration and redeployment indicates an approach in which employees and AI systems operate together to support new projects and responsibilities.
As AI adoption continues to reshape India’s technology services sector, Wipro’s experience also reflects the growing emphasis on using AI not simply to reduce the time required for existing tasks, but to create additional capacity that can be directed towards customer outcomes, new business opportunities and changing technology requirements.
