Artificial intelligence is rapidly entering the Indian workplace, with most employees reporting productivity gains. But a major new study from Cognizant reveals a paradox: while staff feel more efficient, most companies are not yet seeing the financial
benefits. The reason points to a critical gap between simply using AI and extracting real value from it.
The AI Productivity Puzzle
Indian companies are investing in AI, but many are struggling to see a clear return. A recent study by Cognizant surveyed 700 employees and 75 senior executives in India, uncovering a fascinating disconnect. While an overwhelming 97% of employees reported a productivity boost from using AI, with an average uplift of 15%, the financial impact on their companies has been minimal. The research found that 84% of business leaders have not seen AI lower costs, and a staggering 91% reported no positive impact on revenue. This has led to uncertainty, with 37% of leaders admitting they have paused or even stopped AI initiatives due to an unclear return on investment. This creates a puzzle: if employees feel more productive, why isn't it translating to the bottom line?
The Crucial 'Activation Gap'
The core of the issue, as highlighted by Cognizant's research, is the difference between AI access and effective AI activation. While Indian employees are proactive in preparing for an AI-driven future—with 74% having completed some form of AI training compared to a global average of 56%—this enthusiasm isn't being fully leveraged. Leaders surveyed reported that, on average, only 36% of their employees actually have access to the AI tools they need to perform their jobs effectively. This creates an 'activation gap', where willing and trained employees are held back by a lack of access and strategic implementation. Simply put, having AI in the building is not the same as having it integrated into the workflow in a way that creates tangible value.
Training: From Theory to Practice
The study underscores that the nature of training is just as important as its availability. General, one-off training sessions are proving insufficient. For training to translate into value, it must be role-based, continuous, and focused on practical application. Other studies support this, finding that many employees feel their training lacks real-world practice tasks. Successful AI adoption depends more on people than on technology. The goal is to move beyond basic awareness and equip teams with the skills to apply AI to their specific functions, whether it's for data analysis, summarization, or forecasting—the top use cases identified by employees. This requires a structured approach where training is tailored to different roles, from general staff to specialized 'AI champions' and managers who oversee governance.
Uneven Gains Across Industries
The productivity gains from AI are not being felt equally across all sectors in India. The Cognizant study revealed that healthcare is leading the charge, with 38% of employees reporting productivity gains of more than 20%. Following behind are the communications, technology, and banking sectors. In contrast, the retail and consumer goods sector saw the lowest boost. This disparity suggests that the value derived from AI is highly dependent on industry-specific applications and the readiness of companies within that sector to adapt. The challenge for businesses is to move from scattered pockets of high performance to a broadly based uplift, which requires sharing best practices and developing customized AI strategies that fit their unique operational needs.
The Path to Realizing AI's Potential
For Indian businesses to close the gap between employee productivity and financial returns, a strategic shift is required. The focus must move from mere adoption to value creation. According to experts, this involves several key steps. First, companies need to provide wider access to customized, role-specific AI tools. Second, they must invest in continuous, handson training that empowers employees to integrate AI into their daily tasks safely and effectively. Finally, leadership must define clear rules for AI use, establish metrics to measure impact beyond simple attendance at a training session, and align AI initiatives with long term strategic goals. As Cognizant India's Chairman, Rajesh Varrier, noted, realizing AI's potential requires a concerted effort to combine tool adoption, skilling, and a responsible AI environment at scale.
