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Growing political tensions with Washington are pushing the European Union to seriously prepare for a worst-case scenario in which access to U.S. technology services could be restricted...
India is preparing to dramatically lower import tariffs on European cars, a move that would significantly open one of the world's most protected auto markets. According to sources familiar with the negotiations, tariffs could be slashed from a high of 110% down to 40% as part of a sweeping free trade agreement with the European Union.
The agreement, dubbed "the mother of all deals," could be announced as early as Tuesday, marking the conclusion of lengthy negotiations. Prime Minister Narendra Modi's government has reportedly agreed to an immediate tax reduction for a limited number of cars imported from the 27-nation bloc.
The proposed changes represent the most aggressive step India has taken to open its auto sector. The plan involves a multi-stage process designed to gradually integrate European vehicles into the market.
Key details of the reported plan include:
• Initial Cut: Import duties will immediately drop to 40% for roughly 200,000 combustion-engine cars per year.
• Price Threshold: The reduced tariff will apply to cars with an import price exceeding €15,000 ($17,739).
• Long-Term Goal: The tariff is expected to be lowered further to just 10% over time.
This new tariff structure stands in stark contrast to the current rates of 70% and 110%, which have been a point of contention for global automakers, including criticism from Tesla CEO Elon Musk.
Electric Vehicles Placed on a Slower Track
Notably, battery electric vehicles (EVs) will be excluded from the initial tariff reductions. This carve-out is designed to last for five years to shield investments made by domestic automakers like Mahindra & Mahindra and Tata Motors in India's growing EV industry. After this five-year period, EVs are expected to benefit from similar duty cuts.
India is the world's third-largest car market by sales, trailing only the United States and China. However, its 4.4-million-unit-per-year market is currently dominated by Japan's Suzuki Motor and homegrown brands Mahindra and Tata, which together command a two-thirds market share. European carmakers hold less than 4% of the market.
Lower import taxes would be a significant boost for European brands.
• Luxury Players: Companies like Mercedes-Benz and BMW, which already assemble some cars in India, could expand their offerings and market reach.
• Mass-Market Brands: Automakers such as Volkswagen, Renault, and Stellantis could sell imported models at more competitive prices, allowing them to test consumer demand before committing to local manufacturing.
This policy shift comes as the Indian auto market is projected to expand to 6 million units annually by 2030. Anticipating this growth, some European companies are already increasing their focus on India. Renault is planning a strategic comeback, while the Volkswagen Group is finalizing its next phase of investment through its Skoda brand.
Beyond the auto sector, the free trade pact is expected to expand bilateral trade and support Indian exports in other key areas, such as textiles and jewelry, which have faced tariff pressure in other markets.
The Trump administration's intense focus on Venezuela and Iran centers on a single commodity: oil. But the strategy runs deeper than controlling energy markets. It's a calculated effort to restrict China's access to cheap, reliable crude at the precise moment Beijing needs it most—to power its race for dominance in artificial intelligence (AI).
While this policy has multiple goals, including curbing China's influence in the West and countering the BRICS currency, its most critical function is to create an energy bottleneck for America's chief technological rival.

For years, Venezuela offered an incredibly good deal for China. Sanctioned by the U.S. and isolated from Western markets, Caracas sold its crude at a heavy discount to Chinese refiners willing to accept the risk. This oil wasn't premium, but it was dependable and cheap, supplying about 5% of China's annual needs—a small but significant buffer against global price volatility.
The Trump administration's decision to blockade Venezuelan oil exports and assert control over its infrastructure effectively killed this arrangement. With this U.S. intervention, China lost access to a supply source that accounted for roughly 4% of its needs, forcing Beijing to seek alternatives that are often more expensive, further away, or politically complicated. For the world's largest oil importer, even minor disruptions create major headaches.

Compared to Iran, Venezuela's oil flow to China is minor. China is Iran's single largest oil customer, purchasing as much as 80% of Tehran's exported crude. This deeply discounted oil is the lifeblood for China's independent refineries, petrochemical industry, and power-hungry industrial base. In short, Iranian oil is a critical input for China’s economic and technological growth.
This dependency casts Trump's pressure campaign against the Iranian regime in a new light. The combination of tariffs, strict sanctions enforcement, and support for internal dissent is designed to put China in a strategic bind. Beijing must choose between continuing to buy Iranian oil and risking severe U.S. economic retaliation, or complying with sanctions and losing one of its most vital and affordable energy sources. Either path forces China to pay more for less reliable energy.

There is a common misconception that AI operates in a clean, digital world of algorithms and cloud servers. The reality is that AI runs on electricity, which is still predominantly generated from fossil fuels and nuclear power. The energy requirements are staggering. Training a single large AI model consumes enormous power, and a hyperscale data center can use as much electricity as a medium-sized city.
This physical reality makes energy, not just silicon chips, the primary bottleneck in the global AI competition.
Beijing is acutely aware of this. It continues to approve new coal plants and expand its natural gas infrastructure even as it invests heavily in renewables. This isn't a contradiction; it's a strategy.
• Grid Stability: Oil and gas provide the stable, always-on power that intermittent renewables cannot guarantee, which is essential for data centers running AI systems.
• Industrial Inputs: AI hardware itself is petroleum-dependent. Plastics, resins, coolants, and advanced composites used in servers and chips are all derived from oil.
• Cost of Intelligence: Relatively cheap oil lowers the cost of training AI models. The nation that can train more models faster and for less money gains a decisive advantage.
By cutting China off from discounted oil, the U.S. isn't just raising fuel prices—it's raising the cost of developing intelligence itself.
This is the core of the strategy. The United States doesn't have to win by building more data centers if it can make it too expensive for China to power its own. America benefits from abundant domestic oil and gas, growing LNG exports, and the deep capital markets needed to finance new energy-intensive infrastructure.
China, in contrast, is fundamentally vulnerable. It imports over 70% of its oil, much of it from politically unstable or sanctioned nations. By disrupting these supply chains, the U.S. can make China's AI ambitions more fragile, expensive, and subject to geopolitical pressure. Oil thus becomes a powerful weapon that indirectly targets China's technological progress.
While Russia remains a factor in global energy markets, it is not the primary target of this strategy. The real objective is to slow China's momentum. The Trump administration's energy foreign policy is designed to blunt China's rise without direct conflict, forcing it to spend more capital and operate with a structural disadvantage in the most important technological race of the 21st century.
Ultimately, dominance in AI won't be achieved by writing the best code alone. It will be determined by who can affordably and reliably power the most machines for the longest time. By squeezing Venezuela and pressuring Iran, the U.S. is betting that energy geopolitics, not algorithms, will decide the winner. If that bet pays off, the future of AI will be shaped not just in Silicon Valley or Shenzhen, but in the oil fields and shipping lanes few are watching.
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