Many IT organizations today face hurdles to unlocking new business opportunities with AI. Some core challenges they face include lack of standard internal configurations for AI/ML infrastructure, proliferation of shadow IT testbeds, and delays in production deployment. These obstacles not only impede progress, but also have profound business implications such as slower experimentation, delayed production deployment, decreased productivity, and increased infrastructure spending.To address these challenges, organizations must focus on building standards and automation. This includes:
- Providing standardized AI/ML workbenches
- Establishing standard landing zones for AI/ML applications
- Implementing automated policies for cost control (and FinOps, if applicable) by streamlining infrastructure management and empowering developers and data scientists
Join Rama Ponnuswami, worldwide GTM Specialist for AI/ML at AWS, and Anirban Chatterjee, Head of Product Marketing at Rafay Systems, as they explore practical strategies for overcoming IT challenges and driving business growth through AI/ML adoption.
Trusted by leading enterprises and service providers
