Beijing-based artificial intelligence startup Moonshot AI has confidentially filed for a Hong Kong initial public offering that could raise about $3 billion, three people familiar with the plans told Reuters.

The filing has set up one of the most closely watched Chinese AI listings as investors increasingly turn to the sector for exposure to China’s rapidly developing technology industry.

Moonshot, the developer of the Kimi large language model, is targeting proceeds of around $3 billion in the offering, one of the sources said.

The timing of the potential listing is subject to regulatory approvals, while the amount raised and other financial details could change depending on market conditions, the sources said.

A successful listing would give investors a major new avenue for gaining exposure to China’s generative-AI industry and could provide a valuation benchmark for a group of rapidly expanding domestic AI companies.

Moonshot has been valued at about $50 billion in an ongoing fundraising round, according to two separate sources. That valuation puts the company below some of its major Chinese AI rivals, including DeepSeek, which sources have valued at roughly $74 billion, and Z.AI, formerly known as Zhipu, whose Hong Kong-listed shares give it a market capitalization of about $66 billion.

The potential IPO also comes as Hong Kong’s equity market experiences a resurgence in technology listings. Companies raised $41.2 billion through Hong Kong IPOs as of mid-August, a 142% increase from the same period a year earlier, according to LSEG data, with Chinese technology companies accounting for most of the proceeds.

Moonshot’s latest model, Kimi K3, released in July, has received positive reviews and generated strong demand, according to sources. The company says K3 contains 2.8 trillion parameters, making it the world’s largest open-weight model. The scale of the model has also placed substantial pressure on Moonshot’s computing infrastructure as demand has increased.

The company is now in discussions with Microsoft, Amazon and Google over potential revenue-sharing arrangements that would allow the U.S. cloud companies to host Kimi, according to sources.

A deal with any of the three would be notable because it could become the first major revenue-sharing agreement between a Chinese AI company and a leading U.S. cloud provider.

Such an arrangement would give Moonshot access to substantially greater computing infrastructure and potentially allow its model to reach a much larger international customer base. For the U.S. cloud companies, hosting a leading Chinese AI model could provide a new source of cloud revenue while giving them exposure to demand for AI computing outside the domestic U.S. market.

U.S. Scrutiny Creates Additional Risk

Moonshot has faced growing scrutiny from U.S. officials over allegations that it used restricted Nvidia chips and extracted capabilities from Anthropic’s AI models through a process known as distillation.

U.S. Treasury Secretary Scott Bessent has said he could consider adding Moonshot to a U.S. trade blacklist, potentially increasing the company’s difficulties in obtaining advanced computing technology and accessing international suppliers.

Moonshot has denied that Kimi K3’s performance was achieved through distillation.

The allegations add a significant risk factor for prospective investors. Moonshot’s ability to expand its models depends on access to computing infrastructure, while U.S. restrictions could limit the availability of advanced Nvidia chips or complicate partnerships with American technology companies.

At the same time, potential agreements with Microsoft, Amazon or Google would demonstrate that U.S. cloud infrastructure remains commercially important to Chinese AI developers despite the broader technology rivalry between Washington and Beijing.

IPO Requires Restructuring of Moonshot’s Ownership

Moonshot has also had to make changes to its corporate structure ahead of the IPO.

Two people familiar with the matter said the company had to unwind its offshore incorporation arrangement, known as a red-chip structure, and establish an onshore China domicile to obtain regulatory approval for the Hong Kong listing.

The restructuring reflects the increasing scrutiny Chinese regulators apply to the ownership and overseas structures of strategically important technology companies.

Moonshot was founded in 2023 by Yang Zhilin, an AI researcher who pursued doctoral studies at Carnegie Mellon University in Pittsburgh. Despite its relatively short history, the company has attracted some of China’s largest technology investors.

Its backers include Alibaba, Tencent, IDG Capital and HSG, formerly known as Sequoia Capital China.

