The AI Orchestration Maturity Guide for Data Leaders

The difference between failed AI pilots and shipping AI in production isn’t the model. It’s the orchestration foundation – the context, workflow execution, and continuous evaluation of outputs.

This data leaders’ guide introduces a four-layer AI orchestration maturity model based on live AI workloads at leading organizations. Find out where your organization stands and practical steps to get to the next stage of AI maturity.

You'll learn:

• The four-layers of AI orchestration maturity: AI-assisted data engineering, LLMOps, LLM workflows, and agent workflows
• Real-world examples of data teams operating across each level, including Booking.com, Together AI, and Red Hat
• How to build an orchestration foundation to run AI workloads at scale while controlling token costs and enforcing governance