While initiatives like the National Strategy on Artificial Intelligence (NSAI) have laid promising groundwork, India’s R&D spending as a percentage of GDP remains significantly lower than leading AI nations like the US and China, limiting the country’s potential to compete globally in AI innovation.
The current landscape of AI development in India presents both opportunities and challenges. Indian tech companies are creating innovative solutions across sectors, from healthcare to financial services, but they often find themselves constrained by limited resources for deep research and experimental innovation. This is where strategic government intervention through budgetary allocations could be transformative.
Research and development in AI requires substantial long-term investment with uncertain immediate returns. While venture capital and private equity have played crucial roles in funding commercial applications, fundamental research often struggles to attract similar attention.
The tech industry’s primary ask is for the government to bridge this gap through research grants, tax incentives, and public-private partnership frameworks that make long-term AI research commercially viable.
Infrastructure Support
Infrastructure support remains a critical concern. The industry needs access to high-performance computing resources, data centers, and specialised AI hardware. Many promising startups and research initiatives currently struggle with these fundamental requirements.
Government support through shared infrastructure models, similar to successful initiatives in countries like South Korea and Israel, could democratise access to these essential resources.
Talent development presents another crucial area requiring government intervention. While India produces a significant number of technology graduates annually, specialised AI skills remain scarce.
The industry proposes a collaborative approach where government funding supports advanced AI curricula in educational institutions, industry-academia research programs, and specialised training initiatives. This could include subsidised AI certification programs, faculty development initiatives, and grants for industrial research fellowships.
Standardised Data Repositories
Data accessibility and standardisation form the backbone of AI development. The tech industry seeks government support in creating standardised data repositories across sectors, with clear guidelines for data sharing and usage. This could significantly accelerate AI innovation while ensuring privacy and security compliance.
The success of UPI and IndiaStack demonstrates how government-backed digital infrastructure can catalyse innovation. From experience in the tech space, it’s evident how AI can transform traditional business processes. However, many sectors remain underserved due to the high initial costs of AI implementation.
The industry suggests creating sector-specific AI adoption funds that could subsidise initial implementation costs for MSMEs, enabling wider technology adoption and creating a broader market for AI solutions.
International Collaboration
Cross-border collaboration in AI research presents another opportunity. The tech industry recommends establishing government-backed AI research corridors with leading global tech hubs. This could include joint research programs, talent exchange initiatives, and collaborative projects that bring global expertise to Indian challenges while showcasing Indian innovation globally.
Regulatory support is equally crucial. The industry seeks a balanced regulatory framework that encourages innovation while ensuring responsible AI development. This includes clear guidelines for AI testing and deployment, especially in sensitive sectors like healthcare and financial services. Government support through regulatory sandboxes could allow companies to test innovative solutions in controlled environments.
The industry also emphasises the need for support in commercialising research outcomes. Many promising research projects fail to transition from labs to market due to funding gaps and commercialisation challenges. A government-backed AI commercialisation fund could help bridge this crucial gap, supporting prototyping, pilot implementations, and market validation of innovative AI solutions.
Innovation Clusters
Regional innovation clusters deserve special attention. While metropolitan cities have thriving tech ecosystems, tier-2 and tier-3 cities often lag behind. The industry proposes establishing AI innovation hubs in smaller cities, supported by government infrastructure and incentives. This could help create distributed centers of AI excellence across India.
Looking ahead, the tech industry’s demands reflect a broader vision for India’s AI leadership. With appropriate government support through the budget, India can create an ecosystem that not only serves domestic needs but also positions itself as a global AI innovation hub. The time is ripe for bold initiatives that can shape the future of AI development in India, and the upcoming budget presents an ideal opportunity to demonstrate this commitment.
—The author, Apurv Agrawal, is CEO and Co-Founder of Squadstack, a leading a SaaS-enabled talent marketplace for telesales. The views expressed are personal.
