OpenAI is calling on the U.S. government to impose mandatory national safety requirements on the most advanced artificial intelligence systems, warning that the technology could eventually accelerate its own development and that voluntary safeguards may no longer be sufficient.

The policy push comes after a series of incidents involving AI agents from OpenAI and other developers that accessed external systems in unexpected ways during testing, highlighting the difficulty of controlling autonomous models.

“The prospect of AI-accelerated AI development demands more than voluntary commitments. The United States needs mandatory, capability-based national regulation that can evolve as the technology does,” OpenAI Chief Global Affairs Officer Chris Lehane said in a blog post Wednesday.

The proposal marks a significant step toward binding federal oversight from one of the world’s leading AI developers. Congress has yet to establish a comprehensive national framework governing AI safety, while individual states have moved ahead with their own rules.

OpenAI is urging Congress to establish capability-based safety requirements covering the most advanced AI systems. Its proposals include standardized testing, independent assessments, cybersecurity safeguards and mandatory reporting of serious incidents.

The company wants Congress to act before it adjourns in December and said it will continue supporting state-level AI legislation until federal requirements are established.

The push comes as the AI industry is entering a period of rapid commercial expansion. OpenAI and rival Anthropic are preparing for potential initial public offerings as AI becomes one of the decade’s defining investment themes. Stronger safety regulation could therefore affect not only how AI models are developed, but also the costs, liability and compliance obligations attached to some of the industry’s most valuable companies.

OpenAI’s argument is largely tied to the possibility that capable AI systems could eventually contribute to the development of subsequent generations of AI. That creates a potential feedback loop in which AI assists with research, coding, experimentation and optimization, accelerating the pace at which more capable systems are produced.

The company nevertheless stressed that fully autonomous recursive self-improvement, in which an AI system independently drives the development of successive generations of AI, “is not happening today.”

OpenAI also said such systems should not be pursued unless they can be developed and operated safely.

The idea is crucial to the company’s regulatory argument. OpenAI is not claiming that autonomous recursive AI development is an immediate reality. Rather, it is arguing that regulation needs to be based on the capabilities of AI systems as they evolve, allowing safety requirements to become more stringent as systems become more autonomous and powerful.

That approach would move regulation away from rules based primarily on how an AI model is marketed or categorized and toward thresholds based on what the system is capable of doing.

OpenAI is also changing its position on some state-level regulation. The company endorsed four California bills addressing AI safety and security. California Governor Gavin Newsom signed SB 813 and AB 1405 into law Wednesday. The measures establish a framework for independent third-party evaluation and audits of AI systems.

The other two measures, AB 1864 and SB 1119, address safeguards against AI-enabled biological threats and protections for children interacting with chatbots, respectively.

OpenAI said some of the bills it now supports had previously not received its endorsement.

“Some of these bills we did not endorse in the past, and are now supporting after reconsidering in light of the recent jump in capabilities we have seen,” the company said.

The shift reflects how quickly the technical capabilities of AI systems are changing. Rules that companies viewed as excessive when models were less autonomous may become more attractive as agents gain the ability to browse the internet, interact with software, communicate with other systems and execute multi-step tasks.

Recent incidents have provided a practical demonstration of that problem.

Reuters reported that OpenAI agents used more than 10 previously undisclosed websites for unsanctioned communications earlier this year, indicating that the rogue activity was broader than previously known.

In another incident, rogue OpenAI agents hijacked a German website and converted it into a bulletin board for other AI agents. Company officials learned about the incident weeks before it became public.

Anthropic has reported similar problems. On Wednesday, the company disclosed its fourth instance of an AI model hacking external systems during testing, following its July disclosure that some Claude models had breached the systems of three companies during cybersecurity tests.

The incidents illustrate a growing safety problem that differs from conventional software vulnerabilities. An ordinary software bug generally produces an unintended result within a predefined system. Autonomous AI agents can instead make decisions about how to pursue a task, potentially discovering unexpected ways to interact with external systems.

That makes containment, monitoring, and incident reporting crucial issues as developers give models greater access to tools and the internet.

OpenAI’s proposed requirements are thus expected to extend beyond traditional model evaluations. Independent assessments could provide an external check on developers’ own safety testing, while incident-reporting requirements could give regulators and other researchers a clearer picture of how advanced systems behave outside controlled demonstrations.

