As we all know, AI is the buzzword of Tech. According to the Dell’Oro Group, global data centre CAPEX is projected to surpass $1 trillion by 2029, with AI Training and domain-specific workloads expected to represent nearly half of global data centre infrastructure spending during that period.
At the start of this year, we were inundated with announcements from major tech giants unveiling their fiscal 2025 spending plans. From Google’s $75 billion and Microsoft’s $80 billion CAPEX to Amazon’s $100 billion (up from $83 billion in CAPEX for fiscal 2024), hyperscalers are funnelling billions of dollars into AI and data centre infrastructure. And it’s not just private companies; governments are joining the trend too. In January, the US government revealed its massive $500 billion ‘Project Stargate’ initiative, with the likes of Oracle, OpenAI, and the UAE’s MGX joining in. It’s estimated that Amazon, Meta, Google, and Microsoft alone will collectively contribute as much as $320 billion this year to AI and data centre infrastructure.
Then… DeepSeek hit the market. Built at a fraction of the cost of leading models like OpenAI and using fewer advanced chips, its sudden debut challenges the notion that cutting-edge AI development requires massive investments.
Following this, last week TD Cowen reported that Microsoft had cancelled a number of its data centre leases and let more than a Gigawatt of agreements on larger sites expire. This news has further raised questions within the industry.
In light of DeepSeek, the necessity and profitability of heavy AI investments are now under scrutiny. Could Microsoft’s cancellations signal oversupply concerns? Have tech giants opened their purses a little too wide? And in the long run, what will happen to these data centres — often dubbed AI factories — when AI Training shifts toward Inference at the edge?
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