AI Orchestration in the World's Most Complex Markets

Most enterprise AI never makes it out of pilot. MIT's State of AI in Business 2025 report found that 95% of corporate GenAI projects fail to deliver measurable business value, and in the world's most complex markets, where languages, regulation and scale collide, the gap between demo and production shows up faster than anywhere else. The next five years won't be won with more AI tools. They'll be won by the operating layer that runs them. In this session, we share three principles for the shift from operations to orchestration, illustrated with four real customer stories running in production today:

• 1. The Operating Layer: Stop buying point AI tools and start running an orchestration layer. A single platform that integrates agentic AI, automation and human expertise, modular by industry, governed across the full workflow, live in dozens of regulated environments today.
• 2. Data as the Spine: Treat data as production infrastructure, not the project byproduct. Build the full lifecycle, from collection and validation to annotation, labelling and MLOps, into the platform itself, so every model trained downstream runs on accurate, governed data that is ready for production.
• 3. Hybrid by Design: Replace the binary of "human or AI" with a workforce model where agentic AI handles the volume and human expertise handles judgment, escalation and accountability, proven across hundreds of thousands of operators and 170+ markets.