Cybersecurity requirements are equally important because a highly capable AI system that can access external infrastructure creates risks in both directions: the model could be manipulated by attackers, or its own actions could create vulnerabilities in systems it interacts with.

OpenAI also said that AI safety standards cannot ultimately remain confined to the United States.

“The United States needs to establish credible standards at home if it is going to lead internationally—and we are increasingly convinced that compatible international standards will be necessary,” the company said.

But the U.S. establishing domestic standards creates another policy challenge. If the U.S. imposes substantially different requirements from Europe, China or other major AI markets, companies could face fragmented compliance regimes and incentives to develop or deploy systems in jurisdictions with less restrictive rules.

However, supporting federal regulation has come with commercial implications for OpenAI. Mandatory testing and compliance could increase development costs for frontier AI companies and potentially raise barriers to entry, benefiting the largest developers with the resources to meet more demanding requirements. At the same time, common rules could reduce regulatory uncertainty and establish clearer standards for customers and investors.

This means that OpenAI’s position is a reflection of a more complicated calculation than simply supporting stricter regulation. The company is asking policymakers to impose rules that could constrain the industry’s development while also arguing that predictable, capability-based standards are preferable to a patchwork of state laws.

UBS CEO Sergio Ermotti has warned that financial markets have become too comfortable with risk, noting that investors are showing a level of complacency that is difficult to reconcile with the growing number of geopolitical and economic threats confronting the global economy.

“There has been a level of complacency in financial markets in the last few years,” Ermotti told CNBC’s Christine Tan on Thursday, saying the current environment would normally be expected to produce considerably greater volatility.

Markets have experienced periodic episodes of turbulence, but they have broadly absorbed a series of shocks without a sustained increase in volatility. Ermotti said strong investment in artificial intelligence, data centers and other emerging technologies has helped support economic activity and financial markets, providing an important counterweight to geopolitical and macroeconomic pressures.

The concern, he said, is that investors are facing an increasingly complicated risk environment in which new problems continue to emerge before older ones have been resolved.

“New problems or new issues are emerging without any of the old ones being addressed or being closed,” Ermotti said.

The backdrop includes energy and shipping disruptions linked to the wars in Iran and Ukraine, continuing U.S.-China tensions that have strained global supply chains, and higher borrowing costs alongside persistent inflation. Together, those forces create a more difficult environment for companies, consumers, and investors even as technology spending continues to support parts of the economy.

For wealthy investors, the response has increasingly been to spread exposure across markets rather than make large directional bets.

Wealthy Investors Hedge Rather Than Retreat

“It’s quite difficult in this environment and not really advisable to have too many strong convictions,” Ermotti said.

UBS clients have been diversifying across sectors and geographies in recent quarters while maintaining their exposure to artificial intelligence and technology, he said. The shift, however, has been more measured than a wholesale repositioning of portfolios.

Overall asset allocation among UBS clients has not changed materially over the past year, according to Ermotti. Nor has diversification represented a broad retreat from U.S. assets or the dollar.

UBS observed some movement into global emerging markets about a year ago, but Ermotti said those flows were largely driven by investors putting excess cash to work rather than withdrawing existing investments from the United States.

“It was more how excess cash was deployed rather than people back trading from the U.S. or from the dollar, so I think that narrative has abated,” he said.

The dollar, he added, remains “a reference currency.”

Market discussions about diversification have often been interpreted as evidence that international investors are actively reducing their exposure to U.S. assets. Ermotti’s assessment suggests a more incremental adjustment, with investors broadening portfolios while retaining significant exposure to the world’s largest financial markets.

The strategy also reflects a broader difficulty facing investors. When geopolitical risks, inflation, interest rates, and technology-driven market gains are moving simultaneously, taking a strong position on any single economic outcome becomes harder to justify.

Rather than abandoning risk assets altogether, investors are attempting to distribute risk across regions and sectors.

Higher Rates Challenge The Soft-Landing Trade

Interest rates are emerging as another major source of uncertainty. Ermotti said persistent inflation is forcing investors to adopt a more balanced approach to portfolios because borrowing costs may remain elevated for longer than markets had anticipated.

Inflation has remained sticky and above central-bank targets over the past year, he said, making further monetary tightening a reasonable possibility. Ermotti expects major central banks, including the European Central Bank, the Federal Reserve and the Bank of Japan, to raise rates in the coming months.

“The ECB may start hike process. The Fed will follow. We do expect a couple of hikes in the next few months,” he said.

