- Domestic enterprise tread cautiously, start-ups and Global Capability Centers (GCCs) take the lead in deployments and rolling out of POCs to production respectively.
- Intelligent assistants, marketing automation and document intelligence emerge as the top three use-cases in initial deployments.
- Organizations are dealing with a dynamic value vs. cost equation in their pursuit of GenAI deployments.
16 May 2024, Bangalore – An early analysis of state of GenAI adoption in India in 2024 shows that enterprises have rolled out POCs to production, organisations vary at different levels of adoption maturity. The estimates, available in EY India latest report, "Is Generative AI beginning to deliver on its promise in India? - EY AIdea of India Update", shows that domestic enterprises are carefully considering the enterprise-grade functionality and reliability of GenAI. While digital savvy enterprises such as start-ups and Global Capability Centers (GCCs) are moving faster in rolling out POCs to production.
The report highlights three issues -- hallucination of LLM (Large Language Model) responses, data privacy and sovereignty and the cost implications of deploying GenAI in production -- as the key challenges for organizations in making investment decisions. Mahesh Makhija, Partner and Technology Consulting Leader, EY India, says, “Enterprises need to make the shift from ad hoc experiments to deploying 'fit for purpose' use cases for immediate value creation and long-term programs that provide functional transformation. They will not only have to build their enterprise AI platform but also keep a close eye on cost implications/total cost of ownership and stay agile to adopt a hybrid approach due to lack of India availability of different models.”
The EY analysis of the publicly disclosed adoption of AI/GenAI by India’s top 50 most valued Indian unicorns shows that 66% are already using AI or GenAI technology, indicating that start-ups have been more proactive in terms of adopting AI technology as compared to the legacy players. About 15-20% of POCs by domestic enterprises have been rolled out into production. While, GCCs are rapidly embracing GenAI for innovation, rolling out 30-40% POCs to production. With their deep talent pool in AI/ML, GCCs also hold the key to unlocking a treasure trove of AI-powered opportunities.
Most implemented GenAI use cases among India Inc.
About one-third of the use cases are on utilizing GenAI to execute point tasks using intelligent assistants. Another ~25% relate to marketing automation, enabled by text generation and multimodal capabilities such as text-to-image and text-to-video. Document intelligence is emerging as a key opportunity with around ~20% of the use-cases focusing on document summarization, enterprise knowledge management, and search. Additionally, GenAI assistants are increasingly powering enterprise intranets, and companies are exploring GenAI for customer-facing chatbots, enhanced user experience, coding assistants, and internal process automation.
"Is Generative AI beginning to deliver on its promise in India? - EY AIdea of India Update follows EY’s “AIdea of India Generative AI’s potential to accelerate India’s digital transformation”. Learn latest trends on Generative AI in India | EY India report report released in December 2023, which outlined key imperatives for enterprises to adopt GenAI. Beyond the adoption trends among organizations, the latest report provides an overview of the rapid pace of innovation by platform vendors, rise of Indic LLMs, transaction landscape in AI and the policy developments impacting the Indian AI ecosystem.
AI transaction landscape: A significant portion of investments have been in early stage companies
India’s AI investment landscape is rapidly evolving, marked by strategic emphasis on AI, IoT, and government driven AI initiatives. Unlike the first quarter of 2023, in which investments were primarily in Healthcare, Life Sciences and Financial Services sectors, the first quarter of the year witnessed diversification into various sectors such as Technology, Industrial and Energy Utilities, and Consumer Products Goods (CPGs).
Investors in AI companies are looking at three facets while evaluating potential investees: estimating AI performance and its subsequent impact, understanding the cost implications of AI, and considering AI compliance factors.
Availability of GPU infrastructure to accelerate adoption
The availability of compute is a critical requirement both to train models and to incorporate GenAI into applications. GPUs (the chips which are used for AI) have become expensive as demand has skyrocketed in the GenAI era. However, the government, large business groups and start-ups are building crucial domestic and localized GPU infrastructure, which will boost enterprise adoption of GenAI.
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