OpenAI’s long-anticipated move into consumer hardware is no longer just an experiment in design or form factor. It is emerging as a strategic response to a harder reality facing the company: how to convert unprecedented scale and investor confidence into durable, long-term profit.

After months of speculation following its acquisition of Jony Ive’s startup, io, the AI company has now confirmed that its first hardware device is on track for release in the second half of the year. The confirmation came from OpenAI’s Chief Global Affairs Officer, Chris Lehane, speaking at an Axios-hosted panel at the World Economic Forum in Davos. While details remain scarce, the timing and context of the announcement point to a broader commercial recalibration underway inside the company.

OpenAI today sits at the center of the generative AI boom, backed by tens of billions of dollars in investment and partnerships, most notably with Microsoft. ChatGPT alone is approaching a billion weekly users, a level of reach that rivals the world’s largest consumer platforms. Yet that scale comes at a steep cost. Training and running large language models requires enormous capital outlay for data centers, specialized chips, and energy. Even with paid subscriptions and enterprise deals, the company remains under pressure to diversify revenue streams beyond software access fees.

Hardware offers one such path. By building its own device, OpenAI can reduce reliance on third-party platforms like Apple’s iOS or Google’s Android, where distribution is mediated through app stores and operating system rules. More importantly, a proprietary device creates room for tighter integration between AI models and the physical world, opening up new categories of paid services, upgrades, and long-term user lock-in.

Hints from OpenAI leadership suggest the company is aiming for something deliberately different from the smartphone. Sam Altman has described the upcoming product as more “peaceful and calm” than the iPhone, language that aligns with earlier reporting pointing to a screen-free, pocketable device. The underlying idea appears to be an AI companion that fades into the background, accessible through voice or subtle interactions rather than constant visual engagement.

Industry reporting from Asia has added further color. Multiple outlets suggest OpenAI’s first device may take the form of AI-powered earbuds, internally codenamed “Sweet Pea”. These earbuds are reported to use a custom 2-nanometre processor, enabling certain AI tasks to be handled directly on the device rather than routed to the cloud. If accurate, this would lower operating costs over time, reduce latency, and address growing concerns around data privacy, all while easing pressure on OpenAI’s server infrastructure.

Manufacturing plans underline the scale of ambition. Reports indicate that OpenAI has explored partnerships with Luxshare, a major assembler of Apple products, and is also weighing Taiwan’s Foxconn as a long-term manufacturing partner. Initial shipment targets of 40 to 50 million units in the first year, if realized, would place OpenAI instantly among the largest players in the global wearables market. Such volumes also suggest that the company is thinking well beyond a niche developer device and aiming squarely at mass adoption.

The commercial logic is that hardware allows OpenAI to capture value at multiple points: device sales, premium AI features, subscriptions bundled with hardware, and potentially a marketplace for AI-driven services built specifically for its ecosystem. In an environment where investors are increasingly focused on revenue clarity and cost discipline, owning both the software and the hardware stack offers a more predictable path to monetization.

However, consumer hardware is a brutally competitive arena, and earbuds in particular are already dominated by incumbents with deep integration into operating systems and existing user habits. Convincing users to replace or supplement devices like AirPods will require seamless cross-platform compatibility and a compelling reason to switch, beyond novelty.

The wider track record of AI-first devices offers cautionary lessons. High-profile launches over the past year have struggled to translate hype into sustained usage. Humane’s AI Pin was eventually sold to HP. Rabbit’s handheld assistant has yet to break into the mainstream. Other AI wearables have faced swift backlash over unclear value propositions.

These outcomes have sharpened investor scrutiny around whether AI hardware can move beyond concept appeal to everyday utility.

At the same time, momentum is building elsewhere. Meta’s Ray-Ban smart glasses are steadily improving, blending AI features into a familiar product category and seeing strong consumer demand. Amazon’s recent acquisition of Bee, an AI meeting recorder, signals interest in ambient assistants that live alongside users rather than compete for attention.

OpenAI’s hardware effort sits at the intersection of these trends. It is a bet that the company’s unmatched AI capabilities, combined with design leadership and manufacturing scale, can succeed where others have faltered. More than that, it is a bet driven by financial necessity.

With vast investment to justify and operating costs that continue to rise, OpenAI’s push into hardware is less about curiosity and more about control: control over distribution, over user experience, and ultimately over how generative AI turns popularity into profit.