The company raised more than $2 billion in May from investors including Meituan, China Mobile and Chinese private-equity firm CPE, according to a fundraising document reviewed by Reuters. That financing brought Moonshot’s total capital raised to more than $5.5 billion.

For the planned IPO, Moonshot is working with Goldman Sachs, CICC and Deutsche Bank.

Chinese AI enters public markets

Moonshot’s planned offering follows a wave of Chinese AI companies tapping Hong Kong’s capital markets. Z.AI and MiniMax have already listed in Hong Kong this year, providing investors with publicly traded proxies for China’s rapidly expanding AI industry.

The listings come as global investors increasingly view AI as a major long-term investment theme, while Chinese companies seek to demonstrate that they can develop competitive models despite restrictions on access to the most advanced U.S. chips.

Moonshot’s potential $3 billion offering would be particularly significant because it would test how much investors are willing to pay for a private Chinese AI company with substantial computing requirements, rapid model development and exposure to geopolitical technology restrictions.

The proposed listing also offers a measure of how China’s AI sector is evolving from a venture-capital-driven industry into one capable of accessing public equity markets.

But Moonshot’s valuation and IPO performance will depend on more than the popularity of Kimi. Investors will need to assess whether the company can turn strong model adoption into sustainable revenue, secure sufficient computing capacity and navigate increasingly restrictive U.S.-China technology controls.

If Moonshot succeeds in raising close to its targeted $3 billion, analysts say the deal could reinforce Hong Kong’s role as a financing hub for China’s technology champions and encourage other AI companies to follow. If demand proves weaker, however, it could expose the gap between the enormous private-market valuations assigned to China’s AI startups and what public-market investors are actually willing to pay.

With more than $5.5 billion already raised privately and a reported $50 billion valuation, Moonshot is entering the public markets with both considerable financial backing and high expectations. Its IPO could therefore become an important test not only for the company, but for the next stage of China’s AI investment cycle.

Chinese rare earth suppliers are refusing to ship materials to U.S. customers for fear of retaliation from Beijing, highlighting the growing vulnerability of American supply chains to China’s control over critical minerals ahead of President Xi Jinping’s planned visit to Washington later this month.

Three people familiar with the trade told Reuters that some Chinese suppliers have declined to fulfil U.S.-bound orders, with several becoming more cautious about transactions that could expose them to scrutiny from Chinese authorities.

The development adds another layer to an already strained rare earth supply chain. The United States has repeatedly pressed Beijing to honor commitments reached in Busan and Beijing over the past year to facilitate the issuance of export licenses, but U.S. companies continue to face delays in obtaining supplies of strategically important minerals.

The issue has become part of Washington’s preparations for Xi’s September 24 visit, according to a source familiar with the planning.

A handful of Chinese rare earth suppliers began refusing some shipments to U.S. companies after Beijing imposed sanctions in early August on the U.S.-based Responsible Business Alliance, or RBA, a major supply-chain monitoring organization.

The suppliers were concerned that complying with the due-diligence requirements of the Responsible Minerals Initiative, a mineral-supply-chain auditing programme associated with the RBA, could expose them to punishment from Beijing, one source with direct knowledge of the matter said.

Other Chinese companies had already stopped shipping certain materials to the United States in recent months to avoid becoming caught between Chinese export controls and U.S. restrictions. One source cited four cases in which Chinese companies declined to send material because they feared the products could ultimately be resold to customers or end users subject to U.S. restrictions.

The significance of the development lies in the way China’s rare earth policy is affecting private commercial decisions. Beijing does not need to block every shipment directly if suppliers, manufacturers and exporters become sufficiently concerned about the consequences of dealing with American customers. That can make the export-control system more powerful while also making supply chains less predictable.

A U.S. official, speaking on condition of anonymity, said the Trump administration continues to press Chinese officials to address what Washington regards as China’s failure to comply with the Busan agreement, along with other bilateral issues.

