What Teskey Is Seeing
Worried the AI boom might hit a wall? Teskey is not. He told Bloomberg Television that the need for compute and energy capacity is already far ahead of what is available and will remain that way "throughout the end of this decade and beyond." That cushion is so large, he said, it can absorb short development slowdowns while providers keep building aggressively. In his words: "Despite some of the headlines, we do not see things slowing down whatsoever."
He also flagged a shift in who is paying for all this. As big companies push for tighter control over infrastructure, supply chains and key inputs, more private capital is stepping in as a partner to get projects financed.
Where Brookfield Is Putting Money To Work
In the second quarter, Brookfield raised a record $77 billion and is prioritizing AI and digital infrastructure, together with the energy required to power it, as its fastest-growing focus. Since the start of the year, the firm has struck a strategic partnership with OpenAI and scaled up its agreement with US fuel cell maker Bloom Energy to $25 billion, a fivefold increase. It also participates in an Nvidia consortium committing to finance AI computing deals that add up to more than $500 billion.
Compute and power are now the two binding constraints on AI growth. Market Briefs covers that bottleneck free every weekday.
The Power Side Of The Story
Rising electricity use is pulling investment across generation technologies. Brookfield says activity is ramping up in renewable power, fuel cells, battery systems and nuclear energy, and interest is also flowing into established assets such as utility grids, gas pipelines and transportation networks.
Higher rates can make deployment tougher for some investors and operators, Teskey noted, but he said Brookfield's access to capital is an advantage right now: "There's a lot of growth in the market and that can overwhelm slightly higher cost of capital."
Why It Matters For Your Money
If this supply gap sticks around, capital likely keeps chasing data centers, new power sources and the connectors in between. The real takeaway: the AI rush is not just chips and models, it is also about electricity and infrastructure. That is where a lot of the building - and the financing - is headed.
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