Generative AI Drives Surge in Enterprise Cloud Spending, Over 40% of Companies to Allocate More Than 30% of Budgets Within Three Years
A survey of 215 North American IT buyers by TD Cowen reveals that 42% of companies expect to invest over 30% of their cloud budgets in generative AI within the next three years, with related spending quadrupling by 2028. Gartner analyst Hardeep Singh recommends controlling costs through committed contracts, FinOps, and resource optimization, and notes that enterprises are shifting toward industry-specific cloud solutions to address compliance needs.
At a Glance
- According to a survey released by TD Cowen earlier this month, 42% of enterprises expect to allocate more than 30% of their cloud budgets to generative AI within the next three years. The survey covered 215 North American IT buyers. Additionally, nine out of ten leaders expect generative AI use cases to account for 10% of cloud budgets.
- Enterprise generative AI workloads are rapidly migrating to public cloud hyperscalers such as Oracle, Microsoft, Google, and Amazon. TD Cowen notes that the use of generative AI across organizational functions is rising almost across the board. Survey results show that IT buyers' cloud spending on generative AI workloads will grow fourfold by 2028.
- "As more than 90% of large enterprises deploy generative AI applications by 2028, IT leaders must prepare for higher costs associated with advanced infrastructure and new workloads," said Hardeep Singh, principal analyst at Gartner, to CIO Dive, a sister publication of CFO Dive.
Deep Dive
Generative AI workloads are driving up cloud budgets, potentially affecting how IT leaders manage cloud platform costs.
CIOs typically adopt a multi-pronged strategy to manage spending, including negotiating commitment-based contracts with vendors to improve cost transparency and capacity assurance, Singh said. Deploying cost management tools also helps IT leaders track usage and optimize available resources. CIOs are increasingly adopting cost-tracking practices such as FinOps to analyze cloud spending.
Key strategies include "rightsizing cloud environments," which involves matching resource allocation to workload demands, and implementing auto-scaling policies to adjust capacity based on demand, Singh said.
"These measures help organizations ensure efficient consumption and keep cloud spending aligned with financial goals as AI adoption accelerates," he said.
As IT executives seek more value from cloud offerings, Singh said enterprises want to move beyond basic cloud services toward products tailored to their business needs. Hyperscalers are responding by investing billions of dollars in cloud and AI infrastructure.
Data sovereignty regulatory requirements are also driving demand for specialized or hybrid cloud products to ensure compliance, he added. For example, SAP is investing billions of dollars to build its sovereign cloud offerings in Europe.
"Enterprises are shifting from general-purpose cloud services to more industry-specific solutions to address unique regulatory and operational needs," Singh said.