地圖呈現：各國AI採用率

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Technology

Mapped: AI Adoption Rates by Country

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Mapped: AI Adoption Rates by Country

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Key Takeaways

In the second half of 2025, 16.1% of the global working-age population used AI, indicating substantial room for further adoption.

At the same time, usage varies widely across countries. Adoption rates average 24.7% in the Global North, while they are 14.1% in the Global South. Key countries stand as clear regional outliers including the UAE and Singapore.

This graphic shows AI adoption by country, based on data from the Global AI Adoption in 2025 report from Microsoft.

How AI Adoption Rates Compare Worldwide

For the analysis, Microsoft estimated AI usage across 147 countries worldwide.

Below, we show the share of each country’s working-age population that used AI at least once over H2 2025. Additionally, we show the percentage point (p.p.) change compared to H1 2025, representing the absolute difference between the two periods.

With 64.0% of the population using generative AI tools, the UAE not only ranks first globally, but stands as one of the fastest-growing countries in adoption.

Even before ChatGPT launched, AI technology was being used across public services in the UAE. This was supported by early governance frameworks that were established in 2017, as part of its national AI strategy targeting nine key sectors.

Ranking in second is Singapore, where 60.9% of the population uses AI. Like the UAE, Singapore invested early in AI infrastructure and research and development.

In Europe, Norway ranks first along with taking third place globally with a 46.4% adoption rate. It is followed by Ireland (44.6%), and France (44.0%), two countries with robust tech ecosystems.

Meanwhile, adoption rates in the U.S. stood at 28.3%, or 24th overall. Interestingly, although the U.S. develops world-class AI research and is home to some of the world’s largest AI-related firms, trust in AI technology is fairly low.

According to the Edelman Trust Barometer, just 32.0% of the U.S. population trusts AI. In comparison, the figure jumps to 67.0% in the UAE.

At the tail end of the adoption spectrum is Cambodia, where it stands at just 5.1%. While progress is underway, limited investment and infrastructure remain key barriers to wider adoption.

Learn More on the Voronoi App

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Technology

Charted: The Battle for AI Data Center Revenue (2021–2025)

With the generative AI boom igniting demand for AI chips and data centers, how has market share changed between NVIDIA, AMD, and Intel?

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The Battle for AI Data Center Revenue (2021–2025)

See visuals like this from many other data creators on our Voronoi app. Download it for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Key Takeaways

In just five years, the companies competing for AI chips and data center market share were reshuffled significantly.

This chart visualizes the changing market share of AI and data center revenue over time between Intel, Nvidia, and AMD.

The data comes from Bloomberg and company-reported segment revenue from Nvidia, Intel, and AMD, with the chart showing each company’s share of the combined (peer-set) total from 2021–2025.

AI and Data Center Revenue Market Share (2021–2025)

At the start of the decade, Intel was the undisputed king, capturing over two-thirds of AI chip and data center market share when compared to Nvidia and AMD.

In 2021, Nvidia only had about 25% of market share and was known primarily for gaming GPUs, while AMD was a distant third with just 7% market share.

As seen in the data table below, revenues have shifted significantly since 2021, with Nvidia as the market share leader at 86% as of late 2025.

The viral rise of AI chatbots like OpenAI’s ChatGPT took the world by storm after launching in late 2022, turning the tide quickly as Big Tech and governments rushed to build “AI factories”—huge data centers designed to train and run large language models (LLMs)—driving demand toward GPU-heavy infrastructure.

How Nvidia Took the Lead in the AI Chip Market

Nvidia capitalized on this shift by improving not just the GPU (making it faster and more power-efficient) but the whole AI system.

This includes chips, networking, and software—so gains compounded at the platform level rather than relying on traditional CPU scaling.

CEO Jensen Huang noted that while traditional Moore’s Law had slowed for CPUs, Nvidia’s AI computing performance was doubling nearly every year.

He explained that Nvidia can push performance faster because it builds “the architecture, the chip, the system, the libraries, and the algorithms” together in parallel.

Beyond the silicon, Nvidia’s advantage was its complete software and hardware ecosystem, which created a moat that raised switching costs.

Why Did Intel Lose Its Crown?

Intel’s Data Center & AI share fell for one primary reason amidst repeated delays in its 2021 and 2022 CPU chip iterations.

Intel was CPU-focused while competition intensified, and after ChatGPT’s launch (Q4 2022), data-center spending shifted toward GPU-heavy AI systems.

The company failed to adapt and scale, as its AI-chip deals fell short of initial expectations.

Management even dropped its 2024 target of $500M+ in AI-accelerator revenue, citing a software platform transition.

All those missteps left it underexposed to the fastest-growing slice of AI data-center spend, while Nvidia ran away with the lead.

Learn More on the Voronoi App

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Technology

Charted: The Explosive Growth of Gen AI Apps

ChatGPT has become the #2 app globally by in-app purchase revenue, trailing only TikTok.

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Charted: The Rise of Gen AI Apps

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Key Takeaways

Generative AI has rapidly moved from an experimental novelty to a mainstream consumer product. In just a few years, apps powered by large language models and image generators have become daily tools for writing, search, education, and entertainment.

This chart tracks how generative AI apps are climbing the global mobile rankings. The data for this visualization comes from Sensor Tower and reflects combined iOS and Google Play performance globally (with China measured on iOS only). Figures for 2026 are forecasts.

Gen AI Becomes a Top-Tier Mobile Category

According to Sensor Tower, Generative AI apps were projected to approach 4 billion downloads, generate $4.8 billion in in-app purchase revenue, and account for 43 billion hours of time spent in 2025 alone.

By 2026, consumer spending on Gen AI apps is expected to exceed $10 billion, placing the category among the most lucrative on mobile.

As a result, Gen AI is forecast to jump from #10 in downloads in 2025 to #4 in 2026, ranking ahead of established categories like Multimedia & Design Software and Shopping.

Sensor Tower projects the category will rise to #3 in in-app purchase revenue by 2026, surpassing popular genres such as Dating & Social Discovery.

This surge reflects growing consumer willingness to pay for AI-powered tools, subscriptions, and premium features as these apps become embedded in everyday workflows.

Time Spent Signals Deepening Engagement

Beyond installs and revenue, user engagement is also accelerating. Gen AI apps are expected to climb to #5 globally by time spent in 2026, outranking major consumer categories including Travel & Tourism, Shopping, and Financial Services.

This trend suggests generative AI is not just being tried, it’s becoming a habit.

ChatGPT Leads the Category

By Q3 2025, ChatGPT had already become the #2 app globally by in-app purchase revenue across iOS and Google Play, trailing only TikTok.

As competitors like Google Gemini and other AI-powered tools expand, the category’s momentum is expected to accelerate further.

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