News Report Technology
December 18, 2023

Generative AI Can Contribute $1.5 Trillion to India’s GDP by 2029-30, claims EY Report

In Brief

EY said by harnessing generative AI and its applications, India can add up to 1.5 trillion to its GDP over the next seven years.

Generative AI Can Contribute $1.5 Trillion to India’s GDP by 2029-30: EY Report

Fully harnessing generative AI technology and its diverse applications across various sectors, India can add a cumulative $1.2 to 1.5 trillion to its GDP over the next seven years, according to a recent report by EY India.

The report titled ‘The AIdea of India: Generative AI’s potential to accelerate India’s digital transformation‘ envisions that India stands to potentially inject $359-438 billion into its GDP in the fiscal year 2029-30 alone. This anticipated surge reflects a remarkable 5.9 to 7.2% increase over and above the baseline GDP.

It further outlines that approximately 69% of this economic boost will be propelled by the widespread adoption by key sectors, including business services (IT, legal, consulting, outsourcing, rental of machinery and equipment), financial services, education, retail, and healthcare.

This is expected as the technology can enhance employee productivity and operational efficiency, and help deliver more personalized customer engagement strategies.

“To promote the development of generative AI, policy actions will have to ensure access to data. The development of indigenous training data sets (especially for local Indian languages) will be very important. The government may invest in the creation of structured and unstructured datasets, which can be opened to the public,” highlighted the report.

In recent weeks, a notable trend has already emerged within the Indian business landscape — as several companies and startups have unveiled their large language models (LLMs), including CoRover’s BharatGPT, Sarvam.ai’s OpenHathi, Kissan AI’s Dhenu with support from Microsoft and Krutrim from Ola.

“Besides data, the government could ensure access to critical digital infrastructure through the roll-out of 5G, data center development, access to specialized chips and AI-specific compute infrastructure, along with policies that cultivate and attract specialized talent,” the report mentions.

In a recent survey conducted by EY in October 2023, 1,200 CEOs from global large companies participated in the CEO Outlook Pulse survey. It found that in India, 100% of the respondents plan to make significant investments in generative AI, while 84% of Indian CEOs recognize the urgency to move quickly.

Managing Risks and Talent in Generative AI Deployment

Amid the burgeoning promises presented by generative artificial intelligence, the report also pointed towards a nuanced set of challenges accompanying the intricate deployment and validation of its complex models. Unlike the well-established understanding of data and model-related parameters in ‘Classical’ Machine Learning (ML), generative AI poses a distinctive set of risks that demand meticulous management by enterprises.

Vigilance is crucial to avert potential reputational and financial losses, with C-suite executives and leaders urged to proactively assimilate processes for risk mitigation and governance. Presently, organizations are highlighting data privacy as the paramount risk associated.

In the immediate future, enterprises are expected to confront a scarcity of individuals equipped with the requisite AI skills, a predicament anticipated to persist.

Despite India’s commendable position in AI skill penetration and talent concentration, the advent of generative AI exacerbates this shortage. The widening disparity between the skills demanded by companies and the existing workforce underscores the need for strategic talent acquisition, particularly to facilitate the successful initiation and scalable implementation of prioritized use cases.

Moreover, the implementation necessitates a diverse skill set within generative AI Centers of Excellence or Pods, encompassing expertise in AI engineering, data science, foundation models, LLMs, AI orchestration, prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning and model deployment. Effectively navigating these challenges will be imperative for organizations venturing into the realm of generative AI.

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About The Author

Kumar is an experienced Tech Journalist with a specialization in the dynamic intersections of AI/ML, marketing technology, and emerging fields such as crypto, blockchain, and NFTs. With over 3 years of experience in the industry, Kumar has established a proven track record in crafting compelling narratives, conducting insightful interviews, and delivering comprehensive insights. Kumar's expertise lies in producing high-impact content, including articles, reports, and research publications for prominent industry platforms. With a unique skill set that combines technical knowledge and storytelling, Kumar excels at communicating complex technological concepts to diverse audiences in a clear and engaging manner.

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Kumar Gandharv
Kumar Gandharv

Kumar is an experienced Tech Journalist with a specialization in the dynamic intersections of AI/ML, marketing technology, and emerging fields such as crypto, blockchain, and NFTs. With over 3 years of experience in the industry, Kumar has established a proven track record in crafting compelling narratives, conducting insightful interviews, and delivering comprehensive insights. Kumar's expertise lies in producing high-impact content, including articles, reports, and research publications for prominent industry platforms. With a unique skill set that combines technical knowledge and storytelling, Kumar excels at communicating complex technological concepts to diverse audiences in a clear and engaging manner.

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