By Debashish Banerjee and Shrenik Shah
Driven by the global buzz around AI and analytics, India’s tech and digital talent, and push from the government, India is emerging as a powerhouse in this area. Estimated to grow at a year-over-year CAGR of more than 30 percent, India Inc. has adopted AI in various segments. India might be behind a couple of global matured markets, but far ahead amongst developing economies. The application of AI brings in 3–10X improvement in business processes. Hence, if used effectively, the technology will have a significant contribution to India’s ambitious goals of reaching US$ 5 trillion economy.
The central and multiple state governments have launched various schemes to push AI adoption in India. Some of these schemes/initiatives are “AI for all” by Niti Ayog and Chair at GPAI in the current G20 summit. MeitY also plans to launch IndiaAI, Bhasini Programme, and YuvAI for skilling Indian youth by the central government. Similarly, multiple state government schemes (notably Tamil Nadu, Telangana, and Karnataka) have been launched to grow and develop skills, propel India Inc and investments in this area, and regulate and govern the use of AI.
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While multiple initiatives have been introduced to make India a global AI hub, a few areas need to be considered. First, accelerate programme execution. AI research and such programmes are being launched by almost all mature countries. It is a topic of innovation where speed (and possibly that is the only thing) matters. Second, start reaping the benefits by launching specific programmes under Public-Private Partnership (PPP) with crowd-sourcing ideas, strict timelines, and scaled-up solutions for the country. Third and possibly most critical is the focus on the two foundational elements of AI – data (collection, storage, and analytics) and trustworthy use of AI.
Top asks
Expectation #1: Accelerate research and development for use of AI in various areas, including tax –
While research publications and patents in this area have improved from India, we are still way behind in terms of innovation, citation index, and global exposure. The government should boost investments in AI and identify new research areas, such as quantum computing in AI, digital nudge for social good using AI, Explainable AI (XAI), Gen Chem and Computational Biology, and smart and connected cities. Governments’ role in promoting academia-industry collaboration will be key. Choosing one or two of the transformational areas mentioned above that still need solutions and require a faster path to completion.
– A dedicated pool of officers across direct and indirect taxes should have requisite knowledge of AI and its use. This will enable them to use AI in tax assessment, tax administration, and taxpayer facilitation. In the long run, use of AI by tax officials will help focus on non-compliant taxpayers, including early detection of non-compliance trends and taking preventive measures.
Expectation #2: Promote PPP model with value-based implementation
– India’s AI strategy focuses on social impact and has called out three sectors as a priority – agriculture, education, and healthcare. The key is to identify specific use cases that the government can implement; these cases should have the maximum impact on the society at large. List the key challenges in these sectors, crowd-source ideas, implement those ideas (possibly under the PPP model with value-based impact), and scale the solution to be the service provider to the globe. Some ideas could be the ones mentioned below:
-Digitising lawsuits and judgements in the tax area, and implementing a triage model using efficient reviews on tax, property, marital, and other easy-to-review litigations.
-Using lifestyle-based data to predict future health score (disease propensity models) for the population to reduce the burden on healthcare and proactive mitigation
-Digital nudge using AI to prevent fraud on government schemes, financial and tax-related transactions, and social issues, such as Swatch Bharat
-Quality education in local languages for rural India using LLMs specific to Indian languages possibly under the national language transition mission
-Use of satellite images from ISRO on the crop insurance claims process to make it easy for farmers
Expectation #3: Focus on centralised data repositories for the country
– India has taken various significant steps in this area with Adhaar, CoWin, portability of insurance policies, and multiple other initiatives. However, to boost AI and analytics further, we need to take the following steps:
-Improve the trust of customers and organisations (locally and globally) that this data is protected and secured. We must change the negative perception and narrative that may exist today.
-Completeness of data in several areas, such as having an Electronic Health Records (HER) and centralised medical record database such as those in other mature countries for effective healthcare solutions
-Limited but allowable access to the data for research, crowd-sourcing new ideas, and use by industry (using the latest tools, such as creating and opening model APIs and split learning).
Expectation #4: Focus on trustworthy AI
Establishing a governance mechanism is crucial to ensure trustworthy AI, covering everything from data sourcing and storage to the application of AI methods. This is a challenging task, particularly in advancing research and creating intellectual properties, especially considering India’s diverse landscape.
– Defining governance and creating frameworks on several areas, including the ones mentioned below, are crucial: – Data privacy and accountability
– Transparency, attributability, reliability, and robustness of models
– Fair and impartial use of tools
– Safety and security of technology stacks
– Ownership of results
Debashish Banerjee and Shrenik Shah are Partners at Deloitte India.