The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs
A survey of 107 enterprises found that they are investing in AI infrastructure faster than they can measure its costs, leading to a 'compute gap'. This gap is due to a lack of visibility into the economics of the compute, with most enterprises unable to track their costs or utilization.
What happened
The survey found that only 21% of enterprises run AI in production at scale, despite aggressive spending intentions. Most enterprises are still in the early stages of deployment, and their compute footprint is about to grow. They are planning to move a significant share of AI compute off general-purpose clouds and onto specialized AI clouds, which they barely use today.
Why it matters
This compute gap is a problem for operational business owners because it means they are spending money on infrastructure without being able to see the return on investment. It also means that they are not making informed decisions about their infrastructure choices, which can lead to inefficiencies and wasted resources.
The takeaway
Business owners need to prioritize building visibility into the economics of their compute infrastructure, including tracking costs and utilization. This will help them make more informed decisions and avoid the compute gap.
Our plain-English take, written from public reporting for operational business owners. Always read the original for full context.
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