BEIJING — Chinese businesses are tapping DeepSeek’s newest artificial intelligence model to see how it can improve productivity.
The Chinese AI model took the world by storm in recent weeks after showcasing its reasoning process and claims to undercut rival OpenAI’s ChatGPT on cost — despite U.S. restrictions on Chinese access to the advanced semiconductors needed to develop the tech.
Eight automakers including BYD, at least nine financial securities companies, three state-owned telecommunications operators and smartphone brand Honor are among the many that have rushed in the last week to integrate with DeepSeek. Cloud computing operators Alibaba, Huawei, Tencent and Baidu have all offered ways for clients to access DeepSeek’s latest model.
“This is quite unprecedented,” Wei Sun, principal analyst of artificial intelligence at Counterpoint Research, said in an email Monday. She pointed to the rate of adoption, scale of business integration and breadth of specific industries covered.
“When we have all of these, we know it’s making a big social and economic impact,” she said.
Optimism over artificial intelligence has spread to Chinese stocks. UBS said Wednesday that AI-related Chinese stocks are up by 15% since the start of the year, outperforming the broader MSCI China Index by 9%.
As a result, less developed parts of China gained greater understanding of AI and its impact, a topic previously limited to conversations in China’s largest cities, said Wenhao Zhang, CEO of the Beijing-based consumer marketing consultancy Doodod.
“It’s a major education of the market. This will push the entire ecosystem’s development,” he said Tuesday in Mandarin, translated by CNBC.
Zhang, who studied AI at Tsinghua University, founded Doodod in 2012 to build customer engagement through social media analysis. He said the company — which counts China Merchant’s Bank and Toyota as clients — started looking at DeepSeek’s offerings late last year, and began using it more after the R1 release in late January.
Another attractive factor for businesses is that DeepSeek’s models are open-source, allowing individuals and companies to download and customize it.
DeepSeek also advertised drastically lower prices for applications to use its tech versus that of OpenAI. ChatGPT is not officially available in mainland China and requires users to provide an overseas phone number and payment method from a supported country such as the U.S.
DeepSeek changed the perception that AI models only belong to big companies and have high implementation costs, said James Tong, CEO of Movitech, an enterprise software company which says its clients include Danone and China’s State Grid.
He said Movitech started integrating an earlier version of DeepSeek in the fourth quarter of last year, helping boost sales by about 25% from the same period in 2023. The company plans to launch a new DeepSeek-integrated application by the end of March to improve clients’ ability to make decisions, he said.
Many recent videos on Chinese social media have showed off how to run a local version of DeepSeek on Apple’s Mac mini.
Apple Mac mini online sales in China climbed significantly from November to January, versus the same period the year prior, according to data from consultancy WPIC. The electronics-focused JD.com site recorded unit sales of around 20,200 in January, up from nearly 19,400 in December and around 12,250 in November, the data showed.
DeepSeek’s affordability is pressuring more expensive AI models to cut prices, enabling more businesses to adopt the tech, said Chim Lee, senior Asia analyst at the Economist Intelligence Unit. He added that open-source models allow finance, banking and healthcare businesses — which aresubject to stringent data protection rules in China — to develop AI applications locally.
“It is still very early to point to concrete business applications, but a key takeaway is that DeepSeek will accelerate the commoditization of AI,” Lee said.
Beijing is also increasing support. China’s national supercomputing network announced Tuesday that eligible companies and individuals can obtain three free months of DeepSeek access, along with subsidized computing power.
The network is similar to OpenAI’s Trump-backed Stargate project in the U.S. for building AI infrastructure — with the potential for “even faster scaling,” Winston Ma, adjunct professor at NYU School of Law said Wednesday. He is also the author of “The Digital War: How China’s Tech Power Shapes the Future of AI, Blockchain and Cyberspace.”
Not centered on DeepSeek
The rush to try out DeepSeek doesn’t mean it will be the only AI provider for Chinese companies. Developers in the U.S. and China are regularly releasing new models.
Movitech also uses Alibaba’s Qwen AI model, Tong said, noting that the market wants the tech that can lower costs and produce results the most, whether it’s OpenAI or DeepSeek.
HangHang AI, which has invested several hundred million yuan to develop AI solutions for companies across 20 industries, uses a range of models, said partner and COO Shu Weibing.
