IDC PlanScape: AI Infrastructure Cost Optimization
This IDC PlanScape addresses these and other cost optimization challenges related to AI infrastructure and discusses effective practices for reducing infrastructure expenditures without compromising on the performance of AI workloads. It not only focuses especially on infrastructure for generative AI but also considers AI infrastructure writ large.While the precise steps for building the most cost-effective AI infrastructure will vary depending on the unique needs of each business and workload, the strategies described in the sections that follow will suit the needs of many enterprises seeking to take full advantage of the innovations that AI stands to offer without allowing AI to break infrastructure budgets."As enterprise AI implementation enters into full swing, now is the moment to make AI infrastructure cost optimization a priority and get ahead of inefficient spending," says Chris Tozzi, adjunct research advisor for IDC's IT Executive Programs (IEP).
Please Note: Extended description available upon request.
- IDC PlanScape Figure
- Executive Summary
- Why Is AI Infrastructure Cost Optimization Important?
- What Is AI Infrastructure Cost Optimization?
- Who Are the Key Stakeholders?
- How Can My Organization Take Advantage of AI Infrastructure Cost Optimization?
- Consider as-a-Service Offerings Tailored for AI
- Share AI Infrastructure with Other Workloads
- Minimize Data Movement
- Train and/or Perform Inference at the Edge
- Use Virtual Machines and Bare Metal Servers Strategically
- Configure Autoscaling
- Use Pretrained Models
- Advice for Technology Buyers
- Related Research
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