As the second-half launch window approaches, the device itself will matter. But the bigger story lies in what it represents — a pivotal shift in OpenAI’s business model, from being a powerful engine inside other people’s products to becoming a full-stack company determined to own its future.

Energy costs are fast becoming the decisive factor in which countries lead the global artificial intelligence race, according to Microsoft CEO Satya Nadella, who warned that cheap, reliable power will increasingly determine whether AI translates into real economic growth or remains an expensive technological promise.

Speaking at the World Economic Forum in Davos on Tuesday, Nadella framed AI not just as a software or innovation challenge, but as an economic system built on a new global commodity: “tokens,” the basic units of computation that power modern AI models. In his view, the ability of nations and companies to convert these tokens into productivity, growth, and competitiveness will hinge directly on the price of energy.

“GDP growth in any place will be directly correlated to the cost of energy in using AI,” Nadella said, arguing that economies with cheaper energy effectively enjoy a structural advantage. “The job of every economy and every firm is to translate these tokens into economic growth. If you have a cheaper commodity, it’s better.”

That framing highlights a critical shift in how AI leadership is being contested. The focus is no longer only on who has the best models or the most data, but on who can operate AI at scale at the lowest total cost. Energy, alongside silicon and data center construction, now sits at the heart of that equation.

Hyperscalers, such as Microsoft, Amazon, and Google, are already reshaping global infrastructure around this reality. Microsoft said at the start of 2025 that it expects to spend about $80 billion on AI data centers this year alone, with roughly half of that investment taking place outside the United States. The scale of that spending underlines how energy availability and pricing are influencing where AI capacity is built.

Nadella stressed that the total cost of ownership, rather than headline electricity prices alone, will determine competitiveness. That includes whether countries can generate energy cheaply, whether they can permit and build data centers quickly, and how efficiently advanced chips can be deployed within those facilities.

“It’s not just the production side,” he said. “Are you a cheap producer of energy? Can you build the data centers? What’s the cost curve of the silicon in the system?”

This calculus has major implications for Europe, which currently faces some of the highest energy costs in the world. Prices surged after Russia’s full-scale invasion of Ukraine in 2022 and the subsequent reshaping of European energy markets. While prices have since eased from their peaks, they remain structurally higher than in the United States or parts of Asia, raising questions about Europe’s ability to host large-scale AI infrastructure competitively.

Beyond cost, Nadella also raised a political and social constraint that could shape AI deployment. He warned that public acceptance of AI-driven energy use is not guaranteed, especially as power grids come under strain.

“We will quickly lose even the social permission to actually take something like energy, which is a scarce resource, and use it to generate these tokens, if these tokens are not improving health outcomes, education outcomes, public sector efficiency, private sector competitiveness across all sectors,” he said.

That comment reflects a growing tension between AI expansion and energy sustainability. As data centers consume increasing amounts of electricity, governments and voters are likely to demand clearer economic and social returns from that consumption. AI projects that fail to demonstrate tangible benefits may face political resistance, stricter regulation, or limits on power allocation.

Nadella’s critique of Europe went beyond energy costs to what he described as a narrow inward focus. He argued that European competitiveness in the AI era cannot be built around regional protectionism or sovereignty alone, but must be measured by the global relevance of its output.

“European competitiveness is about the competitiveness of their output globally, not just in Europe,” he said.

He linked Europe’s historical prosperity to its ability, over centuries, to produce goods and services the rest of the world wanted. In his view, replicating that success in the AI age requires investment not only in regulation and governance, but in the physical inputs of AI: energy, compute capacity, and scalable infrastructure.

Nadella also pushed back against what he sees as an overemphasis on technological sovereignty. “Whenever we come to Europe, everyone’s talking about sovereignty,” he said, adding that access to markets and customers may matter more than insulating domestic industries.

Protecting Europe, he suggested, will not automatically make it competitive if its AI-powered products cannot succeed globally.

In summary, Nadella’s remarks underline a broader shift in the AI debate. Leadership is no longer defined solely by research breakthroughs or startup ecosystems, but by industrial fundamentals: energy pricing, infrastructure speed, capital deployment, and public legitimacy. Countries that can align these factors may find themselves converting AI tokens into sustained economic growth, while others risk being priced out of the race, regardless of their technical ambitions.

As the prospect of a renewed U.S.–Europe trade war sharpens, the International Monetary Fund has delivered one of its bluntest assessments yet of Europe’s economic position, warning that the continent risks entering a volatile geopolitical phase without the economic cohesion needed to defend its interests.

