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.
Fixed-income markets recorded significant re-pricing during the week ending July 25, 2026, as a convergence of strong labor market metrics and surging energy costs drove U.S. Treasury yields higher across all maturities. The benchmark 10-year Treasury yield climbed toward 4.70%, reaching its highest point in several months. Institutional bond investors rapidly adjusted portfolio durations as expectations for near-term interest rate cuts by the Federal Reserve faded in response to inflation concerns.
The upward shift in sovereign yields reflects a broader fundamental reassessment of global monetary policy. Earlier in the quarter, money markets had priced in a series of rate reductions designed to support economic activity. However, with initial jobless claims falling to 187,000 and crude oil breaching $100 per barrel, fixed-income traders are pricing in a ‘higher-for-longer’ interest rate environment. The inversion between short-term Treasury bills and long-term bonds narrowed, indicating a shift toward term premium expansion.
Rising Treasury yields present both challenges and opportunities for institutional wealth managers. While commercial lenders and mortgage origination volumes face headwinds from elevated borrowing costs, fixed-income investors are locking in attractive real yields on high-quality sovereign and investment-grade corporate bonds. Institutional debt issuers, conversely, are recalibrating their capital structures, opting for shorter-term refinancing instruments or private credit facilities to avoid committing to elevated long-term coupon rates.
Navigating the current bond market landscape demands strict duration management and credit selection. Wealth advisors recommend maintaining flexible fixed-income allocations, combining short-duration Treasuries with inflation-protected securities (TIPS) to shield capital against potential energy-driven inflation spikes while earning dependable nominal income.
Private credit markets reached a pivotal milestone during the week ending July 25, 2026, as non-bank direct lending consortiums captured a record share of middle-market corporate debt originations. With commercial banks maintaining conservative credit standards and public bond yields remaining elevated, corporate borrowers are increasingly turning to private fund managers for customized capital solutions. This expansion marks a permanent structural shift in enterprise finance, establishing private credit as a primary pillar of institutional corporate liquidity.
The acceleration of private credit deals is driven by speed, deal certainty, and flexible terms. Unlike traditional syndicated bank loans that require lengthy underwriting, credit rating approvals, and public roadshows, private direct lenders can structure tailored financing packages within days. Middle-market firms facing upcoming debt maturities are utilizing private debt facilities to execute recapitalizations, strategic acquisitions, and growth capital deployments without risking execution delay in public markets.
However, financial regulators and central bank supervisors are scrutinizing the sector’s rapid growth. Supervisory agencies are evaluating potential systemic risks associated with non-bank leverage, valuation transparency, and liquidity mismatches during economic downturns. Despite regulatory interest, major pension funds, insurance firms, and sovereign wealth entities continue to expand capital allocations to private credit funds, attracted by reliable floating-rate yields that outperform public fixed-income benchmarks.
As private credit matures into a dominant asset class, corporate chief financial officers must evaluate non-bank lenders alongside traditional banking relationships. Direct lending partnerships provide valuable balance sheet resilience, enabling companies to secure flexible financing terms even during periods of public market turbulence.
The landscape of institutional debt markets is undergoing a profound structural shift on July 21, 2026, as major corporate issuers and commercial banks rapidly accelerate the deployment of tokenized debt instruments. Data published by leading capital market consortiums indicates that primary issuances of digital commercial paper and tokenized corporate bonds have reached record volumes this month. By moving legacy debt origination, underwriting, and secondary distribution onto permissioned distributed ledgers, corporate treasurers are unlocking unprecedented operational flexibility and instantaneous cross-border liquidity.
The adoption of tokenized debt is fundamentally altering how enterprise balance sheets manage short-term liquidity needs. Traditional corporate bond settlement cycles historically required multi-day clearing processes involving numerous intermediaries, custodial entities, and clearinghouses. Through programmable smart contracts on distributed ledgers, issuers can now execute atomic settlement—enabling continuous, 24/7 access to institutional capital pools. This instantaneous clearing mechanism drastically reduces counterparty risk, eliminates costly settlement friction, and allows treasury teams to dynamically optimize working capital in real time.
A major catalyst driving this institutional migration is the establishment of comprehensive digital asset regulatory frameworks across major financial hubs. Clear legal guidelines regarding ledger-based securities ownership have provided institutional compliance officers with the regulatory confidence necessary to transition multi-billion-dollar liquidity facilities onto digital platforms. Furthermore, the integration of automated regulatory reporting directly into token smart contracts simplifies ongoing compliance audits, ensuring that secondary market trades automatically enforce investor accreditation limits and tax withholding requirements.
For chief financial officers and institutional portfolio managers, tokenized debt represents a fundamental evolution in fixed-income strategy. Companies that embrace ledger-based debt structures gain direct access to a broader, global base of digital-native institutional investors while substantially reducing borrowing overhead. As ledger interoperability continues to improve across global exchanges, tokenized debt is poised to become the standard infrastructure for global corporate finance.