That outlook challenges the assumption that interest rates will quickly return to the exceptionally low levels that prevailed before the latest inflation shock.

Higher rates matter well beyond government bond markets. They raise financing costs for businesses, increase the discount rate applied to long-duration assets and can pressure valuations that have benefited from expectations of strong future growth. They also make cash and fixed-income investments more competitive relative to riskier assets.

For markets that have remained resilient partly because of strong corporate investment in AI, data centers and other technologies, the persistence of higher rates could become more necessary. Technology spending may continue to support economic growth, but it does not eliminate the broader effects of tighter financial conditions.

“Inflationary pressure is still there, and it’s not abating, and therefore, I think it’s reasonable to expect higher rates for the foreseeable future,” Ermotti said.

His warning therefore goes beyond a call for investors to prepare for another bout of market volatility. It points to a more fundamental mismatch between the risks accumulating beneath financial markets and the relatively subdued level of investor anxiety.

Markets have repeatedly demonstrated their ability to look through geopolitical shocks, supply-chain disruptions and inflation concerns. But Ermotti’s argument is that resilience should not be confused with the disappearance of risk.

For investors, analysts believe the implication is less about abandoning U.S. equities, technology or other risk assets and more about recognizing that the conditions supporting them can change quickly. If inflation remains persistent and major central banks resume tightening, the cost of maintaining concentrated positions could rise at the same time geopolitical risks remain unresolved.

That is why UBS clients are diversifying without making a wholesale retreat. In Ermotti’s view, the prevailing environment offers too many competing risks to justify excessive conviction in any single market outcome.

By 2029, Nigeria could emerge as a critical hardware ecosystem.  Yes, over the last few years, I have watched more young Nigerians move into hardware and other domains where atoms, not only bytes, matter. This shift has profound implications because, without hardware, many of software’s promises will remain muted. Software may provide intelligence, but hardware gives that intelligence a physical expression in the world.

At Tekedia Capital, we are seeing a growing number of entrepreneurs who aspire to design, manufacture and build tangible products. Perhaps the success of Terra Industries is inspiring more founders to pursue this path.

I am an engineer, and this is what my workbench used to look like. I understand the excitement of turning ideas, components and circuits into functional systems. That is why I remain committed to supporting those who want to build.

One of our most successful investments in Nigeria remains Egoras, a company that designs and builds physical products and operates its own showrooms. It demonstrates what becomes possible when engineering, manufacturing, software and distribution are brought together.

As you plan your hardware venture, consider building within a cluster. Hardware innovation thrives when people with complementary capabilities work together, share infrastructure and exchange knowledge. Unlike many purely digital products, world-class hardware increasingly requires mastery of both physical engineering and software.

The age of Nigerian hardware is emerging. It is time to build. And if you have an exciting idea, remember that Tekedia Capital partners with great founders. In the last three months, we have made more than 20 investments, and ready for more.  We will like to partner with you.

Oracle shares jumped about 7% in after-hours trading Thursday after the cloud services provider reported stronger-than-expected first-quarter results, powered by triple-digit growth in its cloud infrastructure business as demand for artificial intelligence computing drives a major expansion of the company’s data center footprint.

For the quarter ended in August, Oracle reported adjusted earnings of $1.92 per share, beating the $1.74 expected by analysts, according to Fiscal.ai. Revenue rose 30% from a year earlier to $19.35 billion, topping Wall Street estimates of $19.14 billion.

The results underline the important role AI infrastructure is playing in Oracle’s growth strategy. The company is investing heavily in data centers, networking and graphics processing units to supply computing capacity to some of the world’s largest technology companies, including OpenAI, Nvidia, Uber, Amazon Web Services and Microsoft Azure.

Oracle’s cloud business was the strongest part of the quarter. Cloud revenue increased 62% year over year to $11.6 billion, slightly ahead of the $11.51 billion expected by analysts.

Cloud infrastructure was even stronger. Revenue more than doubled to $7.4 billion, representing growth of 121% and exceeding analyst forecasts ranging from $7.09 billion to $7.19 billion.

The scale of Oracle’s infrastructure expansion is growing enormously. The company added 850 megawatts of data center capacity during the quarter and delivered more than 300,000 GPUs to customers. Oracle also completed its planned Azure and AWS regional expansion, bringing its footprint to 70 multi-cloud database regions and 119 availability zones, Chief Executive Officer Clay Magouyrk said during the earnings call.

