Siemens AG’s CEO Roland Busch said Monday that the ongoing U.S.-Israeli war with Iran is causing customers to delay or cancel new industrial projects as prices for raw materials and energy climb sharply.

The conflict, now in its fourth week, has severely restricted shipping through the Strait of Hormuz, the critical chokepoint handling roughly 20% of global seaborne oil and a similar share of liquefied natural gas, and damaged major energy facilities across the Gulf.

“Growth is throttled because of price increases,” Busch told reporters on the sidelines of Siemens’ annual Tech Summit in Beijing. “You see customers holding back their investments. For example, oil and gas customers or petroleum customers who were planning maybe a new plant… so it means investments are slowing down.”

Brent crude futures have risen 56% since the conflict began, pushing energy and feedstock costs higher across manufacturing sectors. Busch’s comments reflect a broader concern among industrial companies that prolonged supply disruptions and elevated prices could dampen capital spending well into 2026 and beyond.

The remarks came during an event where Siemens announced an expansion of its industrial AI partnership with Alibaba Cloud. The two companies will roll out 26 new services covering industrial infrastructure, automation, and AI-powered applications for Alibaba’s cloud customers.

Despite the deepening collaboration, Busch acknowledged persistent challenges in obtaining real-world factory data from Chinese partners due to intellectual property concerns.

“Most of our foundational models, they are so far trained on publicly available data, they haven’t seen industrial data yet,” he said. “This is a big step up to tune models.”

He added that Chinese regulations now permit industrial and machine data to cross borders under certain conditions, creating a pathway for more effective model training.

Busch also revealed that Siemens developers increasingly prefer Chinese open-source large language models, particularly those from Alibaba’s Qwen family and DeepSeek, over closed-source U.S. rivals for certain industrial AI tasks. The primary reasons are lower token costs and greater flexibility in customizing parameters.

OpenRouter’s public token-usage leaderboard shows that six of the top ten most widely used large language models worldwide are now Chinese. Industry estimates suggest around 80% of U.S. AI startups currently rely on Chinese open-source models for development work. Some Western think tanks have raised concerns about security risks and potential political bias embedded in these models, given their training data and origins.

The Siemens-Alibaba announcement underlines Europe’s deepening reliance on Chinese AI infrastructure as U.S. export controls limit access to advanced semiconductors and high-end compute. At the same time, Busch’s caution about investment slowdowns highlights how the Middle East conflict is rippling through global supply chains, raising input costs and clouding the outlook for industrial spending in 2026.

Siemens, like many European manufacturers, has been navigating higher energy prices and supply-chain disruptions since the Russia-Ukraine war began in 2022. The Iran conflict adds a fresh challenge, particularly for energy-intensive sectors such as chemicals, metals, and heavy machinery — all core to Siemens’ industrial automation and digitalization business.

The company’s assertion implies that while partnerships with Chinese tech giants offer access to low-cost AI tools and massive market potential, geopolitical risks and data-sharing restrictions continue to complicate the picture.

This means the path forward for Siemens involves balancing these relationships with efforts to secure reliable energy supplies and protect intellectual property in an increasingly fragmented global technology industry.

Like several other business leaders, Busch is warning that the conflict in the Middle East is no longer a distant headline: it is actively reshaping investment decisions across industrial Europe.

The race to dominate artificial intelligence is beginning to collide with a more fundamental constraint: power. As data centers expand and computing loads surge, the question is shifting from how fast AI can scale to whether the energy system can keep up.

That tension is now drawing some of the industry’s most ambitious bets into view.

At the center is Helion, which is in early discussions to supply electricity to OpenAI in what could become one of the most consequential energy deals tied to the AI boom. The outline, reported by Axios, suggests OpenAI could secure 12.5% of Helion’s future output—about 5 gigawatts by 2030 and 50 gigawatts by 2035.

Those figures are striking not just for their size, but for what they imply. Helion has said each of its reactors would generate roughly 50 megawatts. Meeting the proposed demand would require the company to build about 800 reactors within five years and more than 7,000 additional units over the following half decade. For an industry that has yet to deliver a single commercial fusion plant, the scale borders on an industrial moonshot.

This implies that AI companies are no longer content to rely on utilities and existing grids. They are moving to secure dedicated power sources, often years in advance, and increasingly from unconventional suppliers. Microsoft, OpenAI’s key partner, signed a separate agreement with Helion in 2023 for electricity deliveries beginning in 2028, effectively underwriting the company’s first commercial ambitions.

The common thread in these moves is urgency. Training large AI models and running inference at scale require vast amounts of electricity, and that demand is rising faster than grid expansion in many regions. Securing power is becoming a strategic priority, on par with access to chips and data.

Helion’s approach sets it apart from much of the fusion field. Most developers are pursuing designs that convert fusion-generated heat into steam to drive turbines. Helion is attempting direct conversion, using magnetic fields to compress plasma until fusion occurs, with the resulting energy fed back into the system to generate electricity. The design promises higher efficiency and fewer moving parts, but it also carries unproven engineering risks.

Progress has been incremental. The company’s Polaris prototype has reached plasma temperatures of 150 million degrees Celsius, nearing the 200 million threshold it believes is necessary for sustained fusion reactions. That remains a technical milestone rather than a commercial one. Bridging the gap between experimental conditions and reliable, grid-scale output has eluded the industry for decades.

