Meta is turbocharging its bet on artificial intelligence, with CEO Mark Zuckerberg revealing plans to invest hundreds of billions of dollars in building large-scale AI infrastructure. This massive investment is creating unprecedented opportunities for Taiwan's supply chain ecosystem, with companies like Foxconn positioned to capture significant value from the global AI infrastructure boom.
In a July 14, 2025, post on his social media platform, Zuckerberg announced that Meta will invest vast resources in building AI data centers, with its first flagship facility, dubbed Prometheus, slated to go online in 2026. Several other high-capacity AI computing hubs are also under construction.
According to Zuckerberg, Meta is constructing several gigawatt-class AI data centers. In addition to Prometheus, the company is developing a high-capacity computing cluster known as Hyperion, which could scale to 5GW in the coming years. Meta is also working on multiple Titan-class clusters, with one sprawling across an area comparable to a significant portion of Manhattan.
This represents a dramatic escalation in AI infrastructure investment. The first data center cluster that the company is building as part of the project is called Prometheus. According to Zuckerberg, it's set to launch next year and will consume multiple gigawatts of power. One gigawatt corresponds to the electricity use of about one million households.
The scale of this investment positions Meta competitively against other tech giants. Meta's $64-72 billion 2025 AI investment positions it competitively against Amazon's $100 billion, Microsoft's $80 billion, and Google's $75 billion infrastructure spending.
Despite currency headwinds in the first half of 2025, Foxconn has delivered resilient growth on the back of strong AI server shipments. According to industry sources, the company's shipments of GPU modules and accelerator boards have surged more than 60% year-over-year, while its cloud server revenue has soared by over 150% compared to the same period in 2024.
Foxconn chairman Young Liu indicated that shipments of AI servers began experiencing rapid growth in the second quarter of 2025. He anticipated that this trend would persist throughout the latter half of 2025, with annual AI server revenue expected to exceed NT$1 trillion (US$30.6 billion). This figure would represent over half of the company's total server revenue, positioning AI as Foxconn's next business segment to reach the trillion-dollar mark.
The scale of Foxconn's AI server business transformation is unprecedented. The company's AI server revenue growth in 2024 exceeded 40%, with the revenue contribution from the overall server business increasing from over 30% in 2023 to over 40%. This momentum is accelerating through 2025.
Beyond Meta, cloud giants including Amazon Web Services and Microsoft are also stepping up capital expenditures for AI infrastructure in 2025. Industry analysts describe it as an "AI arms race without smoke," underscoring the collective confidence that Big Tech has in the sector's long-term trajectory.
This competitive dynamic is driving sustained demand for AI infrastructure components. The race to develop superintelligence capabilities is pushing companies to invest in massive computing clusters that require sophisticated supply chain coordination and logistics management.
Although suppliers have refrained from discussing specific customer shipments or facility expansions, industry experts indicate that the rising demand for AI infrastructure will provide renewed support to the technology supply chain through the latter half of 2025. With ongoing uncertainties surrounding global tariff policies and the consumer electronics market, the demand generated by AI projects is becoming a key stabilizing factor for many participants within the ecosystem.
The AI infrastructure boom is creating new requirements for supply chain management. The complexity of AI hardware components, the scale of data center projects, and the speed requirements for deployment are pushing supply chain capabilities to new levels.
Companies must now manage sophisticated component flows, coordinate complex assembly processes, and maintain quality standards across global supply chains while meeting aggressive deployment timelines. This requires advanced supply chain intelligence and logistics management capabilities.
While pending tariff decisions could add a layer of uncertainty, industry sources believe the impact on AI infrastructure investments will be limited. Most major firms have already adopted diversified global manufacturing strategies, including localized production in the US. As long as there's no sharp pullback in end-market demand, AI infrastructure spending is likely to stay strong for the foreseeable future.
Taiwan's supply chain ecosystem is adapting to these new requirements through investment in regional manufacturing capabilities. Foxconn's global production bases span 24 countries, with more than 50 sites in the Americas, and more than 10 sites each in Europe and India. This distributed approach allows rapid response to changing market conditions while maintaining Taiwan's central role in coordination and high-value manufacturing.
Some market skeptics have expressed concern over a potential AI bubble, warning of supply-demand imbalances. But major US cloud service providers remain bullish, continuing to ramp up AI-related capital expenditures. As sovereign AI initiatives gain traction across regions and use cases expand, the AI boom shows no signs of tapering off.
The sustainability of this growth depends on continued innovation in AI applications and the ability of supply chains to scale efficiently. Taiwan's integrated ecosystem provides significant advantages in both areas, with strong capabilities in both hardware manufacturing and supply chain coordination.
The Meta-led AI infrastructure boom represents a fundamental shift in technology supply chain dynamics. The scale of investment, the complexity of hardware requirements, and the speed of deployment are creating new requirements for supply chain management and coordination.
For supply chain professionals, this represents both an opportunity and a challenge. The opportunity lies in the sustained demand for sophisticated logistics and coordination capabilities. The challenge lies in managing the complexity and scale of AI infrastructure projects while maintaining cost efficiency and quality standards.