The View from the Ground Floor
According to Cognizant's recent study on AI in India, employees are embracing the technology with impressive results. The report, which surveyed 700 enterprise employees, found that an overwhelming 97% have experienced a productivity boost from using
AI tools. On average, this uplift is around 15%. Indian workers are also proactively skilling up, with 74% having completed AI training — a figure significantly higher than the global average of 56%. From data analysis and reporting to research and summarisation, staff are finding clear use cases for AI to perform their tasks faster and more effectively. The consensus from employees is clear: AI helps them do their jobs better. The productivity gains are real, measurable at the individual level, and enthusiastically reported across various industries.
The Disconnect in the C-Suite
While employees are celebrating efficiency wins, the view from the executive suite tells a very different story. The same Cognizant study surveyed 75 business leaders and found a stark disconnect between worker output and business outcomes. A staggering 91% of executives reported that they have seen no impact on company revenue from AI implementation. Furthermore, 84% said the technology has not yet helped lower operational costs. This gap is so significant that it's causing hesitation, with 37% of leaders admitting they have paused or even cancelled AI projects because the return on investment (ROI) was unclear. This creates the central paradox: if everyone is working faster, why aren't businesses seeing the financial benefits? It's a modern version of a classic economic puzzle, now playing out across corporate India.
Why the Productivity Paradox Exists
The gap isn't because the technology is failing; it's because of how it's being deployed. One of the primary reasons is limited access. While employees are trained and ready, business leaders in the study estimate that, on average, only 36% of their workforce has access to the AI tools they need. Another major factor is the difference between task automation and workflow transformation. Giving a marketing manager an AI tool to write copy faster is a task-level improvement. However, if the rest of the marketing and sales process remains unchanged, that saved time doesn't necessarily lead to more sales or lower costs. The efficiency gain remains isolated. Experts note that true ROI comes from redesigning entire processes around AI, not just plugging it into existing structures. Without this strategic overhaul, companies are simply creating pockets of efficiency that never translate to the bottom line.
It's a Strategy Problem, Not a Tech Problem
Ultimately, the Cognizant study highlights that the challenge is one of strategy and measurement. Many organisations are treating AI as a shiny new tool rather than a fundamental change agent. They are measuring success in 'time saved' per employee instead of business-critical metrics like revenue growth, cost reduction, or customer retention. Real value is unlocked when the capacity freed up by AI is redirected toward higher-value activities. For example, if a team resolves customer queries faster, that success only impacts the bottom line if the company can then handle more customers, improve retention rates, or redeploy staff to proactive growth initiatives. Merely completing the same number of tasks in less time often results in unused potential. Leading firms that are seeing returns focus less on cost-cutting and more on using AI to drive business growth and investing in employee development to manage this new way of working.
How Indian Businesses Can Bridge the Gap
To turn employee productivity into enterprise value, Indian companies need to think bigger. The first step is to broaden access to AI tools, moving beyond pilot projects to wider, more democratic deployment. The second is to sustain investment in skills, not just for using the tools but for redesigning jobs and workflows around them. Leaders must shift their focus from monitoring individual task efficiency to measuring end-toend business outcomes. Cognizant's report suggests that organisations must strengthen how they measure results to connect individual gains with enterprise value. This means asking a different set of questions: not just 'How much time did we save?', but 'What did we do with the time we saved?'. The goal is to evolve from simply adopting AI to truly integrating it into the strategic fabric of the organisation.
