These systems represent a quantum leap in AI capabilities, offering the potential to augment human creativity, streamline complex processes, and solve previously intractable problems.

India has emerged as a frontrunner in embracing this technology. According to a May 2024 Deloitte survey, India ranks first in the adoption of Generative AI technology across the Asia Pacific region. An impressive 93 per cent of students and 83 per cent of employees in India are actively engaging with the technology, positioning the country as a leader among 13 surveyed nations.

Building on this momentum, the Indian government has unveiled ambitious plans to develop its own foundational AI model. With an initial outlay of Rs 2,000 crore, this project aims to create an AI system tailored for Indian companies, entrepreneurs, academics, and researchers. The initiative, likely to be launched soon, will be led by the India AI Innovation Centre under the Rs 10,000 crore India AI Mission.

This homegrown foundational model will be designed to address India's unique needs, including multilingual capabilities to serve the country's diverse linguistic landscape. The government plans to leverage publicly available data, digitised records from public libraries, and anonymised non-personal data volunteered by companies and researchers to train the model.

The Semiconductor Backbone

While the promise of Generative AI is immense, its realisation hinges on a critical component: Semiconductors. These tiny chips, etched with intricate circuits, form the very foundation upon which the towering achievements of AI are built. As AI models grow in complexity and capability, they demand ever more sophisticated hardware to train and run them effectively.

The symbiotic relationship between AI and semiconductors has spurred remarkable innovations in chip design. Traditional CPUs have given way to specialised hardware like GPUs (Graphics Processing Units), TPUs (Tensor Processing Units) and NPUs (Neural Processing Units), optimised for the parallel processing demands of AI workloads. These chips can perform the complex matrix multiplications that form the backbone of neural networks at unprecedented speeds.

Moreover, the push towards edge AI — running AI models on devices rather than in the cloud — has driven the development of energy-efficient chips that can perform complex computations with minimal power consumption. This trend is enabling AI capabilities in smartphones, autonomous vehicles, and IoT devices, bringing the power of AI to our everyday lives.

The Geopolitical Imperative

The critical importance of semiconductors in AI development has elevated chip production to a matter of national security. The United States has recognised this crucial link between semiconductor manufacturing and AI leadership, responding with landmark legislation like the CHIPS and Science Act.

The CHIPS Act aims to attract microchip manufacturing back to the United States. For several decades the bulk of the manufacturing process has been done offshore, and with the CHIPS Act, the US looks to bring these processes back to the country.

This comprehensive policy framework, with its US$ 50 billion allocation to enhance domestic manufacturing and R&D in semiconductors, demonstrates how nations can strategically position themselves in the AI race through semiconductor policy. 

However, while the CHIPS Act has resulted in a surge in business activity and increased investment into the semiconductor ecosystem by US companies, there have been some challenges to its implementation. Some projects under the Act are reported to have significant delays and disruptions in the operation of their facilities. The lack of a trained workforce in the US is also another hurdle for companies which are breaking ground on semiconductor manufacturing plants. 

While the US is taking the lead in this field, countries like China, Taiwan and South Korea are projected to lead global chip making over the next three years. Furthermore, the global expenditure on semiconductor chip production over the next three years is expected to be around US$ 400 billion. 

For India, the path forward requires similar bold policy initiatives. While the country has already taken steps with its Rs 2,000 crore investment in developing a homegrown foundational AI model, a parallel focus on semiconductor manufacturing infrastructure is crucial. The government's Rs 10,000 crore India AI Mission could be complemented by a comprehensive semiconductor strategy that includes:

1. Significant financial incentives for domestic semiconductor manufacturing
2. Research and development support for chip design and fabrication
3. Strategic partnerships with global semiconductor leaders
4. Development of specialised semiconductor talent through education and training programs

Building A Robust Success Framework

India's position in this technological race is unique. While the US CHIPS Act focuses on regaining manufacturing leadership lost to East Asian countries, India has the opportunity to build its semiconductor ecosystem from the ground up, tailored to its AI ambitions. The country's strong software expertise, combined with its growing AI capabilities, provides a foundation upon which to build a robust semiconductor industry.

The current global competitive landscape underscores the urgency of this mission. Taiwan, through TSMC, produces over 50 per cent of the world's semiconductors and about 90 per cent of the most advanced chips. South Korea, led by Samsung and SK Hynix, dominates memory chip production. China continues its aggressive investments in semiconductor manufacturing despite export controls and other challenges.

India's policy framework must address these competitive realities while leveraging its unique strengths. The country's large pool of technical talent, growing domestic market, and established position in global technology services provide advantages that, with the right policy support, could accelerate its entry into semiconductor manufacturing.

A Holistic Approach to AI Leadership

As we marvel at the latest achievements in generative AI and India's bold steps towards becoming an AI powerhouse, we must recognise that policy frameworks play a crucial role in shaping technological futures. The US CHIPS Act demonstrates how targeted legislation can catalyse industrial development and technological innovation. For India to truly realise its AI ambitions and capitalise on the enthusiasm of its "generation AI", a similarly comprehensive policy approach is necessary.

This means not only investing in AI research and development but also creating a supportive policy environment for building a robust semiconductor industry. By learning from global examples like the CHIPS Act while adapting strategies to its unique context, India can secure its place at the forefront of the global AI revolution. The combination of far-sighted policy, strategic investments, and technological innovation will be key to driving economic growth and technological independence in the age of artificial intelligence.

(The writer is a fellow at the Pacific Forum. Views are personal)