China’s Ministry of Foreign Affairs has said Beijing remains committed to maintaining global critical-mineral supply chains.

But the dispute is taking place against a backdrop of intensifying U.S.-China competition over technology, manufacturing and national security. Critical minerals have become an important part of that rivalry because rare earths and related materials are essential to products ranging from electric motors and electronics to advanced weapons, aircraft engines and high-performance magnets.

The vulnerability is acute because China dominates the global rare earth supply chain, including processing and magnet production. Reuters reported last month that China accounts for about 90% of global production of rare earth products, including magnets, leaving the United States and other industrial economies heavily dependent on Chinese processing capacity.

Supplies Remain Tight Despite Partial Recovery

China’s restrictions on rare earth exports introduced in April 2025 triggered concerns over shortages in the United States and other major industrial economies.

Exports of some rare earths and permanent magnets have since recovered, but access to several strategically important materials remains constrained. Prices for materials including yttrium, tungsten and other critical inputs used in defense, aerospace and semiconductor manufacturing remain elevated.

Yttrium illustrates the problem.

Chinese exports of yttrium oxide to the United States reached 29 metric tons in July, the second-highest monthly volume since Beijing introduced its export controls. The increase provided some relief to U.S. aerospace companies because yttrium is used in specialty alloys and high-temperature-resistant coatings for aircraft engines.

But the rebound has not restored normal supply. U.S. exports of yttrium remain roughly half their 2024 levels, according to Chinese customs data cited by Reuters, even as China continues shipping the material to other markets.

Some U.S. companies have waited more than six months for export licenses, according to two sources familiar with the situation.

“China has been very effective in using rare earth export controls to impose restraint on the Commerce Department’s Bureau of Industry and Security,” said Reva Goujon, a geopolitical strategist at Rhodium Group.

“Supply chain chokepoints will come into focus, but I would expect Beijing to loosen up critical raw material controls a bit around the summit to deflate U.S. allegations that Beijing is not upholding the Busan truce,” she added.

The recent increase in U.S.-bound yttrium shipments could support that possibility. Several U.S. companies have also recently received multiple licenses after lengthy waits, according to sources, raising expectations that Beijing could approve more shipments around the Xi-Trump meeting.

But even if approvals increase, the episode has exposed a structural weakness in the U.S. supply chain: Washington can negotiate for licenses, but it has limited control over the commercial decisions of Chinese companies that actually produce and export the material.

Japan Faces An Even Sharper Squeeze

The restrictions are not limited to the United States.

Chinese suppliers have been even more reluctant to ship critical minerals to Japanese customers, according to two sources familiar with the trade.

Chinese customs data show that China exported no terbium to Japan between January and August this year, compared with 20 tons during the same period last year. Gallium shipments fell 65%, while yttrium exports plunged 98%.

Terbium and gallium are used in small quantities in high-performance rare earth magnets and other advanced industrial applications.

Japanese companies have previously complained about delays in obtaining permits and lengthy customs inspections for critical minerals.

The squeeze demonstrates how Beijing can apply pressure selectively. Export controls do not necessarily have to affect every commodity or every country equally. Licenses can be accelerated for one market, delayed for another, and effectively withheld from a third, giving China considerable leverage over companies whose production depends on specific minerals.

Against that backdrop, there is growing uncertainty for manufacturers even when physical inventories have not yet reached critical levels. Companies must account not only for the availability of material but also for the possibility that future licenses could be delayed or that suppliers could refuse orders altogether.

A Broader Test for U.S. Supply-Chain Resilience

The dispute is increasingly forcing Washington to confront a difficult reality: building alternative mines is not enough to eliminate dependence on China.

The United States and its allies are investing in new mining, processing, and magnet-making capacity, while companies such as Lynas are expanding operations outside China. Lynas, the largest rare earth producer outside China, has been exploring additional supply deals and supporting the development of a U.S. rare earth magnet supply chain.

