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Greek Shipowners Lead Aggressive Rebound In Global Newbuilding Market

Greek shipowners strengthened their position in the newbuilding market during the first quarter of 2026, with activity significantly higher than a year earlier, according to data from Xclusiv Shipbrokers.

Market Rebound And Overview

Between January and March, Greek stakeholders secured 102 new vessel contracts, up sharply from 33 in the same period of 2025. Globally, total orders reached 422 vessels, up from 315 a year earlier, indicating a broader recovery in maritime investment.

Tanker Dominance In Contracting

Growth was largely driven by a renewed focus on tanker vessels. Greek shipowners placed 63 tanker orders, including 24 VLCCs and 23 Suezmaxes, compared to just 13 in the previous year. Across the global market, tanker contracting rose from 79 to 152 vessels. Orders for VLCC and ULCC segments increased from only three units last year to 64, reflecting stronger demand for large-scale crude transport capacity.

Expansion Into Dry Bulk And LNG

Beyond tankers, Greek buyers expanded activity in the dry bulk segment, ordering 16 vessels, including six Capesize and six Newcastlemax ships, following a period of limited engagement.

Nine LNG carrier orders further indicate a strategic shift toward gas transportation, as operators position for evolving energy demand. At the global level, dry bulk contracting also increased, with a clear preference for larger vessels suited for long-haul routes.

Global Trends And Strategic Investments

Containership investment remained relatively stable. Greek owners ordered 13 vessels, mainly in feeder and handy segments, while global container orders reached 159 units. This consistency suggests a more measured approach in container shipping, as operators balance fleet renewal with shifting trade dynamics.

Cyprus-Linked Strategic Expansions

Entities with ties to Cyprus also advanced targeted investments. Mitsui O.S.K. Lines announced a joint venture to build two service operation vessels, while Lemissoler Navigation placed orders in China for methanol dual-fuel Ultramax bulk carriers.

Additional activity from Safe Bulkers and Star Bulk Carriers reflects continued fleet renewal with a focus on efficiency and sustainability. At the same time, companies such as Euroseas expanded into specialized containership segments, while Pelagic Credit pursued diversification through structured vessel investments.

Outlook

Rising order volumes, stronger tanker demand, and broader diversification strategies indicate a clear shift in market dynamics. Activity in early 2026 points to renewed confidence among shipowners, with investment decisions increasingly aligned with long-term trade patterns and operational flexibility.

AI Spending Is Complicating The Fed’s Fight Against Inflation

Silicon Valley leaders have long argued that artificial intelligence will make technology and services dramatically cheaper. OpenAI CEO Sam Altman has described a future where intelligence becomes extremely inexpensive, while Tesla and SpaceX CEO Elon Musk has predicted that AI and robotics will create greater abundance and drive down costs.

So far, those benefits have yet to materialise at scale. AI adoption remains relatively slow, while the enormous investment needed for data centres and AI infrastructure is putting pressure on electricity prices, supply chains and other costs. For the Federal Reserve, this creates a difficult balancing act: AI could eventually boost productivity and reduce inflation, but its current buildout is contributing to higher prices.

OpenAI chief economist Ronnie Chatterji said AI needs to be adopted by organisations and generate measurable value before its broader economic impact becomes visible in productivity statistics.

AI Adoption Remains Uneven

Capital spending on AI infrastructure in the U.S. is expected to reach $581 billion this year, according to Goldman Sachs Research, with global investment potentially reaching $1 trillion.

Despite the scale of spending, adoption remains far from universal. A May survey by the U.S. Census Bureau found that 17% to 20% of U.S. businesses reported using AI, with adoption significantly higher among large companies.

Companies that have implemented AI at scale also highlight the challenges. Julie Averill, former CIO of Lululemon, said successful deployment requires changes in employee behaviour and trust in the technology. OpenAI has observed a similar divide: its most advanced business users deploy AI at around eight times the rate of average companies.

Why Productivity Gains May Take Time

Economists point to the limits of automation. AI can perform individual tasks effectively, but many jobs combine tasks that are difficult to automate.

Stanford professor Charles Jones refers to these as “weak links”. Radiology, for example, involves interpreting scans but also communicating with patients and working with colleagues. AI can automate part of the job without eliminating the profession itself.

As a result, the full economic impact of AI may not become clear until businesses adopt the technology more broadly and reorganise their operations around it.

AI Adds To The Fed’s Policy Challenge

AI’s economic impact has become part of the Federal Reserve’s policy debate. Fed Chairman Kevin Warsh has argued that AI could eventually become a significant disinflationary force by increasing productivity and strengthening U.S. competitiveness.

Other officials are more cautious. In July, the Fed kept interest rates at 3.5% to 3.75%, while some officials expressed concern that AI infrastructure spending could add to inflationary pressures.

Minneapolis Fed President Neel Kashkari pointed to massive data-centre investment as a new source of demand. Household electricity prices rose 10% in the two years through July, compared with a 6.2% increase in overall consumer prices. Meanwhile, shortages of chips and other AI components are pushing up costs. JPMorgan Chase estimates that DRAM prices could rise 400% by the end of 2026 compared with 2024.

Warsh has consequently adopted a more cautious tone, saying that while AI investment is laying the groundwork for future growth, the timing and scale of its economic effects remain difficult to predict.

For the Fed, the challenge is clear: AI could eventually deliver major productivity gains, but the cost of building that future is already showing up in the economy.

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