Customer service and marketing lead AI adoption as operations and supply chain catch up

New Delhi: Marketing, customer experience and customer service are emerging as the sharp edge of India Inc’s generative AI push, with brands using the technology to drive growth, personalisation and measurable improvements in conversion, according to a new EY–Confederation of Indian Industry (CII) report on AI adoption.

The report, titled “Is India ready for Agentic AI? The AIdea of India: Outlook 2026”, is based on an EY India C-suite GenAI survey of over 200 enterprise leaders. It finds that 76% of Indian business leaders believe GenAI will have a significant business impact, and nearly half of the organisations surveyed already have multiple AI use cases live in production.

As per the report, more than 95% of organisations allocate less than 20% of their IT budgets to AI. Only 4% have crossed the 20% threshold, highlighting that while belief is high, funding for scaled AI transformation is still conservative. There is a clear imbalance between conviction and commitment, which is becoming a defining factor in how quickly enterprises extract measurable returns from AI.

Customer-facing functions sit at the heart of that deployment. The report noted that customer service and marketing continue to be among the top three functions prioritised for AI interventions, even as mid- and back-office areas such as operations and supply chain rapidly catch up.

Fresh survey data from the study shows that operations, customer experience and cost reduction are the top three business functions that enterprises plan to prioritise for GenAI and Agentic AI use cases over the next 12 months. 

Marketing, customer service, R&D, supply chain and risk analytics are also in the next tier, with more than a quarter of respondents bringing AI into these functions.

The emphasis is shifting from pilots to use cases that can directly influence revenue and customer metrics. The report frames GenAI’s role in marketing-led growth as enabling highly personalised customer interactions that can lift engagement and conversion, while Agentic AI unlocks new business models such as AI-assisted commerce and AI-native customer experiences.

Measurable lifts in conversions and NPS

Several case studies in the report highlighted how Indian companies are already hard-wiring GenAI into sales and marketing funnels. Axis Bank has rolled out GenAI-powered assistants across its employee and branch network. Beyond answering queries, these assistants are directly driving business outcomes: the bank has seen a 30% uplift in product conversions across term deposits, mutual funds and credit cards, along with a 10-point improvement in Net Promoter Score.

State Bank of India (SBI) has adopted a dual approach, using Agentic AI for customer service front-ends and GenAI assistants for employees. This has reduced average handle time and improved first-contact resolution, critical metrics for both service quality and sales opportunities in a branch-heavy network of over 22,500 outlets.

In fast-moving consumer goods, Hindustan Unilever (HUL) has plugged GenAI into retail marketing operations. The company uses AI to generate retailer advertisements and analyse shelf availability, creating more than one lakh ads at zero marginal cost and processing around 2.5 crore shelf images every month. These deployments are helping improve sales execution and on-shelf visibility, turning AI into what the report describes as a frontline growth driver.

Telecom players are also using AI to reshape customer experience, which feeds back into marketing and retention. Reliance Jio is leveraging Agentic AI for real-time network optimisation and customer experience management, leading to better network uptime and lower call-centre load. Bharti Airtel has deployed network-level AI to block spam calls and SMS, intercepting more than 26 billion calls and reducing fraud as well as churn risk.

From campaign planning to AI-native journeys

The report argued that the next phase of adoption will be driven by AI agents that can take on end-to-end marketing workflows rather than single tasks. It describes Agentic AI as software with “initiative”, capable of planning multi-step activities towards a goal.

One example the report offers is a marketing use case: an AI agent can research a target audience, suggest slogans, shortlist promotion channels and draft content for each, while maintaining memory of its actions and adjusting its plan as it goes.

This shift from isolated tools to autonomous agents, the authors say, moves AI closer to a goal- and action-oriented paradigm. For marketers, that could mean agents that not only generate campaign ideas but also run experiments, optimise media plans, iterate creatives and feed performance data back into future campaigns with minimal human intervention.

AI as a growth engine, not just a cost lever

While cost savings and productivity are still important, the report makes clear that Indian enterprises increasingly see AI as a top-line driver. In its “revenue generation” section, the study notes that GenAI and Agentic AI enable personalised experiences and new service models that go beyond incremental efficiencies and create entirely new revenue streams.

Rewiring marketing operations and jobs

The survey also captured how AI is changing the structure of marketing and customer operations. Sixty-four per cent of respondents say AI is causing selective displacement in outsourced and standardised functions such as administrative operations, customer success and tele-calling, rather than triggering large-scale internal layoffs.

This, the report argued, indicated a shift in how work is organised along the marketing value chain: routine and repetitive tasks are being automated, while internal teams are expected to move up the value curve towards strategy, creative thinking and complex relationship management.

At the same time, India’s bet on small language models is seen as especially relevant for customer-facing applications. These models are designed for Indian languages and edge deployments, powering vernacular chatbots and AI interfaces in compliance-heavy sectors such as banking and healthcare. That, in turn, can expand the reach of marketing and service campaigns into the next wave of regional-language users coming online.

Marketers still grapple with data, integration and ROI

Despite the bullishness, the report underlines that marketers and CIOs face significant execution hurdles. Integration and data readiness emerge as the single biggest roadblocks in scaling GenAI, with 78% of respondents citing issues such as connecting AI systems to core platforms and poor data quality as top challenges. Measuring ROI and dealing with data governance and security also rank high.

This complexity is shaping how enterprises deploy AI. About 71% prefer hybrid cloud for GenAI and Agentic AI, balancing agility with control, while 91% of respondents say speed of deployment is the primary factor in their buy-versus-build decisions, a sign that organisations are racing to get marketing and customer-facing solutions into production quickly.

Overall, the EY–CII study concluded that corporate India has moved beyond AI experimentation to a phase where marketing, customer service and experience are central to proving business value. The coming years, it says, will be defined less by how many AI models are deployed and more by how effectively they are integrated into revenue, brand and customer metrics across the enterprise.