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The article discusses the evolving landscape of AI cost management, emphasizing the importance of tagging and model governance for FinOps practitioners. It highlights insights from Deeja Cruz of Datadog, who underscores that while the tools may change, the fundamental principles of understanding usage and costs remain constant. This perspective is crucial for small business operators who are navigating the complexities of AI investments.
For small business owners, the emphasis on tagging and governance is particularly relevant as they seek to optimize their AI expenditures. As AI technologies become more integrated into operations, understanding the cost implications and ensuring proper management practices will be vital. This piece serves as a reminder that while the AI landscape is rapidly evolving, foundational financial management principles should not be overlooked.
Takeaway: Focus on tagging and governance to effectively manage AI costs in your business.
From the original item — SiliconAngle:
AI cost management is bringing a new taxonomy to FinOps practitioners, but the core discipline — understanding what you’re using, why, and what it costs — remains the same. That constancy is reassuring and instructive, according to Deeja Cruz (pictured), senior FinOps analyst at Datadog Inc. The biggest practical lesson enterprises can carry from cloud […]
The post Datadog sees tagging and model governance as the foundation of AI cost management appeared first on SiliconANGLE.