Speaking at the World Economic Forum in Davos, IMF Managing Director Kristalina Georgieva urged European leaders to move faster on long-delayed reforms, arguing that the continent’s internal weaknesses are leaving it exposed just as U.S. President Donald Trump escalates trade pressure on long-standing allies.

Her remarks came days after Trump announced plans to impose escalating tariffs on imports from eight European countries — Denmark, Norway, Sweden, France, Germany, the United Kingdom, the Netherlands and Finland — unless Washington is allowed to acquire Greenland, an autonomous Danish territory. Under Trump’s plan, tariffs would begin at 10% on February 1 and rise to 25% by June 1 if no agreement is reached.

The threat has injected fresh uncertainty into transatlantic relations, already strained by disputes over trade, defense spending and industrial policy. It has also revived concerns that tariffs are again becoming a central tool of U.S. foreign policy, applied not only to rivals but also to allies.

Against that backdrop, Georgieva’s message to Europe was stark. “Europeans, if you’re watching, get your act together,” she said, arguing that the continent is failing to fully use its economic weight at a time when power politics are reshaping global trade.

According to the IMF chief, Europe’s challenge is not simply external pressure from Washington but deep-seated structural problems that have lingered for years. She pointed to weak productivity growth, fragmented capital markets and persistent barriers that prevent small firms from scaling into global champions.

“Europe has fallen behind in productivity. Europe has fallen behind in getting small companies to grow to giants,” Georgieva said, warning that these shortcomings are eroding Europe’s competitiveness relative to the United States and parts of Asia.

She outlined four priorities she said are essential if Europe is to regain momentum and credibility. The first is completing the capital markets union, which would allow savings to flow more easily into productive investment across the bloc. Georgieva noted that around 300 billion euros of European savings are currently invested in the United States, capital that could otherwise be funding innovation and expansion at home.

The second is completing the energy union. High and uneven energy costs, exacerbated by geopolitical tensions and the transition away from Russian gas, have left European industry at a disadvantage. Georgieva said it is impossible for Europe to compete globally while operating what are effectively 27 separate energy systems.

Third, she highlighted labor mobility. While free movement is a core EU principle, practical barriers still prevent workers from easily taking jobs across borders.

“You cross the border from Germany to France, you can’t work there,” she said, arguing that this rigidity undermines growth and limits firms’ ability to find talent.

Finally, Georgieva stressed the need for sustained investment in research and innovation, warning that Europe risks falling further behind in key technologies if it does not move faster.

Her comments reflect a growing sense among international institutions that Europe’s economic model, while resilient, is struggling to adapt to a more confrontational and fragmented global environment.

European leaders have reacted angrily to Trump’s tariff threats. Several governments have described the measures as unacceptable and have called for dialogue rather than escalation. France is reportedly pushing for the European Union to consider deploying its Anti-Coercion Instrument, the bloc’s strongest trade defense mechanism, which would allow it to retaliate against countries that use economic pressure for political ends.

European Commission President Ursula von der Leyen used her Davos keynote to frame the moment as a turning point. She said Europe can no longer rely on the assumptions of the old global order and must be prepared to stand on its own as geopolitical shocks become more frequent.

“If this change is permanent, then Europe must change permanently too,” von der Leyen said, calling for the construction of what she described as a “new independent Europe.”

While she did not explicitly endorse retaliation, her remarks underscored a growing willingness in Brussels to consider a more assertive stance.

Trump, meanwhile, said he had agreed to meet European officials in Davos to discuss his Greenland ambitions, even as leaders in Denmark and Greenland have repeatedly said the territory is not for sale. The issue has raised alarm within Europe, where officials warn that linking trade penalties to territorial demands could set a dangerous precedent and strain NATO unity.

Despite the rising tensions, the IMF is urging caution. Georgieva noted that the Fund had slightly upgraded its global growth forecasts this week, projecting growth of 3.3% this year and 3.2% in 2027. One reason, she said, is that the economic damage from tariffs has so far been less severe than many feared, largely because governments avoided full-scale retaliation.

“There was no tit for tat trade war,” she said, adding that this restraint helped prevent last year’s tariff threats from tipping major economies into recession.

She urged policymakers and markets alike to remain calm, arguing that economic rationale has so far prevailed over political impulses.

Still, Georgieva’s warning carried a clear subtext. As countries increasingly weigh the strategic use of trade tools, Europe’s ability to protect itself will depend less on rhetoric and more on whether it can finally deliver long-promised reforms. Without deeper integration and stronger competitiveness, she suggested, Europe risks entering a more hostile global era from a position of relative weakness.

