Three areas need attention if India is aiming to become the AI powerhouse of the world
The pandemic has taught us many lessons and opened our minds to new ways of doing things, including understanding the potential of technologies such as artificial intelligence (AI) and machine learning (ML). AI/ML models and algorithms have supplemented the work of healthcare professionals, medical researchers, public health authorities and local administrations in monitoring and predicting trends.
Lockdowns have led to a boom in Internet consumption. According to the Department of Telecommunications, Internet consumption in India rose by 13% after the lockdown was announced. Higher consumption has generated goldmines of user data that online businesses can harness. COVID-19 has created an AI moment that India can ill afford to miss.
India’s rising eminence in AI
We have made significant progress in AI capability-building in the past few years through government initiatives and private sector investments. NITI Aayog’s national strategy for AI envisages ‘AI for all’ for inclusive growth, and identifies healthcare, agriculture, education, smart cities and infrastructure, and smart mobility and transportation as focus areas for AI-led solutions for social impact. The Telangana, Karnataka, Tamil Nadu and Maharashtra governments, among others, have announced policies and strategies for AI adoption. Technology companies have established AI centres of excellence to create solutions for global clients.
India has a thriving AI start-up ecosystem with cutting-edge solutions being developed in areas such as cancer screening, smart farming and conversational AI for the use of enterprises. Our talent pool in AI/ML is fast growing, with over 5,00,000 people working on these technologies at present. India is thus poised to become the AI powerhouse of the world. And with that, there is a potential of the rise of an AI economy in the country.
Data and AI services are expected to help boost India’s economic growth in a big way. Nasscom believes that data and AI will contribute $450 billion-$500 billion to India’s GDP by 2025, which is around 10% of the government’s aspiration of a $5 trillion economy. The thrust will come from three key segments: consumer goods and retail, agriculture, and banking and insurance.
As more opportunities are created, we can expect a net positive effect on employment generation. The growing AI economy is estimated to create over 20 million technical roles alone. AI can create not just niche solutions to specific problems that banks and other service providers are deploying, such as speeding up loan application processing or improving customer service; it can also provide solutions for better governance and social impact.
For example, during the lockdown, the Telangana police used AI-enabled automated number plate recognition software to catch violations. The pandemic has thus provided technology companies in the country a great opportunity to test their own capabilities to create solutions for fast evolving, real-world situations. We are now better prepared for an AI-led future in which we not just solve business problems but also find answers to complex social issues.
Top priorities for India
The stakes are high for India. We need to speed up our readiness to seize the opportunities that the future presents. Three areas need our attention. The first is talent development. No meaningful conversation on AI preparedness can take place unless we are able to meet the rising demand with the right talent. In 2019, we nearly doubled our AI workforce to 72,000 from 40,000 the year before.
However, the demand continues to outpace the supply. That means our efforts to develop talent must pick up speed. The second area is policies around data usage, governance and security. Without data, there cannot be AI. However, we need a balanced approach in the way we harness and utilise data. We need a robust legal framework that governs data and serves as the base for the ethical use of AI.
Third, though the use of digital technologies has gone up, the level of digitisation continues to be low. This poses a big challenge for organisations in finding the right amount of training data to run AI/ML algorithms, which in turn affects the accuracy of the results. Then there is the problem of availability of clean datasets. Organisations need to invest in data management frameworks that will clean their data before they are analysed, thus vastly improving the outcomes of AI models.
The future for AI looks promising but to convert the potential into reality, India will need better strategies around talent development, stronger policies for data usage and governance, and more investments in creating a technology infrastructure that can truly leverage AI.