Context

• The aftermath of the 2024 U.S. presidential election has indicated a renewed wave of protectionist economic policies, most notably in the form of substantial tariffs on imported components crucial to artificial intelligence (AI) infrastructure.
• While intended to strengthen domestic industry and reduce dependency on foreign technology, these tariffs are catalysing a significant transformation in the global technology supply chains that underpin AI development.
• This shift carries implications not only for major players like the United States and China but also for emerging economies such as India, which now finds itself navigating both peril and promise as a potential third option in this technological power rivalry.

The Economic Repercussions of Tariff Expansion and Theoretical and Empirical Insights

• The Economic Repercussions of Tariff Expansion
  • In 2024, electronics imports to the U.S. totalled nearly $486 billion, with data processing machines accounting for approximately $200 billion.
  • These imports largely originated from tariff-targeted nations such as China, Mexico, Taiwan, and Vietnam.
  • The new tariff regime, extending up to 27% on critical AI hardware components, has made the U.S. one of the most expensive environments for AI infrastructure development.
  • This paradoxically incentivizes firms to relocate data centre operations abroad, often to China, the very competitor the tariffs aim to isolate.
  • This scenario echoes the consequences of the earlier tariff wave during 2018–2020, when prices for imported semiconductors surged.
  • Although these protectionist policies aim to develop domestic production by substituting imports with local manufacturing, they ignore the complexities of globalized AI hardware supply chains.
  • AI components are highly specialised and require globally dispersed expertise.
  • Artificial segmentation of these networks through tariffs leads to inefficiencies and higher costs.
• Theoretical and Empirical Insights
  • Classical economic theories offer mixed predictions about the effectiveness of such policies.
  • While import substitution can stimulate domestic manufacturing, Ricardian trade theory underscores the enduring relevance of comparative advantage.
  • Empirical studies further dampen the optimism surrounding tariffs.
  • A one standard deviation increase in tariffs can reduce output growth by 0.4% over five years, and reversing the current U.S. tariffs could yield a 4% cumulative output gain.
  • The implications for AI development are profound. Rapid innovation cycles in AI demand constant access to cutting-edge technology and seamless international collaboration.
  • Tariffs not only inflate the costs of essential components but also introduce uncertainty that discourages long-term investment.
  • Additionally, by shielding domestic firms from competition, they may reduce the incentive to innovate, leading to what economists term deadweight loss, a state where diminished trade volume benefits neither consumers nor producers.

AI Infrastructure and the Innovation Bottleneck

• The projected demand for AI chip capacity is staggering, with data centre power requirements expected to rise from 11 gigawatts (GW) in 2024 to 327 GW by 2030.
• Without the corresponding infrastructure growth, U.S. competitiveness in AI risks erosion.
• Access to advanced computational infrastructure is increasingly the primary determinant of AI innovation capacity, reinforcing a global stratification where resource-rich nations outpace others.
• Tariffs also alter technology transfer dynamics. While those imposed by developed countries typically inhibit transfer and innovation, similar measures by developing nations can sometimes catalyse domestic innovation while disrupting wage structures and technology access.
• This complex interplay risks exacerbating global inequalities in AI capabilities.

India’s Emerging Role in a Polarised Landscape

• Amidst these shifts, India has emerged as a strategic alternative in the U.S.-China tech rivalry.
• With IT export growth rates between 3.3% and 5.1% and an increasing AI and digital engineering sector, India is positioning itself as a viable manufacturing and innovation hub.
• Government initiatives in semiconductor design and fabrication, alongside investments from multinational corporations such as AMD, underscore India’s growing relevance.
• India’s strengths lie in its cost-effective labour market and a massive pool of technically skilled graduates, approximately 1.5 million engineering students annually.
• Yet, its heavy dependence on imported hardware and international partnerships exposes it to the same tariff-induced vulnerabilities faced by others.
• Nevertheless, as firms seek to diversify away from China, India could benefit as a preferred destination for manufacturing and data centre development.

Broader Implications of Tariff Policies

• Shifting Dynamics and Cost Reduction
  • Tariff policies have also triggered what economists describe as ‘capital substitution effects.’
  • As hardware costs escalate, companies are prioritising algorithmic efficiency, model compression, and architectural innovations over brute computational force.
  • This shift is driving a dramatic reduction in the cost of using AI models, by as much as 40-fold annually, without a commensurate rise in consumer prices.
• Decentralisation of AI
  • Moreover, differing regulatory environments can mediate the impact of tariffs.
  • Nations with more lenient data protection rules and broader digital access may offset hardware disadvantages through richer datasets for AI training, creating new competitive dynamics that defy straightforward economic analysis.
  • An unexpected outcome of this evolving landscape is the architectural decentralisation of AI.
  • The rise of application-specific integrated circuits (ASICs), projected to account for over 50% of AI workload accelerators by 2028, signifies a shift away from general-purpose computing.
  • This trend echoes the decentralisation seen in the transition from mainframes to personal computers in the 1980s, indicating that constraints, like tariffs, often spur innovation in unexpected ways.

Conclusion

• The restructuring of global AI supply chains, spurred by renewed U.S. tariffs, underscores the delicate balance between national economic strategy and global technological progress.
• While intended to protect and stimulate domestic industry, such protectionist measures risk stalling innovation, inflating costs, and fragmenting a deeply interconnected technological ecosystem.
• For nations like India, this presents both a challenge and an opportunity: to navigate these disruptions skillfully and emerge as a pivotal player in the evolving AI order.
• Ultimately, the trajectory of AI development in this new era will be shaped not just by technological capability, but by how nations choose to wield their economic and regulatory power.