But creating a fully independent supply chain takes years because rare earth production involves mining, separation, refining, alloy production and magnet manufacturing. China has built dominance across much of that chain, meaning alternative suppliers must compete not only on access to ore but also on processing expertise, scale and cost.

The geopolitical stakes are consequently rising.

The latest supplier refusals show that China’s leverage extends beyond formal export bans. Beijing’s policies can influence how Chinese companies assess the risks of doing business with foreign customers, particularly when transactions involve supply-chain audits, sensitive end users or industries subject to U.S. national-security restrictions.

That could make the rare earth dispute more difficult to resolve than a conventional tariff disagreement.

The United States wants reliable access to materials essential to its aerospace, defense, energy and technology industries. China wants to preserve control over a strategically valuable part of its industrial base while resisting what it views as U.S. restrictions on Chinese companies and technology.

The result is a supply chain in which commercial transactions are shaped by geopolitical calculations.

However, it is not clear whether Beijing will ease licensing restrictions before or during Xi’s Washington visit as a gesture toward stabilizing the broader trade relationship. It is also not clear whether U.S. manufacturers can reduce their exposure sufficiently to make future Chinese export controls less disruptive.

Nvidia has emerged as one of the technology industry’s largest corporate investors, with the value of its equity holdings soaring more than tenfold over the past year to about $99 billion as the chipmaker deploys its enormous cash resources to shape the rapidly expanding artificial intelligence ecosystem.

Nvidia’s equity investments were valued at $99 billion as of July 26, compared with roughly $7 billion a year earlier and about $2.2 billion two years ago. The company has committed more than $40 billion to investment and financing deals in 2026 alone, expanding its reach across almost every layer of the AI industry, from frontier model developers and specialized cloud providers to networking, photonics, semiconductor manufacturing and emerging software companies.

The strategy gives Nvidia a role that extends well beyond selling GPUs.

By providing capital to companies that buy its chips, build infrastructure around them or develop technologies compatible with its architecture, Nvidia can help finance future demand for its own products while strengthening its position against rival accelerators and increasingly capable custom chips developed by major cloud providers.

“Nvidia has a clear interest in ensuring that its customers and partners prosper to provide future business for Nvidia,” Ian Fogg, research director at CCS Insight, told CNBC.

“Equity investments help companies to innovate, but also give Nvidia a degree of control to encourage companies to take a Nvidia-related innovation path,” he added.

From Chip Supplier to Capital Provider

Nvidia’s transformation into a major strategic investor has been enabled by the extraordinary growth of its core business. The company’s shares have risen about 33% over the past year, while fiscal second-quarter revenue surged 106% to $96.2 billion.

Nvidia remains dominant in the market for advanced GPUs used to train and run AI models, creating a powerful financial feedback loop: demand for AI computing generates revenue for Nvidia, which gives the company more capital to invest in the companies and infrastructure generating the next wave of demand.

Fogg said Nvidia was increasingly seeking to diversify its AI business.

Of the company’s $96.2 billion in quarterly revenue, $48.7 billion came from its Hyperscale segment, which includes the world’s largest cloud providers. The company is therefore trying to broaden the customer base around its technology while creating new sources of demand.

“Increasing the range of customers and creating an AI ecosystem” is becoming a key part of that strategy, Fogg said, with some investments aimed at emerging cloud providers and others targeting new markets such as telecommunications.

Nvidia’s $1 billion investment in Nokia is one example of that expansion.

The company’s most consequential investments have involved the infrastructure needed to support frontier AI models. Nvidia Chief Financial Officer Colette Kress said on the company’s latest earnings call that Nvidia had invested nearly $50 billion in frontier AI laboratories.

In February, Nvidia said it would invest $30 billion in OpenAI as part of the artificial intelligence company’s $110 billion funding round.

The rationale is straightforward. Frontier AI developers have enormous and rapidly growing requirements for computing capacity, but their balance sheets and credit profiles may not be expanding quickly enough to finance the infrastructure independently. That creates an opening for Nvidia to provide capital to companies that will ultimately spend much of that money purchasing Nvidia hardware.

