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BYD Loses EV Market Share As Competition Intensifies In China

BYD, the world’s largest electric vehicle manufacturer, reported a decline in domestic sales during the first two months of 2026. Adjusted for seasonal fluctuations linked to the Chinese New Year, sales fell by 36% year-over-year, highlighting intensifying competition in China’s electric vehicle market.

Competitive Surge And Shifting Market Dynamics

While BYD’s sales weakened, several competitors posted strong gains. Leapmotor and Xiaomi reported year-over-year sales growth of 19% and 48%, respectively. Leapmotor delivered 60,126 vehicles during the two months, while Xiaomi exceeded 59,000 units.

Other manufacturers also recorded significant increases. Deliveries at NIO rose by 77%, while Zeekr reported an 84% increase, according to calculations cited by CNBC.

Not all automakers saw growth. Deliveries at XPeng declined by 42%, while Li Auto recorded a smaller drop of nearly 4%, illustrating uneven performance across the sector.

China’s Leveling Playing Field

Analysts say competition in China’s EV market is becoming more balanced. Leon Cheng, head of the mobility practice at YCP, noted that BYD still holds a substantial market share but faces increasing pressure from competitors targeting mid-range vehicle segments.

New product launches are also reshaping the landscape. Xiaomi’s YU7 SUV became the best-selling passenger vehicle in China in January, surpassing the Tesla Model Y, which had previously held the top position.

Policy changes may have also affected recent sales. China reinstated a 5% purchase tax on new energy vehicles, prompting many consumers to accelerate purchases before the tax took effect.

Push For Self-Reliance And Diversification

Chinese EV manufacturers are increasingly expanding beyond domestic markets. BYD has accelerated its international strategy, and in February, its exports exceeded domestic sales for the first time. Growing overseas demand provides a buffer against rising competition in China, where multiple manufacturers are targeting the same consumer segments.

Regulators are also gradually reducing purchase incentives for electric vehicles to encourage technological development and greater industry self-reliance. Lawrence Loh, professor at the National University of Singapore Business School, noted that this shift is encouraging companies to develop new financing strategies.

Several automakers have already introduced new financing offers. Tesla launched five-year zero-interest loans, while Xiaomi introduced seven-year low-interest financing options aimed at maintaining consumer demand.

Looking Ahead

BYD is preparing new product launches for the domestic market later this year, including models featuring updated battery technologies and driver-assistance systems.

Industry observers say these developments could support renewed demand while avoiding another round of aggressive price competition in China’s EV sector.

AI Spending Is Complicating The Fed’s Fight Against Inflation

Silicon Valley leaders have long argued that artificial intelligence will make technology and services dramatically cheaper. OpenAI CEO Sam Altman has described a future where intelligence becomes extremely inexpensive, while Tesla and SpaceX CEO Elon Musk has predicted that AI and robotics will create greater abundance and drive down costs.

So far, those benefits have yet to materialise at scale. AI adoption remains relatively slow, while the enormous investment needed for data centres and AI infrastructure is putting pressure on electricity prices, supply chains and other costs. For the Federal Reserve, this creates a difficult balancing act: AI could eventually boost productivity and reduce inflation, but its current buildout is contributing to higher prices.

OpenAI chief economist Ronnie Chatterji said AI needs to be adopted by organisations and generate measurable value before its broader economic impact becomes visible in productivity statistics.

AI Adoption Remains Uneven

Capital spending on AI infrastructure in the U.S. is expected to reach $581 billion this year, according to Goldman Sachs Research, with global investment potentially reaching $1 trillion.

Despite the scale of spending, adoption remains far from universal. A May survey by the U.S. Census Bureau found that 17% to 20% of U.S. businesses reported using AI, with adoption significantly higher among large companies.

Companies that have implemented AI at scale also highlight the challenges. Julie Averill, former CIO of Lululemon, said successful deployment requires changes in employee behaviour and trust in the technology. OpenAI has observed a similar divide: its most advanced business users deploy AI at around eight times the rate of average companies.

Why Productivity Gains May Take Time

Economists point to the limits of automation. AI can perform individual tasks effectively, but many jobs combine tasks that are difficult to automate.

Stanford professor Charles Jones refers to these as “weak links”. Radiology, for example, involves interpreting scans but also communicating with patients and working with colleagues. AI can automate part of the job without eliminating the profession itself.

As a result, the full economic impact of AI may not become clear until businesses adopt the technology more broadly and reorganise their operations around it.

AI Adds To The Fed’s Policy Challenge

AI’s economic impact has become part of the Federal Reserve’s policy debate. Fed Chairman Kevin Warsh has argued that AI could eventually become a significant disinflationary force by increasing productivity and strengthening U.S. competitiveness.

Other officials are more cautious. In July, the Fed kept interest rates at 3.5% to 3.75%, while some officials expressed concern that AI infrastructure spending could add to inflationary pressures.

Minneapolis Fed President Neel Kashkari pointed to massive data-centre investment as a new source of demand. Household electricity prices rose 10% in the two years through July, compared with a 6.2% increase in overall consumer prices. Meanwhile, shortages of chips and other AI components are pushing up costs. JPMorgan Chase estimates that DRAM prices could rise 400% by the end of 2026 compared with 2024.

Warsh has consequently adopted a more cautious tone, saying that while AI investment is laying the groundwork for future growth, the timing and scale of its economic effects remain difficult to predict.

For the Fed, the challenge is clear: AI could eventually deliver major productivity gains, but the cost of building that future is already showing up in the economy.

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