Despite these hurdles, many believe India is well-positioned to leap ahead armed with technology-specifically AI. At the recently held 10th edition of Google for India in New Delhi, Google India’s Roma Datta Chobey stated that the country’s AI-fuelled leap can propel an entire generation of Indians towards ‘escape velocity’.
Many experts offer a caveat: AI isn’t a silver bullet. While its potential is immense in key sectors, success depends heavily on collaboration between governments, research institutions and non-profits. Together, they can roll out scalable, effective solutions that align with the needs of the population.
India’s National Strategy for Artificial Intelligence (#AIforall) describes the country as the perfect testbed for global enterprises to develop and scale AI solutions. Given the size and diversity of population, AI models developed here can be less biased, making India’s success a template for solving similar issues around the world. Solving for India, then, means solving for the world.
Across the country, AI-driven projects are being launched in sectors identified as ‘national priorities’-education, health, agriculture, smart cities and mobility. That’s not all, states such as Telangana are leveraging AI for monitoring forests in real-time to take prompt action against poaching and illegal logging. Rockefeller Foundation and Karnataka have unveiled an AI-driven disease surveillance system.
These initiatives not only offer new solutions, but also generate lessons. Wadhwani AI works with GoI and states since 2018 to identify problems and develop AI-driven solutions that are then integrated with the government’s existing technology frameworks allowing both stakeholders to experience AI deployment at scale together.According to Wadhwani AI CEO Shekar Sivasubramanian, early learnings from the field have been instructive:Distinct user groups India’s AI journey caters to two different user bases-‘India,’ representing urban, well-connected citizens, and ‘Bharat,’ where many people are using smartphones for the first time. For ‘Bharat,’ AI solutions need to be simple and intuitive, considering the learning curve that comes with new tech. While AI collects data from broad demographic groups, its delivery must be personal, considering each user’s context, language and communication preferences.
Data challenges With India’s diverse society, collecting representative data is a challenge. While perfect data is elusive, making the most of what’s available, accepting that tech evolves, with the aim to build systems that work even with imperfect data should be the focus.
Agriculture, for example, presents a unique problem. Which is where solutions like Agri Stack, the GoI digital foundation being set up to make it easier to bring various stakeholders together, can help. ‘While there is a lot of India or state/district level data available, plot size-based data is unavailable,’ says The/Nudge Institute’s managing partner Akshay Soni, adding, ‘There isn’t consensus that small plot sizes reduce productivity. Unless the data is available, it’s difficult to look at solutions for aggregation of land… I am hoping that Agri Stack will solve this issue.’
Trust is key Building trust among users is critical, particularly in rural areas. A pest management solution for cotton farmers initially faced hurdles when some farmers misunderstood how to use it, sending photos of the sky instead of pests. This highlighted the importance of clear communication and user education for successful AI adoption.
Cascading learnings Wadhwani AI is partnering with Gujarat government to implement a reading fluency solution, reaching 6 mn students. The AI-driven tool listens to students read aloud, evaluates their performance and provides feedback to teachers in real-time. It’s now exploring ways to extend this solution to adult professionals, such as plumbers, to improve their language skills for better customer interactions.
Inclusivity and diversity Every AI project must be accessible in 10-12 languages to ensure inclusivity. This not only makes AI tools available to more people, but also helps tailor solutions to individual communication styles. Despite being in its early stages, India’s AI journey provides rich lessons. A recent Google India white paper emphasises that maximising AI’s potential will require collaboration between gov, industry and civil society. The focus must be on investing in infra, building an AI-skilled workforce and ensuring accessibility for all.
AI in India isn’t just about pushing the boundaries of tech, it’s also about creating trust and freeing up people for work that truly needs a human touch. It’s about building safeguards, streamlining solutions and maximising resources. In short, it must be a Tech+Touch combo.
