AI Cost Management vs.
Cloud Cost Management

AI’s spending, pricing, and complexity are higher – making it harder to stay in the black while pursuing the green.

AI is 4x harder to govern

0 %
of companies have core cloud usage management practices like FinOps
0 %

of companies have comparable practices for AI

Cloudflation is real, but AI inflation is extreme

Up to

0 %
rate increases driven by cloudflation, depending on the provider
0 %

increase in the average cost of AI computing between 2023-2025

2x

increase forecast for critical power needs for GPU servers between 2023-2026

AI budgets are accelerating twice as fast as cloud

0 %

of organizations plan to increase their cloud budgets

0 %

of companies plan to increase their AI investments by 2028

0 %

increase in spending on compute and storage hardware for AI deployments in the first half of 2024

AI maturity is 14x harder to achieve than cloud maturity

0 %

of companies are at the “Run” level of FinOps – the top maturity stage designated by the FinOps Foundation

1%

of enterprises say their AI investments have reached maturity, meaning they are financially optimized to drive substantial outcomes

AI is 6x more expensive than cloud

$320

for a standard cloud server with 2 CPUs, 16 GB of memory, and 256 GB of storage

$1,897

for a GPU-powered server with dual NVIDIA Pascal processors and 32 GB of GPU memory

Bottom line: without proper cost oversight, the cloud services required to power AI can become the top barrier to its success.

0 %
of organizations have canceled or postponed at least one AI initiative due to costs, and roughly 20% of initiatives fail to scale for this reason
0 %

of organizations now manage AI spending, more than double compared to 2024

See how a FinOps-certified platform like Tangoe One Cloud makes AI cost management faster, smarter, and more scalable.