Saudi Aramco has resumed crude loadings at its Ras Tanura terminal in the Gulf on Friday, marking a symbolic and practical return to normal operations after nearly four months of disruption caused by the Iran war, according to shipping data.

The restart comes as the world’s largest oil exporter joins a broader regional rush to move cargoes, driven by cautious optimism that the U.S.-Iran ceasefire framework will hold and allow the Strait of Hormuz to fully reopen.

Two Very Large Crude Carriers (VLCCs) operated by Saudi’s shipping arm Bahri were actively loading at the terminal, with another waiting nearby. Each VLCC can carry up to 2 million barrels, signaling a significant step toward restoring pre-war export levels.

Ras Tanura, the world’s biggest oil port, once exported more than 5 million barrels per day (bpd) before the conflict. It also hosts a 550,000 bpd refinery that was shut as a precaution during the war. The terminal’s reactivation is critical not just for Saudi Arabia but for global oil markets, as the kingdom had diverted much of its output to the Red Sea port of Yanbu after Iranian forces effectively blockaded the strait.

Aramco last loaded a cargo from Ras Tanura for China on March 8. In the intervening months, Saudi crude exports slumped to around 4 million bpd from more than 7 million bpd in February, contributing to one of the most severe supply disruptions in recent history.

The resumption occurs against a backdrop of persistent uncertainty. A ship operated by Taiwan’s Evergreen Marine was struck by an unknown object in the Strait of Hormuz on Thursday, prompting the British navy’s UKMTO to pause escort operations. Two U.S. officials attributed the incident to Iranian forces, while Iran’s Persian Gulf Strait Authority warned that vessels straying from approved routes would not be guaranteed safe passage.

Despite these tensions, oil flows through the strait have begun to recover, reaching their highest levels since the conflict erupted. Middle Eastern producers have been ramping up output and exports in anticipation of normalized shipping lanes. Iraq’s SOMO and Qatar issued new crude tenders this week, following similar moves by Kuwait and the UAE. Iran, too, is accelerating exports after Washington temporarily eased sanctions.

This surge in supply is already weighing on prices. Brent crude fell more than $1 a barrel on Friday, slipping below $76 for the first time since early March. Physical market differentials have normalized toward pre-war levels, reflecting improved availability.

Rystad Energy’s MENA research director Aditya Saraswat noted the rapid pace of recovery.

“Two million barrels a day came back online in three weeks, and the recovery is spread across the region,” Saraswat said.

The consultancy estimates shut-in production across the Gulf has dropped to 9.6 million bpd in mid-June from 11.7 million bpd just three weeks earlier, forecasting a full regional supply recovery by the end of the year.

For Saudi Arabia, the restart is both a commercial necessity and a geopolitical signal. As the de facto leader of OPEC+, Riyadh has a vested interest in stabilizing markets after months of elevated prices that risked damaging global demand. At the same time, the kingdom is positioning itself to regain market share lost during the blockade, particularly in Asia, its largest customer base.

Aramco is expected to cut its official selling prices for August sharply next week as competition among producers intensifies. This price discipline will be crucial in preventing a supply glut from derailing the fragile ceasefire.

The broader oil market is transitioning from a period of acute shortage fears to one of potential oversupply concerns. While the ceasefire roadmap provides a 60-day window for negotiations, any breakdown could quickly reverse recent gains. Investors remain wary, with prices still elevated compared to pre-war levels but well off their peaks.

The reopening also comes with significant implications for global energy security. Economists have noted that a sustained return to normal flows through the Strait of Hormuz, which handled a fifth of the world’s oil and LNG before the conflict, would ease inflationary pressures on energy-importing economies and provide breathing room for central banks navigating sticky inflation.

The resumption at Ras Tanura underscores how quickly energy markets can pivot when diplomatic progress occurs, but it also highlights the vulnerability of global supply chains to regional conflicts. While Saudi Arabia’s ability to redirect exports to Yanbu during the blockade demonstrated operational resilience, the preference for Gulf terminals like Ras Tanura remains clear due to lower costs and logistics efficiency.

China’s onshore technology listings are on track for their strongest year since 2023, driven by a deliberate push from Beijing to nurture homegrown chipmakers, artificial intelligence companies, and other strategic tech firms as the country seeks greater self-reliance in its intensifying rivalry with the United States.

Technology companies have already raised $3.1 billion through stock market listings in China this year as of June 18 — more than five times the amount raised in the same period last year, according to LSEG data. Nearly 50 companies, spanning robotics startups to semiconductor players, have filed for initial public offerings in Shanghai and Shenzhen, with combined fundraising plans totaling at least 126.1 billion yuan ($18.7 billion), based on Reuters calculations from regulatory filings.

