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Last year, India rolled out an ambitious National Artificial Intelligence Mission backed by a hefty ₹10,371.92 crore outlay for the next five years. As AI continues disrupting industries and redefining competitive advantages, it signals India’s aspiration to become an AI powerhouse. But more than just technical prowess, the initiative aims to cultivate indigenous AI capabilities and nurture a thriving ecosystem of homegrown innovation.

Indigenous AI fosters an ecosystem aligned with national priorities, enabling impactful breakthroughs across sectors such as agriculture and healthcare. Furthermore, it inspires a wave of entrepreneurial disruptions, propelling India to the forefront of the global AI race.

An example of an indigenously developed digital solution that sparked a global interest in its open-source nature is UPI (unified payments interface). The underlying technology of UPI makes it an attractive solution for digital payments, demonstrating India’s potential to develop disruptive solutions tailored to local needs without relying on global tech giants.

This ‘Make in India, Make for India’ paradigm underpins the AI mission’s focus on developing customised solutions like large language models (LLMs) tailored to India’s linguistic diversity.

Democratising computing power

The lack of affordable computing infrastructure, quality datasets, and early-stage financing has hindered many domestic AI startups’ ambitions. As a part of the AI Mission, the government’s decision to invest in INDIAai, a public-private partnership featuring a staggering 10,000 or more graphics processing units (GPUs), is a significant change for researchers and innovators alike.

For too long, GPUs have been a scarce and expensive resource, posing significant barriers to entry for cash-strapped startups and small businesses. With this initiative, India is poised to level the playing field, making state-of-the-art computing power accessible to even the most resource-constrained innovators.

Manoeuvring data mining

Accessing and harnessing data remains a formidable challenge. While the government has amassed a vast trove of data from various public bodies, making it available at little to no cost, startups often find themselves lost in the maze of stakeholders and sources. This knowledge gap presents a significant barrier, hindering their ability to tap into the very lifeblood of AI development.

Here startup accelerators are bridging the divide by serving as a custodian and mediator, guiding startups to the right stakeholders and curating structured datasets tailored to their needs. By tracking data utilisation and the problems being tackled, they provide a more holistic view, thereby creating an ecosystem for startups to thrive and flourish.

Yet the challenges extend beyond mere accessibility. Data quality is paramount, and the costs associated with cleaning, anonymising and structuring datasets can quickly become fiscal black holes for resource-constrained startups. Their key role is to minimise these costs, ensuring that high-quality, ready-to-use data is within reach for even the leanest of teams.

Funding too is a critical hurdle, as deep tech and AI startups often require larger investment rounds than their counterparts in other sectors. By curating a network of deep tech and AI-focused investors, accelerators are empowering startups to secure the capital they need to bring their data-driven visions to life.

Fuelling the fire: talent and capital for India’s AI dream

While data may be the fuel, talent and capital are the sparks, which are critical components shaping India’s AI ambitions. Accelerators are constantly curating a network of investors with the bandwidth and appetite to back deeptech and AI startups. They play a pivotal role by assembling a cohort of venture capitalists and angel investors, both domestic and international, and connecting startups with these forward-thinking investors.

Yet, even with ample funding, the scarcity of AI talent poses a significant hurdle. Many Indian startups find themselves relying on expertise from the United States, Israel and other tech hubs, as the domestic talent pool struggles to keep pace with demand.

Addressing this skills gap head-on needs a comprehensive suite of AI courses and certifications. This is a long-term investment in India’s AI future, equipping a new generation with the knowledge and skills to drive homegrown innovation.

Creating academia-industry synergies

Startup accelerators play a critical role in fostering strategic academia-industry partnerships. Collaborations with premier institutions like IITs and universities abroad are birthing tailored AI curricula. Initiatives are empowering academia to integrate AI into education through industry knowledge exchange.

The underlying message is clear: nurturing a world-class AI workforce demands tearing down siloes and catalysing seamless collaboration between universities and the corporate world.

From exporters to indigenous pioneers

India aims to become the world’s largest exporter of AI services, leveraging the country’s vast population and talent reserves. The next half decade will witness a watershed shift as India transitions from a services outpost to a powerhouse birthing trailblazing AI products and solutions.

While the Global North currently leads innovation, an indigenous renaissance will propel India to the vanguard, setting new global benchmarks and leading the Global South.

To aspiring Indian entrepreneurs, the message is clear: seize the moment.

With lots of data, government backing, and resources, it’s easier than ever to create powerful AI solutions with global impact. By tackling funding, talent, and accessibility challenges, we are building a self-sustaining AI ecosystem in India, unlocking indigenous innovation and driving the nation to the forefront of AI revolution through data, capital, and human ingenuity.

The author is the CEO of MATH (Machine Learning and Artificial Intelligence Technology Hub).