India ranks first among the top 15 countries for AI adoption by companies across categories, except IT and cybersecurity, according to a Deloitte India-FICCI report released this month. The report, titled Consumer trends IGNITEing growth and governance, indicates that AI is evolving from a productivity tool into an 'intelligence layer' across FMCG, retail and ecommerce businesses, influencing everything from consumer engagement and product development to demand forecasting and supply-chain planning. However, as more firms embrace AI, the question that emerges is: what is the return on investment, and how are companies quantifying it?
Consumer companies are increasingly able to point to operational returns from AI implementation, but evidence that these gains are translating directly into higher revenue, margins or earnings before interest and taxes (EBIT) remains much thinner. A McKinsey survey conducted between December 2025 and January 2026 among 27 C-suite executives across European retail, consumer packaged goods, apparel and related consumer services found that 23 had increased AI activity over the previous year, while none had scaled it back. Yet only six reported an EBIT impact of at least 1% from AI initiatives, while more than half said it was still too early to determine the financial impact. The Deloitte India-FICCI report suggests measurable benefits are emerging across parts of the consumer value chain, with AI potentially delivering savings of around 8-10% across planning, buying, manufacturing and product development.
Several major consumer companies have demonstrated measurable AI-driven operational improvements. Hindustan Unilever (HUL) deployed machine learning-driven process controls and AI-powered autonomous troubleshooting at its Pondicherry factory, enabling 25% volume growth and reducing defects by 23% while supporting a threefold increase in product variants within existing production capacity. Procter & Gamble's India business used data, analytics and automation to optimise its supply chain, reducing the number of supply-chain touchpoints by 60% compared with a few years earlier and shifting distributors to an AI and machine learning-based ordering system that helped reduce out-of-stock rates by 15%. Tata Consumer Products reported that AI embedded in its sales-force automation platform influenced 41% of orders and contributed a 'meaningful delta in monthly sales', while using AI-driven route optimisation to reduce average field travel distance by 30%.
IT firms are actively integrating tools like GitHub Copilot, ChatGPT Enterprise, and proprietary language models into their core workflows. This integration means automating routine coding, fast-tracking quality assurance, and using predictive models to resolve IT outages before human engineers even notice them. The most immediate benefit is efficiency through generative AI, which can write boilerplate code, debug legacy systems, and generate test scripts in a fraction of the time it takes a junior developer. This reduction in hours spent on low-level tasks significantly boosts IT firms' gross margins. According to Trusted Data, AI agents can coordinate multi-step knowledge and workflow tasks, but they should operate within explicit permissions and controls, with the path from read to recommend to act being deliberate. Praveen Ojha, Chief Technologist at EPAM Systems India Pvt. Ltd., notes that AI now blends reasoning, prediction and content generation with enterprise data, enabling companies to redesign business models and boost workforce productivity.
The economics of scaling AI implementation present significant challenges for consumer companies. A June 2026 survey of 39 senior consumer packaged goods (CPG) and retail executives by Boston Consulting Group (BCG) and The Consumer Goods Forum found that around 75% of CPG respondents remained in pilot or exploration mode, while only 18% were scaling AI with significant impact. More than half of companies across the two sectors did not formally measure the return on their AI investments. Sandeep Verma, FICCI FMCG Committee Member and Cluster Head of South Asia, Bayer, summarised the challenge: "Realising its (AI's) full potential will require more than just the deployment of tools. Organisations will need robust data foundations, integrated ways of working and leadership that embeds AI into everyday decision-making." Looking ahead, the IT sector's relationship with AI will mature from experimentation to enterprise-wide execution, with the benchmark increasingly becoming financial return rather than adoption alone.