One of the most anticipated debuts is memory-chip maker ChangXin Memory Technologies, which is planning a 29.5 billion yuan Shanghai IPO — the largest this year and a deal that would help push total tech listing proceeds to a three-year high. The momentum marks a sharp reversal from the listing drought that gripped China’s domestic markets in 2024, when many firms instead rushed to Hong Kong to tap offshore capital.

The revival is no accident. On June 17, Chinese regulators signaled strong support for listings of startups in “future industries” such as quantum technology, nuclear fusion, and brain-computer interfaces. The Shanghai Stock Exchange has also introduced new rules to streamline public share sales by large-language-model companies on its STAR Market, part of a broader effort to champion domestic AI development.

“The acceleration of technology IPOs has provided long-awaited exit opportunities for private equity and venture capital funds that have backed these companies,” said Li He, co-head of law firm Davis Polk’s Asia (ex-Japan) practice.

Annual proceeds from tech listings in China fell to $2.7 billion in 2024 from $15.7 billion in 2023, before rebounding to $3.6 billion last year. In comparison, Chinese tech companies raised $6.6 billion in Hong Kong in 2025. The shift back onshore reflects both improved domestic market conditions and Beijing’s strategic preference for keeping critical technology firms under closer national oversight.

Policy Support Meets Strong Investor Appetite

The China Securities Regulatory Commission (CSRC) has gone further, saying it would support qualified Hong Kong-listed companies seeking secondary listings on the mainland. This could open the door for firms like Zhipu AI, which raised HK$4.35 billion ($555.2 million) in Hong Kong in January and is now targeting a 15-billion-yuan STAR Market listing. Baidu’s chip unit Kunlunxin, awaiting approval for a $2 billion Hong Kong float, is also planning a smaller domestic listing, according to a person familiar with the matter cited by Reuters.

Kenny Ng, a strategist at China Everbright Securities International, said such moves could significantly improve liquidity and broaden investor access.

“If companies from other regions listed in Hong Kong can be included in the future, it can provide investors with more diversified choices and bring better liquidity to the market.” Ng said.

Ho-Yin Lee, Asia-Pacific co-head of technology and communications at Citigroup, highlighted the appeal of mainland listings for Hong Kong-traded firms.

“They would get access to a deep pool of capital, funding to grow businesses and great domestic branding,” Lee said.

Recent debuts have shown robust demand. SJ Semiconductor has surged more than eightfold from its IPO price, while Semight Instruments has jumped nearly 28-fold, demonstrating strong investor appetite for quality tech names.

“The pickup in Chinese tech issuance is part of a broader global AI wave, with China and the U.S. the two markets that set the tone,” said James Wang, head of Asia ex-Japan equity capital markets at Goldman Sachs.

The surge in domestic listings aligns with Beijing’s long-term goal of reducing dependence on foreign technology amid escalating rivalry with Washington. Export controls on advanced chips and AI tools have accelerated China’s push for self-sufficiency, making domestic capital markets a vital channel for funding innovation in semiconductors, AI, robotics, and other strategic sectors.

For private equity and venture capital investors who poured money into Chinese tech over the past decade, the reopening of onshore IPO windows offers much-needed exit liquidity after years of limited options. This could encourage fresh capital deployment into emerging technologies that align with national priorities.

However, challenges remain. Geopolitical tensions continue to cast a shadow, with analysts noting that success will now depend on sustained investor confidence, regulatory predictability, and the ability of these companies to deliver commercial breakthroughs. The focus on “future industries” suggests Beijing is prioritizing sectors with both economic and strategic importance, potentially creating a more resilient domestic tech ecosystem over time.

Process efficiency is important, but a winning business model is even more critical. A company can become exceptionally efficient at doing the wrong thing. Ultimately, success depends on operating in a position where you can create and capture value. Largely, since the internet is unconstrained and largely unbounded, businesses must continually rethink and redesign their operating models.

Consider this example. In 2000, assembling the world’s top movie producers to create short-form videos for a digital platform would have seemed like a brilliant idea, something akin to Quibi. But by 2021, the rules had changed. In the internet age, owning demand and mastering discovery became more strategic than owning supply. Consequently, a model built around professionally produced content struggled.

A different model emerged. Build a platform where millions of people can create and upload videos, and let algorithms discover, rank, and distribute the best content to billions of users within seconds. That is the essence of TikTok’s success.

The lesson is clear: the most catalytic thing a leader can do today is to build and maintain a responsive business model. Markets, technologies, and consumer behaviors are changing too quickly for static strategies.

If you miss the business model, everything else eventually falls apart. The internet has fundamentally altered the mechanics of competition, and in this new era, adaptability is not optional, it is the foundation of enduring success.

