ARK Invest forecasts the growth of the AI infrastructure market to $1.5 trillion - ForkLog: cryptocurrencies, AI, singularity, the future

# At ARK Invest, they forecast the AI infrastructure market to grow to $1.5 trillion

The decreasing cost of training neural networks makes the technology more accessible, and rising demand requires large investments in computing power. By 2030, global spending on AI infrastructure could approach $1.5 trillion, according to ARK Invest.

AI adoption is outpacing the internet, and infrastructure is scaling to match.

We believe this is the beginning of a massive buildout, as consumers and enterprises signal strong demand.@downingARK shares the latest on AI infrastructure in a new blog.https://t.co/tatNHMFiuM

— ARK Invest (@ARKInvest) March 25, 2026

Prices Drop, Demand Rises

According to analysts, the cost of training neural networks drops by 75% annually. Inference for models with accuracy above 50% in benchmarks becomes even cheaper — on average by 95%.

Source: ARK Invest Cost reduction typically lowers expenses. However, in the case of artificial intelligence, the situation is different: the more affordable training and operation of models become, the broader the range of tasks where their application is economically justified.

Mass adoption of AI is happening twice as fast as with the internet. In just three years, technology penetration reached 20%. It took the World Wide Web over six years to reach the same level.

Corporate demand is also rapidly increasing. Token requests via OpenRouter have grown 28 times since December 2024. Anthropic increased its annual revenue from $100 million in 2023 to $14 billion by February 2026. By November 2025, OpenAI had reached 1 million business clients.

Source: ARK Invest ## Infrastructure Boom

Since the launch of ChatGPT, demand for accelerated computing has skyrocketed. Nvidia’s annual revenue grew from $27 billion in 2022 to $216 billion in 2025. Analysts forecast that in 2026, this figure will reach $350 billion.

Global investments in server systems accelerated from 5% annually (over the decade before 2022) to 30% in the last three years. According to ARK, solutions based on GPUs and specialized chips (ASICs) have become the dominant segment, accounting for 86% of the server computing market.

Private investments in AI infrastructure in 2025 exceeded $200 billion, with about $80 billion going to developers of foundational models. hyperscalers are seeking alternative funding sources: Meta’s deal with Blue Owl for $30 billion became the largest private capital transaction in history.

Chip Battle

Rising demand has intensified competition among hardware manufacturers. AMD managed to catch up with Nvidia in total cost of ownership (TCO) for inference of small models. However, in the heavy model segment, Nvidia maintains a performance lead thanks to the Grace Blackwell architecture.

Source: ARK Invest Hyperscalers are actively developing their own semiconductor solutions. Google has been designing TPU for 10 years. According to SemiAnalysis, using custom chips for internal tasks could reduce computing costs by 62% compared to architectures from Nvidia.

Amazon promotes Trainium, making it the preferred platform for training Anthropic. Microsoft is deploying the second generation of Maia accelerators optimized for inference.

Broadcom dominates backend design, partnering with Google TPU, Meta MTIA, and the upcoming OpenAI chip. Citi forecasts the company’s AI revenue to grow from $20 billion in 2025 to $100 billion in 2027.

Startups with new architectures are becoming more active. Cerebras, known for its Wafer Scale Engine chip, plans to go public this year. Meanwhile, Groq has signed a licensing agreement with Nvidia worth $20 billion.

Forecast

According to ARK, by 2030, annual investments in AI infrastructure will reach $1.5 trillion — a threefold increase in five years. The share of specialized ASICs in computing power will grow to one-third of the market.

Source: ARK Invest

“The infrastructure built today is not a bubble ready to burst but a foundational platform shift happening once in a generation. Useful AI agents are just beginning to be deployed; they are ‘token-hungry,’ but far more capable than what users are accustomed to. Scaling these agents across millions of businesses will require colossal computing power, justifying the investments,” — experts summarized.

Remember, Citrini Research experts predicted an economic collapse due to artificial intelligence.