Many people first used “Baidu, then realized it wasn’t as good as Kimi, then it wasn’t as good as [ByteDance’s] Doubao, which also cut prices,” Shu said in Mandarin, translated by CNBC. “Now it’s DeepSeek.”
It remains to be seen how much generative AI can boost productivity and profits.
Shu predicts that small businesses and companies that integrate AI with hardware will benefit more than large, consumer-facing internet platforms, whose AI work so far, he said, has focused more on boosting efficiency rather than creating new consumer services.
Despite AI models’ falling prices, “small and medium-sized businesses may still be in a period of wait-and-see” for adopting the tech due to the relatively high cost for a full deployment, including computing power and customization, Mike Fang, senior director analyst at Gartner, said Wednesday in Mandarin translated by CNBC.
But the consulting firm predicts that by 2027, the average price to access a generative AI model will be less than 1% of what it costs now — and that by 2029, 60% of Chinese businesses will have incorporated AI into their primary products and services, forming the top drivers of revenue growth.
A turbulent week in the U.S. Treasury market prompted the Treasury Department to sharply increase the size of its long-term debt buyback program, as bond prices fell even while equity markets pushed toward record highs. The divergence has drawn attention from fixed-income strategists who see it as a signal of underlying investor unease about federal borrowing levels.
What Happened This Week
U.S. Treasury Secretary Scott Bessent told CNBC on Thursday, August 20, 2026, that the Treasury had doubled the size of its long-term debt buyback operations, moving from roughly $2 billion to at least $4 billion per operation. Bessent indicated the figure could climb further, saying “we’re going to increase the size of the buyback,” and noted the accelerated pace could exceed the announced $4 billion threshold per issue.
Buybacks allow the Treasury to repurchase outstanding government bonds directly from the market, which can help support prices and dampen yield volatility during periods of stress. The expanded program came as stocks staged a late-week recovery: the S&P 500 and Russell 2000 both advanced on Friday, August 21, even as Treasuries logged mild losses, according to Bloomberg market data.
Why Bond and Equity Markets Are Diverging
Capital.com senior market analyst Daniela Hathorn described the week’s dynamic as markets “ending the week on a softer tone after the relative calm of early August was disrupted by renewed pressure in global bond markets, another rise in oil prices, and growing uncertainty around the Federal Reserve’s next move.” She noted that higher long-term borrowing costs are increasingly challenging elevated equity valuations, even as U.S. equities pull back modestly from record highs.
This divergence — equities near record levels while bonds sell off is unusual and reflects two different sets of investor concerns. Equity investors have remained focused on corporate earnings strength, particularly from large technology companies ahead of Nvidia’s closely watched August 26 earnings report. Bond investors, by contrast, are more directly exposed to concerns about the scale of federal borrowing, highlighted this week by the national debt crossing the $40 trillion threshold for the first time.
The Fed and Treasury “Working in Opposite Directions”
Wilmington Trust senior bond portfolio manager Wil Stith told Yahoo Finance that current conditions reflect “the Fed and the Treasury basically working in sort of opposite directions,” adding that the imbalance will likely require the Federal Reserve which he described as having “the larger sandbox” to adjust the federal funds rate rather than relying on Treasury market interventions alone to manage yields.
Notably, the bond market’s reaction to the Treasury’s buyback expansion was relatively muted; strategists described the move as being largely absorbed without a major rally, suggesting the underlying pressure on yields stems from factors, such as inflation persistence and debt sustainability concerns, that a buyback program alone cannot resolve.
What Comes Next
Markets are now looking to two major events in the days ahead: Nvidia’s earnings report on Wednesday, August 26, and the Federal Reserve’s Jackson Hole Economic Symposium, running August 27-29. This will be the first Jackson Hole gathering under new Fed Chair Kevin Warsh, whose public communication style and policy signals remain less established than his predecessors’, according to market commentary from Regards of Wall Street.
For investors, the key metrics to watch are the size and frequency of future Treasury buyback operations, movements in the 10-year Treasury yield, and any policy signals from Warsh’s keynote address. Continued yield volatility alongside record equity valuations would suggest the market imbalance identified this week has not yet been resolved.
The global banking system is undergoing a comprehensive modernization of cross-border payment infrastructure. Driven by real-time settlement networks, open banking APIs, and interoperable messaging standards, financial institutions and multinational corporations are eliminating multi-day delays and reducing transaction costs associated with legacy international wire transfers.