Kress described Nvidia as being needed to help power the “flywheel” between AI model development, infrastructure construction and chip demand. The same model is playing out among so-called neocloud providers, which purchase large quantities of Nvidia GPUs and rent computing capacity to AI companies and other customers.

Nvidia invested $2 billion in CoreWeave in January, while Nebius secured a $2 billion investment from Nvidia in March.

“By injecting capital directly into AI infrastructure financiers, specialized cloud providers and foundation model labs, Nvidia provides these startups with the balance sheet strength to purchase tens of thousands of Nvidia GPUs,” said Naveen Chhabra, principal analyst at Forrester.

The idea is believed to have made Nvidia’s investment strategy potentially self-reinforcing: the company provides capital, the recipient uses the capital to build AI infrastructure, and that infrastructure creates demand for Nvidia’s GPUs.

The investment programme also extends into technologies that could determine the economics of AI data centers in the coming years. Since March, Nvidia has committed at least $6.5 billion to companies developing photonics and optical technologies, which use light rather than electrical signals to transmit data.

Lumentum, Coherent and Marvell each received $2 billion in investments from Nvidia.

Optical networking could become more relevant as AI clusters grow larger and the amount of data moving between processors increases. Conventional electrical interconnects face power and bandwidth constraints, making faster and more energy-efficient networking technologies increasingly valuable.

For Nvidia, investing in those technologies can also ensure that emerging components remain compatible with its broader architecture.

“Optics/networking specialists, like Coherent, receive investments to ensure their tooling, NVLink protocols and design engines remain strictly optimized for Nvidia’s architecture,” Chhabra said.

But analysts see that strategy increasing the cost for customers of moving away from Nvidia’s ecosystem.

The company’s competitive advantage extends beyond the physical GPU. Nvidia’s CUDA software platform, networking technology and broad hardware stack form an integrated ecosystem that customers must consider when evaluating alternatives from AMD or custom accelerators developed by Amazon, Google and other cloud companies.

Nvidia is also using its balance sheet to address supply-chain risks. Its $5 billion investment in Intel has already increased in value to about $30 billion, while its holding in SpaceX was worth approximately $21 billion as of June.

The Intel investment has a dimension beyond potential financial returns. As AI chip production encounters constraints in advanced packaging, high-bandwidth memory and other components, access to manufacturing capacity is becoming an important competitive factor.

Chhabra said Nvidia’s investment in domestic manufacturing options such as Intel could help secure priority access to production, reduce its concentration on Asian foundries and stabilize critical component supplies. Nvidia has remained heavily dependent on a complex global semiconductor supply chain even as demand for its products continues to accelerate.

A $500 Billion Financing Network

Nvidia’s financial ambitions are now becoming large enough to influence the broader structure of AI infrastructure financing.

In August, the company announced partnerships with major investment firms intended to mobilize more than $500 billion in financing for Nvidia GPUs. It also said it would provide up to $105 billion in conditional credit support for an OpenAI data-center project in Ohio.

The company’s planned $12.9 billion acquisition of AI startup Hugging Face, announced Thursday, would take that strategy beyond minority investments and into outright ownership of a major AI software and developer platform.

Together, the deals show how Nvidia is attempting to influence the entire AI value chain rather than simply supplying one of its most important components.

But as Nvidia invests in customers, cloud providers and companies building complementary technologies, the distinction between supplier, investor and financial backer becomes increasingly blurred. The more capital Nvidia provides to companies that subsequently purchase its GPUs, the more important it becomes for investors to distinguish genuine end-user demand from demand enabled by Nvidia’s own financing.

This does not necessarily make the investments uneconomic. Financing constraints are a genuine bottleneck for AI infrastructure, and Nvidia has a strong commercial interest in ensuring that promising customers have enough capital to build computing capacity.

Analysts believe it creates greater exposure to the health of the AI capital cycle.

