Tesla’s China-produced electric vehicle deliveries showed modest resilience in January 2026, rising 9% year-on-year to 69,129 units from 63,238 in January 2025, according to data published by the China Passenger Car Association (CPCA) on Wednesday.

The figures, which reflect shipments from Tesla’s Shanghai Gigafactory for both domestic sales and exports, placed Tesla third among major Chinese EV makers, behind BYD’s 205,518 units and Geely’s 124,252 vehicles.

While the increase marks a positive contrast to the broader market’s slowdown, analysts caution that the numbers primarily reflect production and export dynamics rather than a clear resurgence in domestic demand. Tesla’s Shanghai plant produces the Model 3 and Model Y for the Chinese market as well as for export to Europe, Asia-Pacific, and other regions.

New registrations—a closer proxy for actual sales—showed only slight growth in Europe in January, per Reuters tracking, with no clear domestic uptick reported. The performance comes against a backdrop of intensifying challenges in China’s EV market. New energy vehicle (NEV) sales, including battery-electric and plug-in hybrid models, grew just 1% year-on-year in January—the fourth consecutive month of decelerating growth, according to CPCA data.

The slowdown reflects a combination of policy shifts, economic pressures, and fierce domestic competition. A key policy change took effect on January 1, 2026, when China reinstated a 5% purchase tax on NEVs after more than a decade of full exemption from the 10% vehicle purchase tax. This reversal has prompted some consumers to delay purchases, with analysts expecting further moderation in early 2026 demand.

“We see increasing pressure on China’s auto market in 2026, driven by a combination of policy and competitive factors,” Helen Liu, partner at Bain & Company, noted.

Tu Le, founder of Sino Auto Insights, said: “We know [EV sales will] slow, we just don’t know by how much. We’ll know much better after the first quarter is over.”

Tesla has faced particularly stiff competition from local rivals offering more affordable models. The base Model 3 sedan starts at around 235,500 yuan ($33,943), nearly three times the price of BYD’s Seal base model at approximately 79,800 yuan. To counter this, Tesla has introduced aggressive incentives on its Chinese website, including five-year 0% interest loans and seven-year ultra-low interest rate loans for orders placed before February 28, 2026.

The price war has squeezed margins across the industry, with Abby Tu, principal research analyst at S&P Global Mobility, noting: “We have [had] really intense price wars that have gone on, although the government and industry have called on automakers to not engage with aggressive pricing strategies.”

Despite these efforts, Tesla’s full-year 2025 China-produced EV sales fell 4.8%, one of only two major manufacturers to report an annual decline.

Regulatory changes add further complexity. On Monday, February 2, 2026, China’s Ministry of Industry and Information Technology (MIIT) announced that, effective January 1, 2027, all vehicles sold in China must feature interior and exterior mechanical door releases. The rule follows high-profile incidents in the U.S. and China where EV occupants could not escape burning vehicles due to power failures in electronic door-locking systems.

Flush, concealed door handles—popularized by Tesla as a signature design element—will need modification or replacement. Tu Le described the regulation as a “decent sized headache” for Tesla, given the brand’s reliance on minimalist, flush-handle designs. However, he noted that most Chinese automakers are unlikely to be caught off guard.

“When regulators were drafting the new regulations, they consulted OEMs and industry experts intensively,” he said.

Tesla will have a runway to adapt, but the change could require design adjustments and additional costs. Despite these headwinds, Tesla’s Shanghai Gigafactory continues to serve as a major export hub, supporting deliveries to Europe and other markets. The modest January growth may partly reflect export demand and production scheduling rather than pure domestic recovery.

Geely, which climbed to second place in China’s NEV market, reported strong performance across its Galaxy and Zeekr brands, while Aito (Huawei-backed), Leapmotor, and Nio posted year-on-year delivery gains. Broader economic pressures, including a prolonged real estate slump and weak consumer confidence, continue to weigh on discretionary spending.

The auto sector, supporting over 30 million jobs, remains a critical economic pillar. Fitch Ratings economist Alex Muscatelli noted that while autos represent only 3.7% of fixed asset investment (versus real estate’s 23%), further deterioration could prompt Beijing to reinstate subsidies if Q1 data confirms a deeper slowdown.