Transition to Real-Time Gross Settlement Networks
Historically, international business-to-business (B2B) payments relied on complex correspondent banking relationships involving intermediary fees and processing delays. In 2026, the widespread adoption of ISO 20022 messaging protocols alongside interconnected Real-Time Gross Settlement (RTGS) systems allows direct, end-to-end processing of cross-border transfers.
Commercial banks are providing corporate clients with continuous, 24/7 payment clearing capabilities. Real-time transaction confirmation and automated FX rate locking allow international businesses to settle cross-border trade obligations within minutes, significantly reducing counterparty risk.
Central Bank Digital Currency (CBDC) Interoperability
Wholesale Central Bank Digital Currency (CBDC) pilot initiatives are reaching operational maturity across several key financial centers. Collaborative multi-CBDC platforms enable participating central banks and commercial institutions to settle foreign exchange and international trade transactions directly on shared distributed ledgers.
These wholesale digital currency networks eliminate traditional clearinghouse delays and minimize foreign exchange slippage. Enterprise treasury departments benefit from enhanced liquidity management, as cross-border cash balances can be deployed and repatriated instantaneously.
Corporate Treasury Transformation
For enterprise treasurers, instant cross-border settlement transforms cash management strategies:
– Working Capital Optimization: Reduced transaction float allows companies to lower precautionary cash reserves and optimize short-term liquidity investments.
– Automated Reconciliation: Enriched data formats embedded in ISO 20022 payment messages streamline automated general ledger posting and invoice matching.
– Reduced Processing Overhead: Account-to-account (A2A) real-time clearing bypasses costly intermediary correspondent banking fees.
Strategic Financial Priorities
1. Upgrade Treasury Systems: Ensure internal core enterprise software supports real-time ISO 20022 payment messaging standards.
2. Leverage Instant Clearing Rails: Utilize direct payment networks to lower cross-border transaction fees and eliminate settlement delays.
3. Evaluate Multi-Currency Liquidity: Modernize liquidity management frameworks to capitalize on 24/7 real-time settlement capabilities.
The global private credit market has solidified its role as a fundamental pillar of enterprise finance, expanding rapidly across middle-market lending, asset-backed finance, and infrastructure financing. As non-bank financial institutions capture a larger share of corporate debt origination, global regulatory bodies are increasing oversight to evaluate market transparency and systemic risk interconnections.
Growth Drivers in Direct Lending
Direct lending platforms have continued to attract substantial institutional allocations from pension funds, sovereign wealth entities, and insurance companies seeking attractive risk-adjusted yields. Private debt funds offer corporate borrowers customized financing structures, faster execution timelines, and confidentiality compared to syndicated loan markets.
In 2026, private credit managers are increasingly financing larger corporate transactions, providing multi-billion-dollar credit facilities for buyout deals and corporate restructurings. The flexibility of private debt contracts—featuring unitranche pricing and tailored covenant packages—has made direct lending the preferred capital source for middle-market enterprise sponsors.
Regulatory Scrutiny and Systemic Risk Assessment
The rapid growth of non-bank intermediation has drawn heightened scrutiny from financial regulators in North America and Europe. Because private debt agreements are negotiated privately without public exchange disclosures, central banks are evaluating potential vulnerabilities related to asset valuation consistency and fund liquidity profiles.
Regulatory agencies are introducing guidelines aimed at improving reporting standards for private investment vehicles managing institutional assets. Key focus areas include monitoring leverage ratios within private credit funds and evaluating indirect credit exposures between commercial banking institutions and private debt funds.
Navigating Elevated Refinancing Costs
With benchmark interest rates remaining elevated, private debt borrowers face higher debt service obligations on floating-rate credit facilities. Financial advisory firms report an increase in proactive liability management strategies, including payment-in-kind (PIK) interest options, equity infusions from sponsors, and covenant modifications.
Private credit managers with deep operational capabilities are actively working alongside portfolio companies to optimize working capital and maintain cash flow coverage ratios during periods of higher borrowing costs.
Key Financial Takeaways
1. Mainstream Asset Class: Private credit has expanded beyond niche alternative asset status into a core corporate finance solution.
2. Enhanced Transparency Standards: Regulatory frameworks are evolving toward greater disclosure requirements for private debt managers.
3. Proactive Risk Management: Lenders and sponsors must prioritize debt sustainability and active portfolio monitoring amid high benchmark rates.