Join me today to co-learn on the Grand Playbook of Business at Tekedia Mini-MBA

Sat, June 27 | 7pm-8.30pm WAT | The Grand Playbook of Business and Four Plays in Markets – Ndubuisi Ekekwe | Zoom link

Amazon has increased prices for several of its artificial intelligence cloud services, underscoring how persistent shortages of advanced memory chips are beginning to reshape the economics of AI infrastructure and raise costs across the technology industry.

The latest increase affects Amazon Web Services’ (AWS) EC2 Capacity Blocks for ML, a service that allows customers to reserve graphics processing unit (GPU) capacity in advance for AI training and inference workloads. Beginning in July, hourly prices for several server configurations will rise by approximately 20%, following an earlier **15% increase introduced in January.

The consecutive price hikes suggest that pressure on AI infrastructure costs is intensifying rather than easing, even as hyperscale cloud providers continue investing hundreds of billions of dollars in new data centers.

In announcing the changes, AWS said: “Amazon EC2 Capacity Blocks for ML reservation prices are updated periodically based on supply and demand.”

The move is enormous in weight because AWS is the world’s largest cloud computing provider, serving millions of developers, enterprises, startups, and government agencies. Many AI applications, enterprise software platforms, and consumer services depend on AWS infrastructure, meaning higher cloud costs could eventually be passed through to businesses and end users.

Unlike price increases for consumer electronics, such as smartphones or gaming consoles, higher cloud computing costs have the potential to ripple across the broader digital economy, increasing operating expenses for companies building AI products and potentially slowing adoption among smaller businesses with limited technology budgets.

While much attention has focused on breakthroughs in foundation models and software capabilities, the industry’s biggest bottlenecks are tied to physical infrastructure, particularly the supply of advanced semiconductors. At the center of those constraints is high-bandwidth memory (HBM), a specialized memory technology that sits alongside AI processors from companies such as Nvidia and AMD. HBM dramatically increases the speed at which GPUs can access data, making it essential for training and deploying today’s largest AI models.

However, production of HBM remains limited because manufacturing is highly complex and concentrated among a small number of suppliers, primarily Micron, SK Hynix, and Samsung Electronics. Demand from hyperscalers has far outpaced supply, driving up prices for AI servers and increasing the cost of expanding data center capacity.

Those supply constraints are now flowing directly into cloud pricing.

Industry-wide, similar trends are emerging. Apple recently increased prices on several products, citing sharply higher memory costs, while Microsoft raised Xbox prices. Elon Musk has also complained publicly about unprecedented increases in memory prices affecting AI infrastructure.

The implications extend well beyond individual hardware products. Cloud providers purchase thousands of AI servers equipped with advanced GPUs and HBM memory. As the cost of these systems rises, cloud operators face a choice between absorbing the higher expenses or passing them on to customers. Amazon’s latest pricing decision suggests that hyperscalers believe demand remains strong enough to support higher prices.

Peter Berezin, chief economist at BCA Research, argued that the industry’s biggest constraint is no longer software innovation but manufacturing capacity.

“As there is a limit to how much memory can be produced, then there is a limit to how many GPUs can be produced, which means that there’s a limit to how many data centers can be built,” Berezin wrote on X.

He added that the shortage gives large cloud providers unusual pricing power because customers have few alternatives when GPU capacity is scarce.

“While the memory shortage raises their costs, it also keeps the demand for compute above the available supply, which gives them greater pricing power over access to cloud computing,” Berezin said.

The pricing dynamics highlight how the AI boom is evolving. During the early phase of generative AI, competition centered on developing more capable foundation models. Increasingly, however, competitive advantage depends on securing access to scarce computing resources, advanced memory chips, and electricity needed to operate large-scale AI infrastructure.

Major cloud providers, including Amazon, Microsoft, Google, and Oracle, have collectively committed hundreds of billions of dollars to expanding AI data center capacity, yet supply continues to lag demand. That imbalance has enabled infrastructure providers to maintain premium pricing even as they incur higher capital expenditures.

The beneficiaries of this trend include memory manufacturers. Strong demand for HBM has propelled companies such as Micron and SK Hynix to record valuations, with investors betting that AI-driven demand will keep the memory market tight for years.

For enterprises building AI applications, however, the picture is more challenging. Higher cloud rental costs could increase the expense of training models, deploying AI agents, and running inference workloads, potentially slowing experimentation by startups while reinforcing the advantages enjoyed by larger technology companies with deeper financial resources.

Amazon’s latest increase, therefore, represents more than a routine pricing adjustment. Industry analysts see it as a sign of a growing reality in the AI economy: where the pace of innovation is becoming increasingly dependent on the availability of physical infrastructure, from advanced memory chips and GPUs to data centers and power, making compute capacity one of the industry’s most valuable and scarce resources.