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Enterprises Grapple with AI Costs and Inefficient GPU Utilization
Importance: 88/1004 Sources
Why It Matters
As AI adoption accelerates, effectively managing and optimizing the substantial costs associated with AI development and infrastructure, particularly GPU usage, is critical for businesses to ensure profitability and derive maximum value from their investments.
Key Intelligence
- ■BNY Mellon is implementing 'disciplined' strategies to track and manage its growing Artificial Intelligence-related expenditures.
- ■A significant majority (79%) of enterprises are underutilizing their Graphics Processing Units (GPUs) for AI, operating at less than 50% capacity.
- ■New FinOps solutions, like CloudKeeper, are emerging to help businesses monitor and optimize their AI and Large Language Model (LLM) costs.
- ■The push for better cost tracking highlights a broader industry challenge of achieving efficiency and return on investment from AI initiatives.
Source Coverage
Google News - AI & Bloomberg
10/27/2026BNY Mellon Says It Has Become ‘Disciplined’ to Track AI Costs - Bloomberg.com
Google News - AI & Bloomberg
10/27/2026BNY Mellon Says It Has Become ‘Disciplined’ to Track AI Costs - Bloomberg.com
Google News - AI & VentureBeat
10/26/2026Shocking GPU Usage Statistics: 79% of Enterprises Run at Less Than 50% GPU Utilization - 36Kr
Google News - AI & LLM
10/26/2026