This is because if AI companies generate sufficient revenue and returns from their computing investments, Nvidia can benefit on multiple fronts: through GPU sales, increased ecosystem adoption, and appreciation in its equity holdings. If the economics of AI infrastructure disappoint, however, the company could face pressure across several channels simultaneously.

Nvidia’s equity portfolio has already benefited enormously from the surge in technology valuations. The $99 billion value of its holdings therefore represents both a strategic asset and a source of market exposure.

Nvidia Is Buying More Than Shares

The broader significance of Nvidia’s approach is that capital has become another competitive weapon. The company is using its financial strength to help build the customers that will consume its products, support technologies that make its architecture more valuable, and secure access to components and infrastructure that could constrain future growth.

That makes Nvidia look like an ecosystem orchestrator rather than a traditional semiconductor company. Its core advantage remains the demand for AI computing. But by deploying billions of dollars across the companies and technologies surrounding that demand, Nvidia is attempting to ensure that the next generation of AI infrastructure is built on, and remains economically tied to, its technology.

The result is a powerful feedback loop: Nvidia’s AI dominance generates cash, the cash finances the AI ecosystem, and the expanding ecosystem generates more demand for Nvidia’s computing platform. The longer that cycle persists, the harder it may become for competitors to challenge Nvidia solely by producing a faster or cheaper chip.

Global government bonds face further selling pressure as governments ramp up borrowing faster than traditional investors are willing or able to absorb it, renowned economist Mohamed El-Erian said Friday, warning that the resulting rise in yields represents a deeper imbalance than concerns over inflation or Federal Reserve credibility alone.

“I don’t see any appetite in the U.S. for immediate fiscal consolidation. So I suspect we will continue to see upward pressures on yields,” El-Erian told CNBC’s Carolin Roth at the Ambrosetti Forum in Cernobbio, Italy.

Government bond markets have suffered a sharp sell-off this week, pushing yields on debt issued by several major economies to multidecade highs as investors reassessed the outlook for inflation, interest rates and public finances.

Bond prices move inversely to yields, meaning the increase in yields has been accompanied by significant declines in government bond prices. The sell-off eased on Friday, with yields broadly steady across major developed markets. U.S. Treasury yields were marginally lower across the curve in early trading.

El-Erian, a professor at the University of Pennsylvania’s Wharton School and chief economic adviser at Allianz, said he did not see evidence of dysfunction in the bond market itself. Instead, he said that the market was adjusting to a structural shortage of dependable buyers relative to the amount of debt being issued.

“Reliable buyers and holders” of U.S. Treasurys are coming under pressure, he said.

“China, for geopolitical purposes, is no longer as willing,” El-Erian said. “Japan and the Gulf countries have domestic issues.”

He also cited the possibility that Norway’s sovereign wealth fund could reconsider its allocation to U.S. government bonds.

“The size isn’t big, but the signal that traditional holders and buyers are becoming less reliable is a very important one,” he said.

El-Erian said the problem was becoming more pronounced because debt supply was expanding well beyond traditional government issuance.

“If you look at the amount of issuance that’s coming from governments, from hyperscalers, from companies, it far exceeds what you can count on in terms of reliable buyers,” he said.

“And that’s why there’s been pressure on interest rates. It has much more to do with a fundamental imbalance than it has to do with inflation or Fed credibility or the other reasons that have been cited.”

U.K., Japan and France Face Particular Risks

El-Erian identified the U.K., Japan and France as the three G7 economies most exposed to sovereign-debt pressures.

The U.K. is particularly vulnerable to swings in global borrowing costs, he said, describing it as a “high-beta country.”

“That every time rates move by a bit in the U.S., they move by a lot more in the U.K.,” he said.

The shift in investor attention toward France is also significant for European markets.

“In the old days you would worry about Italy. Italy is trading inside France, and the focus now is on one of the two countries at the core of the eurozone, not at the periphery of the eurozone,” El-Erian said.