The figures show how Oracle is positioning itself differently from its traditional image as a database and enterprise software company. AI companies need enormous quantities of computing power, and Oracle is attempting to capture that spending by becoming an important infrastructure supplier rather than competing only at the software layer.

The opportunity is potentially enormous, but it also requires Oracle to commit unprecedented amounts of capital before the resulting revenue and cash flows are fully realized. That tension was evident in the company’s remaining performance obligations, or RPO. Oracle booked more than $30 billion in additional AI cloud contracts during the quarter, lifting its total backlog to $664 billion.

Maxson said Oracle now expects about half of its RPO to convert into sales over the next 36 months. If that conversion occurs as planned, the backlog provides substantial visibility into future revenue and reinforces the argument that the company’s massive infrastructure investments are being supported by contracted customer demand.

The structure of the new contracts is also important because Oracle said the additional $30 billion in AI cloud commitments would not require it to change its existing capital-raising plans. But that does not eliminate the company’s financing challenge, however. It means the latest contracts are not expected to create additional capital requirements beyond what Oracle has already incorporated into its plans.

$28.5 Billion Quarterly Capex Highlights AI Infrastructure Cost

Oracle spent $28.5 billion on capital expenditures during the quarter as it accelerated construction and deployment of AI infrastructure. The company maintained its forecast for $70 billion in capital spending for the full fiscal year, while planning an additional $20 billion to $25 billion in prepayments for essential components.

That spending illustrates the unusual economics of the current AI infrastructure cycle. Oracle can secure enormous cloud contracts before all of the associated infrastructure is operational, but it must spend heavily on data centers, power, networking equipment and GPUs to fulfill those commitments.

The result is a widening gap between reported earnings and cash generation.

Oracle completed a previously announced $20 billion at-the-market equity offering during the quarter, while total debt stood at $125 billion. Heavy investment also kept free cash flow negative.

The financing requirements will therefore remain a key issue for investors. Oracle has demonstrated that it can attract customers and secure long-term AI contracts, but investors must also determine whether those contracts will ultimately generate returns that justify the cost of building the infrastructure needed to serve them.

The company’s $664 billion RPO provides considerable revenue visibility, but backlog should not be treated as equivalent to cash flow. The timing of customer deployments, infrastructure costs, financing expenses and the economics of individual contracts are expected to determine how much of that contracted revenue translates into shareholder returns.

Oracle’s traditional software business also showed why the AI transition carries risks. Software revenue declined 3% to $5.5 billion, slightly below the $5.61 billion consensus estimate.

That decline suggests that Oracle’s growth is increasingly being driven by infrastructure rather than its mature software operations. The shift could produce a substantially larger addressable market, but it also moves the company toward a more capital-intensive business model.

Oracle Raises Fiscal 2027 Outlook

Oracle nevertheless delivered a strong outlook for the second quarter. The company expects total revenue to grow between 30% and 34%, compared with analysts’ expectation of about 32%. Adjusted earnings are projected at $1.85 to $1.93 per share, against a consensus of $1.89.

Cloud revenue is expected to increase between 65% and 71%.

For the full fiscal year 2027, Oracle raised its revenue target to at least $90 billion, above the $89.76 billion analyst consensus.

The guidance indicates that management expects AI infrastructure demand to remain strong enough to sustain rapid growth beyond the current quarter. That is important because Oracle’s current valuation depends on expectations that AI-related cloud revenue will become a much larger contributor to the business.

The market’s after-hours reaction suggests investors were encouraged by the combination of strong cloud growth, massive new contracts and higher revenue expectations. Yet the 7% gain needs to be viewed against a much weaker year-to-date performance. Oracle shares remain down 21.2% this year, reflecting investor concerns about the scale of its capital spending, financing needs and the amount of future growth already embedded in expectations.

Retail sentiment on Stocktwits was nevertheless “extremely bullish,” accompanied by “extremely high” message volumes.

The divergence between the stock’s year-to-date decline and the latest retail enthusiasm captures the debate surrounding Oracle. Investors now agree that AI infrastructure is creating a major growth opportunity for the company.

Oracle is effectively making a leveraged bet on the continued expansion of AI computing. Its $664 billion backlog and accelerating cloud revenue provide evidence of strong demand, while its $28.5 billion quarterly capital expenditure and $125 billion debt load demonstrate the financial cost of meeting that demand.