With all of the disorientation around AI right now, there are some things that are constant. Executive leaders must show quantifiable value from your agentic AI investments to receive sustained funding.

But they face two big problems:

1. The cost and value of AI agent use cases at scale are highly unpredictable.
2. The operational, interim and outcome metrics and frameworks normally used to justify technology investments — especially conventional ROI calculations — do not fully reflect the unique cost and value dynamics of AI-agent-powered workflows.

In this report from Gartner, you’ll discover the hidden cost drivers that cause budget overruns, learn about the different vendor pricing models, and understand next-generation metrics like agent value multiple (AVM) and context memory optimization score (CMOS) — just to name a few.

Download the report to gain the skills and insight needed to demonstrate quantifiable value, secure sustained funding, and successfully scale AI agent deployments across your organization.

Our key takeaways from the report:

• Avoid the 70% failure rate of AI agents with proven cost management strategies specific to agentic AI deployments.
• Master lifecycle budgeting beyond licenses — including integration, governance, data management, and business transformation.
• Compare vendor pricing models (consumption-based, conversation-based, outcome-based) to minimize cost escalation risk.
• Implement next-generation metrics (AVM, ACCT, CMOS, ECU) that accurately reflect AI agent workflow economics.
• Convert productivity gains into financial outcomes with frameworks for harvesting time savings as realized ROI.
• Reduce costs by up to 60% and increase accuracy by 80% through AI-ready data and semantic optimization strategies.