Large-scale adoption of technologies such as AI in sectors like healthcare, agriculture and education needs to be backed by a robust data ecosystem, intellectual property rights and collaboration between private players, according to a report by NITI Aayog.

The discussion paper on ‘National Strategy for Artificial Intelligence #AIforALL’, released by NITI Aayog on Monday, states that while AI has the potential to provide incremental value to a range of sectors, adoption is still driven from a commercial perspective. It should also be used to create societal impact, it said.

Amitabh Kant, CEO, NITI Aayog, said in a tweet that AI should be leveraged to provide quality solutions at scale across education, health, agriculture and efficiency and safety in Smart Cities and Smart Mobility.

But there are gaps to be bridged to reap the benefits of AI on a large scale. For instance, there is a lack of broad-based expertise in research and application. Data ecosystem that enables access to intelligent data is absent as well. Privacy and security are a major concern as there is no formal regulation in place for anonymisation of data.

Combined funding

To overcome the gaps, the report suggests a two-tiered data structure approach. The first one is to build a Centre of Research Excellence focussed on developing existing core research and pushing technology frontiers through creation of new knowledge. The second is the creation of International Centres of Transformational AI to develop and deploy deploying application-based research in collaboration with the private sector. Around ₹200-500 crore, which will be a combination of government and private funding, will be invested to build the infrastructure, the report stated.

The report also suggests adoption of AI across the value chain like start-ups, private sector, public sector undertakings and government entities to unlock the potential by creating a virtuous cycle of supply and demand. It additionally recommends the creation of marketplace model focussing on data collection and aggregation, data annotation and deployable models.

As India gets into the AI wave, there is also a need for a robust intellectual property regime, says the report. Here, IP facilitation centres can help bridge the gap between practitioners and AI developers.

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