U.S. equity markets opened the week on a sharply lower note on Tuesday, with technology shares bearing the brunt of investor unease over President Donald Trump’s escalating rhetoric on acquiring Greenland and his threats of punitive tariffs against European allies.

The sell-off reflected broader concerns about renewed transatlantic trade tensions, just as global leaders converged on Davos, Switzerland, for the World Economic Forum. The State Street Technology Select Sector SPDR ETF (XLK) declined 1%, while major tech names posted steeper losses. Nvidia and Tesla each tumbled nearly 3%, with Meta Platforms, Alphabet, Apple, Microsoft, and Amazon all shedding more than 1%. Broader indexes followed suit: the Nasdaq Composite closed down 1.3%, underperforming the S&P 500’s 1.1% drop and the Dow Jones Industrial Average’s 0.9% decline.

The catalyst came from Trump’s Truth Social posts over the weekend, where he reiterated his long-standing interest in U.S. control of Greenland—an autonomous Danish territory he views as strategically vital for national security, Arctic defense, and countering influence from China and Russia.

In a lengthy January 17 post, Trump announced plans for a 10% tariff on goods from eight European nations—Denmark, Norway, Sweden, France, Germany, the United Kingdom, the Netherlands, and Finland—effective February 1, escalating to 25% on June 1. He tied the levies directly to negotiations for a “Complete and Total purchase” of Greenland, framing the move as essential for “Global Peace and Security.”

Trump doubled down on Tuesday with a flurry of posts, sharing what appeared to be private messages from leaders like French President Emmanuel Macron, mocking allies, and insisting “there can be no going back” on his ambitions. He even posted edited images depicting Greenland and parts of Canada under U.S. flags, while refusing to rule out forceful options if diplomacy fails.

European leaders responded with alarm. EU Commission President Ursula von der Leyen called the tariff threats a “mistake” that undermines trust between allies. French President Emmanuel Macron warned of a potential shift to a “world without rules” and signaled readiness to activate the EU’s anti-coercion instrument—a so-called “trade bazooka”—for retaliatory measures worth billions.

Belgian Prime Minister Bart De Wever declared that “so many red lines have been crossed,” while others in Davos urged compartmentalizing the Greenland dispute from broader trade talks. U.S. Trade Representative Jamieson Greer, speaking at Davos, suggested the threats were tactical to “set the scene” for negotiations, downplaying immediate escalation.

Treasury Secretary Scott Bessent brushed off market “hysteria,” but investors remained skittish, with the CBOE Volatility Index (VIX) spiking to levels not seen in recent months.

The renewed focus on tariffs revives memories of trade frictions from Trump’s first term, now complicated by Greenland’s strategic importance amid melting Arctic ice and great-power competition. Analysts note that any broad tariffs could disrupt supply chains for U.S. tech firms reliant on European components, markets, or partnerships, amplifying the “risk-off” sentiment hitting AI and growth stocks hardest.

Yet not all voices were bearish. Wedbush Securities analyst Dan Ives, attending Davos, framed the dip as a classic buying opportunity.

“Tech stocks will be hit as the ‘risk off dynamic’ hits AI names front and center but ultimately we view this as an opportunity to own the tech winners for 2026 and beyond,” Ives wrote in a note to clients.

He dismissed the geopolitical “soap opera” as temporary noise, arguing that the AI revolution remains in its early innings and unaffected by short-term trade spats.

Ives pointed to an impending catalyst: a “robust” fourth-quarter earnings season from tech giants, fueled by an estimated $550 billion in capital expenditures dedicated to AI infrastructure. He recommended accumulating shares on weakness in names like Nvidia, Microsoft, Palantir, CrowdStrike, Nebius, Apple, Palo Alto Networks, Alphabet (Google), and Tesla—stocks he sees as core beneficiaries of the ongoing “4th Industrial Revolution.”

While the tariff threats contributed to Tuesday’s losses, tech had already shown signs of rotation fatigue earlier in January, with the “Magnificent Seven” group underperforming amid valuation concerns. The pullback erased recent gains and pushed some indexes into negative territory for the year so far.

As Davos proceedings continue—with Trump scheduled to address attendees on Wednesday—investors will monitor for any de-escalation signals. European retaliation threats and potential Supreme Court scrutiny of tariff authority loom as additional risks.