Can The Private Cloud Help Control AI Spending? HPE Thinks So

The cost of AI is spiralling. Research from automation provider Esker, found 72% of finance leaders agreeing their organization has spent more than planned on AI initiatives over the past year. However, many organizations are looking to the private cloud to get better control over spending.

According to Broadcom’s Private Cloud Outlook 2026 report, 56% of enterprises are running or plan to run production AI inferencing in the private cloud, while 83% are considering repatriating workloads from public to private cloud.

One company betting big on the private cloud is enterprise technology provider, HPE. After announcing record revenue of $12.2 billion for Q3 2026, up 34% year-over-year, HPE CFO Marie Myers noted during the company’s earnings call that the company has seen success from deploying an agentic AI platform built with its own private cloud AI (PCAI) open source and open weight models.

The platform uses the private cloud and intelligent routing to send each workload request to the most cost-effective AI model. Myers claims this approach has reduced token costs versus the public cloud by up to 60% internally, with routine tasks performed on-premises and frontier models reserved for more complex work.

Investing In The Private Cloud

As enterprises seek to push AI adoption to extremes, tokenmaxxing has become common across the tech industry, with companies like Meta and Uber consuming high volumes of tokens, with the latter blowing through its AI budget in just a matter of months.

Though as scrutiny over spending increases in the wake of these cautionary tales, more organizations are turning to efficiency and model routing to control costs. Speaking on HPE’s investment in private cloud AI, Marie Myers told me in a video interview that, in order to “manage costs”, the company decided that “investment in our own private cloud would be the right path to really accelerating enterprise AI adoption.”