“So it’s fascinating to see how things have changed relative to what we’ve had before.”

France has become a focal point for investors concerned about European fiscal sustainability, highlighting how sovereign-debt risks have moved beyond the eurozone’s traditional peripheral economies.

The development matters because higher borrowing costs can feed directly into government finances, particularly for countries already carrying high debt burdens. If investors demand progressively larger risk premiums, governments can face rising debt-service costs even without a sharp deterioration in underlying economic conditions.

El-Erian Criticizes Treasury Intervention

El-Erian also criticized the Trump administration’s attempts to influence financial-market outcomes and monetary policy, saying the U.S. Treasury had gone “too far.”

The Treasury announced last month that it would at least double the size of its purchases of long-dated Treasury securities after long-term borrowing costs climbed to multidecade highs.

Vice President JD Vance on Thursday renewed pressure on the Federal Reserve to cut interest rates, adding to repeated calls from the administration for lower borrowing costs.

El-Erian described the moves as “unfortunate.”

“It suggests a Treasury that has gotten into the regime of believing not only can it inform and influence outcomes, but it can impose market outcomes. I think that’s a step too far,” he said.

“And the question now is, how do you step back from this? I think the results are clear. It’s a massive market. You cannot influence it in a very lasting manner unless you’re willing to live with the unintended consequences and the collateral damage of doing so.”

The comments highlight a fundamental constraint facing policymakers: the U.S. Treasury can influence the composition and timing of government debt issuance and conduct buybacks, but the scale of the Treasury market makes sustained control over borrowing costs difficult without potentially creating distortions elsewhere in financial markets.

Political Pressure Complicates Fed Outlook

El-Erian said Fed Chair Kevin Warsh, who succeeded Jerome Powell in May after being selected by President Donald Trump, would “hear” calls from Vance and other administration officials for lower interest rates.

But he said the more important question was what political pressure for lower borrowing costs meant for the Treasury, particularly because of the effect of interest rates on the mortgage market.

“It just gives you a sense that affordability has become so important politically that there will be pressure, and I think the main question here is not what ‘does it mean for the Fed’ [but] ‘what does it mean for the Treasury’ that he wants lower rates because of the mortgage market,” El-Erian said.

Markets were pricing in roughly an even chance of the Federal Open Market Committee either raising rates or leaving them unchanged at its September meeting, according to the CME’s FedWatch tool.

That unusually divided outlook adds another source of uncertainty to bond markets already wrestling with heavy issuance, fiscal concerns and shifting expectations for inflation.

El-Erian nevertheless said Warsh had handled his address at the Jackson Hole economic symposium particularly well, identifying three aspects of the speech that he considered important.

“First, he addressed the concerns about his reaction function,” El-Erian said.

He also praised Warsh for warning against excessive reliance on forward guidance, which he described as creating a “hall of mirror phenomenon.”

“Forward guidance had gone too far,” El-Erian said.

His third point, which he said received the least attention but was potentially the most important, was Warsh’s characterization of artificial intelligence as a potential factor of production.

“And then the third thing he did, which captured the least attention, but I think is the most important one, is he characterized AI as a potential factor of production, meaning it can have a huge impact on the supply side,” El-Erian said.

“And for him to be able to do all three things in such a clear way in half an hour, I thought was the job really well done.”

The comments point to a more complicated monetary-policy outlook than simply whether inflation is moving higher or lower. If AI substantially increases productivity and expands the economy’s productive capacity, it could eventually alter the relationship between economic growth, inflation and interest rates.

For bond investors, however, the immediate problem remains the sheer volume of debt competing for capital. Unless fiscal consolidation reduces supply or a new group of large buyers emerges, El-Erian’s warning suggests that elevated long-term yields could persist even if inflation pressures moderate. That would keep borrowing costs high across economies and increase the sensitivity of equities, credit markets and currencies to every change in fiscal policy and central-bank expectations.