The future of artificial intelligence adoption in India

© Provided by The Financial Express However, AI adoption in India can be accelerated through



a store front at night: However, AI adoption in India can be accelerated through the formulation of more focused policies related to innovation, for example, patent control and security.


© Provided by The Financial Express
However, AI adoption in India can be accelerated through the formulation of more focused policies related to innovation, for example, patent control and security.

By Ravi Mehta & Pradeep Rajendran

Covid-19 has accelerated the evolution of the way work is designed and delivered. Many companies and countries are experimenting with innovation using emerging technologies such as artificial intelligence (AI), to reimagine their businesses and operating models making themselves more agile, flexible and responsive.

Enhanced computing power, digitisation, increase in data storage capabilities at reduced costs has improved applicability of AI in business and society. This has resulted in an enhanced focus on AI with many organisations and economies focusing on building and scaling up AI capabilities, including in India.

Currently, AI adoption in India is primarily driven by the large global technology conglomerates, selected startups and the GICs/GCCs (Global Capability Centers) based out of India. Some of the sectors that have adopted AI include:

Banking & financial services industry: A few companies in India have started leveraging AI to solve India-centric issues. For example, a leading fintech company uses AI to develop customised financial products for the highly heterogeneous rural population. Few other banks in India have adopted AI to increase digitisation to improve customer experience, improve investment returns and use algorithms in risk management (for example, fraud detection).

Pharma & healthcare: A healthcare startup in Hyderabad launched AI-powered low-cost ventilators that can capture patient information to make medical intervention decisions. Similarly, a Mumbai-based startup has used AI to analyse chest X-rays to identify the extent of infection in the lungs and help in tuberculosis detection.

Agriculture: A company is using AI to power a sowing app in Andhra Pradesh, resulting in a higher crop yield per hectare. Additionally, AI algorithms are being used to monitor crop and soil health, where AI-based analytics solutions are used to plan events like crop harvesting, pest control and fertilisation to optimise yields.

While there are a few good AI success stories in India, overall, less than 25% of Indian enterprises have deployed AI solutions thus far. Some of the barriers to increases adoption in India include:

  • Limited understanding of AI: Many Indian companies may have not yet understood the full benefits of leveraging AI in their companies
  • Low investments and less evolved startup ecosystem: AI requires an initial investment/incubation period (example, for POCs, discerning real use-cases). Startup/investment funding ecosystem in India is yet to scale up in terms of AI startups and service providers.
  • Limited availability of AI trained talent: There is limited infrastructure to ‘democratise’ and scale-up important AI skills such as deep learning and neural networks.

Countries like China, USA and Israel currently lead the way in terms of AI adoption. India can consider a few learnings from these countries to further scale-up its AI ecosystem while keeping in mind the overall social development and inclusiveness agenda. This requires a focus on three key areas:

Clear central strategy and policy framework: The National Strategy for Artificial Intelligence (NITI Aayog, June 2018) which is focused on inclusive AI (AI for all), and the New Education Policy (NEP, 2020) which addresses the need to inculcate AI in the curriculum are the right strategic steps in this direction to encourage core and applied research. However, AI adoption in India can be accelerated through the formulation of more focused policies related to innovation, for example, patent control and security.

Collaboration among government, corporates and academia: These three critical stakeholders need to come together and work synergistically to undertake actions like nurturing entrepreneurship, promoting re-skilling, encouraging research and development, and driving the policies on the ground. While this is happening in pockets, there is a need to drive this in a structured and consistent manner with clear outcomes.

Leveraging MNCs and their GICs: MNCs and their GICs are leading the way in terms of AI adoption in India, their experience (for example approach, business solutions) can be leveraged effectively to help other companies learn about AI applicability in their industry to further accelerate AI adoption.

More than ever, rapid and scalable innovation has become critically important for companies and countries to survive and thrive in this rapidly evolving complex economic and social environment. As Abraham Lincoln famously said ‘The best way to predict the future is to create it’. AI will play a big role in creating this future, and India, due to its inherent strengths, has the potential to lead the way if it makes the right choices now.

Mehta is partner and Rajendran, associate director, Deloitte India. Views are personal

Source Article