India must prioritise telecom infrastructure and data access investment to unlock AI potential

EY India’s latest report titled ‘Realising AI for All in India’ underscores the necessity for sustained policies and emphasises the pivotal role that government intervention can play in fostering the beneficial utilisation of AI technology. The report outlines key policy considerations aimed at expediting AI development and ensuring its democratisation. These include revitalising telecom investments, catalysing an open data ecosystem, fostering research initiatives, implementing ethical AI practices, and reforming education to meet the demands of the AI era.

Prashant Singhal, Telecom Leader, Indian Member Firm of EY Global said, “India has made significant strides in positioning AI as a leading development tool. To leverage the full potential of AI, the government is also creating an ecosystem through strategic policy interventions. However, to access India’s readiness to drive widespread social impact, the government must address key areas including technology infrastructure, research capabilities, skills development, regulatory environment, and the establishment of ethical AI guidelines.”

Emphasising the government’s crucial role in steering extensive AI implementation, the report outlines six key considerations to position India as a hub for AI. 

Open data ecosystems: Promote sector-based data trusts and platforms for collecting and sharing data:

Data and AI hold the potential to address dual goals of economic and social value creation and recovery. Open data ecosystems are crucial for advancing AI development, emphasising the need for a robust data infrastructure in priority sectors such as agriculture, healthcare, and mobility. The quality of data determines the effectiveness of an AI model. As part of the IndiaAI Mission, the government will develop a non-personal data collection platform accessible to Indian startups and companies. 

Revive investments in telecoms infrastructure:

Reviving telecom infrastructure to support AI applications, steps include reducing telecom levies, minimizing Right of Way charges, and subsidising fiber deployment costs. Collaborating with operators for rural connectivity and implementing TRAI’s recommendations can expedite deployment. Additional initiatives involve de-risking handset financing, reducing taxes on entry-level smartphones, and encouraging private players to establish ecosystems for refurbished handsets in rural areas, creating a supportive telecom environment for AI growth. 

Promote AI research and AI CoE:

To advance AI in India, it’s vital to focus on regional language research, establish AI Centers of Excellence CoEs, and create tailored datasets for major Indian languages.  Invest in research and development of algorithms and models specific to Indian languages. Promote collaboration between industry regulators, private players, academia, investors, and venture capital firms to expand the regional-language applications and content.

Establish more state-level CoE hubs for AI, with focus areas such as Generative AI and computer vision, or even create sector-driven CoE such as those focused on agriculture, education, public services, etc. 

Establish AI clusters for rural innovation:

To nurture a self-reliant AI ecosystem, vital initiative includes aligning AI clusters with government bio-incubators under Startup India. India needs to step up AI funding and provide targeted incentives to promote the commercialisation of AI applications. Encourage rural innovation through dedicated funds for AI startups in rural areas. Incentivising AI-allied industries in hi-tech manufacturing, particularly essential components like chips and networking equipment, is crucial. 

Implement ethical AI frameworks:

Concerted efforts are needed to address issues of algorithmic bias and other ethical considerations. Ethical AI implementation demands focused efforts to tackle algorithmic bias and ethical concerns. Leading the establishment of comprehensive AI ethics guidelines is crucial. Promoting bias prevention, detection, and mitigation in AI systems is vital. Recommending the development of open-source AI testing frameworks and toolkits supports startups, researchers, and public/private entities. 

Promote public awareness of AI and reform education:

India needs to incorporate fundamental aspects of AI systems starting from the secondary school level. Create mandatory training around automated decision systems’ societal, legal, ethical, and political impacts. Impart working knowledge for non-professional users of AI and build teaching capacity and accelerate digital delivery of education.