Even if the physics holds, the manufacturing challenge looms just as large. Producing thousands of reactors would require a supply chain that does not yet exist, along with regulatory approvals and capital commitments on a scale rarely seen outside conventional energy megaprojects. Helion raised $425 million last year from investors including Sam Altman, Mithril, Lightspeed, and SoftBank, but that sum would cover only a fraction of the cost implied by mass deployment.

Altman’s role ties the narrative together because he has backed Helion while leading OpenAI’s expansion, and though he has stepped away from formal decision-making in the discussions, the overlap highlights how closely the future of AI is becoming linked to the future of energy. His earlier move to step down as chair of Oklo, another advanced energy company exploring partnerships with AI firms, points in the same direction.

There is also a competitive dimension. If Helion succeeds, it could leapfrog other fusion developers targeting the early 2030s for commercial deployment. Securing anchor customers such as OpenAI and Microsoft would give it both financial backing and a guaranteed market—two factors that have historically been missing in fusion’s long development cycle.

However, the timelines assume rapid technical validation, regulatory clearance, and industrial scaling, all within a decade. Any delay in one area could cascade across the entire plan. For OpenAI, the arrangement would secure long-term energy supply, but it would also tie part of its infrastructure to a technology that has yet to prove itself outside the lab.

What is clear so far is that the relationship between computing and energy is tightening. The expansion of AI is beginning to reshape power markets, drawing capital toward new generation technologies and accelerating timelines that once seemed distant.

Fusion, long treated as a distant prospect, is being pulled forward by that demand.

Grab Holdings Limited announced Monday that it has agreed to purchase Delivery Hero’s Foodpanda business in Taiwan for $600 million in cash, subject to regulatory approval.

The transaction is Grab’s first major step beyond its traditional Southeast Asian footprint and positions the Singapore-based ride-hailing and delivery platform as a dominant player in one of Asia’s most mature food-delivery markets.

The deal is expected to close in the second half of 2026. Grab aims to complete the full migration of users, merchants, and driver-partners to its platform by early 2027. Once integrated, Grab will operate in 21 cities across Taiwan, combining its AI-powered logistics and operational expertise with Foodpanda’s established local network.

Anthony Tan, Grab’s Group CEO and co-founder, emphasized the strategic fit, saying: “This is a natural next step for Grab, as our experience in Southeast Asia is a direct fit for this market. Our longstanding expertise in managing complex delivery logistics for dense and high-traffic cities is well-suited for Taiwan’s bustling cities. Taiwan’s population of approximately 23 million also has a high demand for mobile-first services, similar to the Southeast Asian consumers who Grab serves every day. We see a significant opportunity to grow the food and groceries delivery scene here.”

Foodpanda’s Taiwan operations generated approximately $1.8 billion in gross merchandise value (GMV) in recent periods, according to Delivery Hero disclosures. The business has maintained a leading position in the market, with reports from 2022–2023 showing Foodpanda holding roughly 52% share and Uber Eats controlling 48%.

The acquisition follows Uber’s failed attempt to buy Foodpanda’s Taiwan business in March 2025. Taiwan’s Fair Trade Commission blocked that deal, citing competition concerns. A combined Uber Eats–Foodpanda entity would have controlled nearly 90% of the market, raising risks of reduced competition and higher prices for consumers.

Grab’s entry presents a different competitive picture. The company would inherit Foodpanda’s roughly 52% market share, giving it a strong but not monopolistic position against Uber Eats. Analysts view the structure as more likely to pass antitrust review, as it would preserve a two-player market rather than consolidate it under one operator.

The deal arrives at a pivotal moment for Grab, which has been expanding its delivery and financial services businesses across Southeast Asia while navigating rising competition from regional players and global giants entering the market. Taiwan offers a high-density, tech-savvy consumer base with strong demand for on-demand services — characteristics that closely match Grab’s core markets in Indonesia, Vietnam, Thailand, and the Philippines.

Taiwan’s food-delivery sector has matured rapidly since the pandemic, with high smartphone penetration, dense urban populations, and widespread use of mobile payments. The market has also shown resilience despite economic headwinds, making it an attractive entry point for Grab as it seeks to diversify revenue beyond Southeast Asia.

The transaction also underscores the shifting dynamics of the global food-delivery industry. Delivery Hero, which has been under pressure to reduce debt and refocus on core markets, has been shedding non-strategic assets. Selling its Taiwan business allows the Berlin-based company to streamline operations while providing Grab with a ready-made platform to establish a foothold in East Asia.

But regulatory approval will be the key hurdle. Taiwan’s Fair Trade Commission will scrutinize the deal for potential impacts on competition, pricing, and consumer choice. Grab’s position as a new entrant rather than an incumbent consolidator could improve its chances of clearance compared with Uber’s blocked bid.

For consumers and merchants in Taiwan, the transition could bring more robust platform features, including Grab’s AI-driven route optimization, dynamic pricing, and integrated financial services. The shift to Grab’s ecosystem is also expected to offer driver-partners access to a broader range of earning opportunities across ride-hailing and delivery.

If the deal closes on schedule and integration proceeds smoothly, Taiwan could become a proving ground for Grab’s ability to scale outside its home markets.