As organisations accelerate investment in agentic AI, the conversation is shifting from potential to performance. While early use cases promise efficiency and transformation, many are discovering that the true cost of building, deploying, and scaling these systems is far more complex than anticipated. From token usage and infrastructure to integration, maintenance, and governance, costs accumulate quickly, often without a clear understanding of how value is measured or realised. At the same time, many organisations are still struggling to define what "ROI" actually means for agentic AI, or how it compares to simpler alternatives like automation or traditional machine learning. This panel brings together leaders to share a more transparent view of what it really takes to make agentic AI deliver measurable business impact.
• Understand the full cost structure of agentic AI, from experimentation through to enterprise-scale deployment
• Evaluate ROI in context, comparing agentic AI to automation, traditional AI, and alternative approaches
• Identify where value is genuinely realised across efficiency, cost reduction, and operational performance
• Build a realistic framework to track, measure, and optimise ROI over time, not just justify initial investment