China’s top leaders will release 2026 policy targets at the annual parliamentary meeting in March. With the Lunar New Year holiday contributing to volatile early-year figures, the full impact of the tax reinstatement and competitive pressures will become clearer later in the year.

Goldman Sachs is accelerating its bet on artificial intelligence, partnering with AI startup Anthropic to build autonomous agents that could fundamentally reshape how core banking functions are performed, from trade accounting to client onboarding.

For the past six months, the Wall Street giant has been working closely with embedded Anthropic engineers to co-develop AI agents powered by Anthropic’s Claude model. The initial focus is on two operationally intensive areas: accounting for trades and transactions, and client vetting and onboarding, according to Goldman’s chief information officer, Marco Argenti.

The agents are still in development, but Argenti said the bank expects to deploy them soon. While he declined to give a specific launch date, the direction is clear: Goldman is no longer treating generative AI as an experimental add-on but as a core pillar of its operating model.

Argenti described the technology as a “digital co-worker” designed to operate alongside humans in roles that are complex, repetitive, and highly scaled. These are functions that sit at the heart of a modern investment bank and traditionally require large teams to manage regulatory requirements, documentation, reconciliations, and approvals.

The initiative fits into a broader transformation outlined by Goldman Sachs CEO David Solomon last year. In October, Solomon said the bank had embarked on a multi-year plan to reorganize itself around generative AI. Even as Goldman benefits from strong revenues in trading and advisory businesses, Solomon said the firm would seek to constrain headcount growth as AI-driven productivity gains take hold.

At Goldman, the move into autonomous agents builds on earlier experiments with AI-assisted coding. Last year, the bank began testing an autonomous coding tool known as Devin, which is now widely available to its engineers. That project served as a proving ground, demonstrating that advanced models could reliably handle complex tasks within a highly regulated environment.

What surprised Goldman’s technology leadership was how quickly those capabilities translated beyond software development. Argenti said Claude’s strength is not limited to writing code, but lies in its ability to reason through complex problems step by step, applying logic across large volumes of data and documents.

That capability is particularly valuable in areas like accounting and compliance, where staff must interpret rules, reconcile discrepancies, and make judgments based on incomplete information. In Argenti’s words, technology teams realized that “there are these other areas of the firm where we could expect the same level of automation and the same level of results that we’re seeing on the coding side.”

The potential operational impact is significant as client onboarding, often slowed by manual checks, document reviews, and regulatory approvals, could be completed much faster. Trade reconciliation issues, which can take days to resolve, could be identified and fixed more quickly, reducing operational risk and improving client experience.

Goldman is also exploring the use of AI agents in other parts of the business. Argenti pointed to possibilities such as employee surveillance and the creation of investment banking pitchbooks, both of which require processing large amounts of information under tight timelines. While these ideas are still exploratory, they underscore how broadly the bank is thinking about automation.

The announcement comes at a sensitive moment for the AI sector. Recent model updates from Anthropic have triggered sharp reactions in financial markets, with investors selling off shares of software companies and reassessing which firms are best positioned to benefit from the AI boom. The volatility reflects growing recognition that rapid improvements in foundation models could disrupt existing business models, including those built around legacy enterprise software.

Goldman’s willingness to work closely with Anthropic also highlights a shift in how large financial institutions engage with AI vendors. Rather than simply buying off-the-shelf tools, Goldman is embedding engineers and co-developing systems tailored to its specific needs, regulatory obligations, and risk controls.

Despite the scale of automation being discussed, Goldman has been cautious in addressing concerns about job losses. The bank employs thousands of people in compliance, accounting, and operations, and Argenti said it would be premature to assume the technology will directly eliminate those roles. Instead, Goldman’s stated aim is to “inject capacity,” allowing teams to do more work faster and improve service quality.

Still, the longer-term implications are difficult to ignore. As AI agents mature, Goldman could reduce its reliance on third-party service providers that currently handle parts of its operational workload. That could shift costs away from external vendors and further concentrate expertise and control inside the bank.

More broadly, Goldman’s strategy signals a bigger change in how Wall Street views technology. Generative AI is no longer framed as a productivity tool for individual workers, but as an organizing principle for the firm itself. By embedding autonomous agents into core processes, Goldman is testing whether a global investment bank can be redesigned around machines that reason, decide, and act with limited human intervention.

If successful, the effort could set a precedent for the industry, forcing rivals to accelerate their own AI adoption or risk falling behind.