AI Systems Scale

Overview

AI is moving from isolated models to integrated systems embedded across enterprise platforms. For technology leaders, the challenge is no longer building AI capabilities, but making them reliable, scalable, and operational across complex environments.

This roundtable will explore how organisations are designing AI systems that can scale across infrastructure, data, and applications without breaking performance, cost, or control.

Discussion Points

• From Models to Systems – Moving beyond standalone AI tools to system-level integration across enterprise platforms.

• Scaling Infrastructure – What it takes to run AI reliably across cloud, data, and hybrid environments.

• System Interoperability – Connecting AI across tools, APIs, and legacy stacks without fragmentation.

• Cost vs Performance – Managing scale without losing control of cost, latency, and efficiency.

• Built-in Governance – Embedding security, compliance, and observability directly into AI systems.

• Pilot to Production Gap – Why most AI pilots fail to scale, and what changes in system design when they do.

What to expect

• Senior Executives 10+
• Hours
• Discussions Interactive

Agenda

• 11:45 am Delegate arrival & registration(Executive Luncheon) Welcome on arrival. Enjoy a moment to connect informally with fellow attendees before the session begins.
• 0:00 pm Welcome drinks & refreshments(Executive Luncheon) networking break with light refreshments as we prepare for the session ahead.
• 0:15 pm Opening remarks(Executive Luncheon) An introduction to today’s topic and discussion focus: • Why AI is shifting from tools to enterprise-scale systems • The real bottleneck: scaling, not building AI • What “AI Systems Scale” means for technology leaders in 2026
• 0:30 pm Interactive discussions(Executive Luncheon) From Models to Systems • Embedding AI into core platforms, not side experiments • Reducing fragmentation across tools and teams Scaling AI Infrastructure • Running AI workloads across cloud, hybrid, and legacy environments • Managing performance, reliability, and operational complexity at scale Cost, Control & Governance • Balancing AI scale with cost efficiency and predictability • Embedding security, compliance, and observability into systems
• 1:45 pm Closing remarks(Executive Luncheon) A brief summary of key takeaways and insights shared during the discussion. • Key takeaways from scaling AI systems in the enterprise • What separates successful scale from stalled pilots • Next steps for operationalising AI systems across the organisation
• 1:50 pm Networking drinks & end of session(Executive Luncheon) An opportunity to continue conversations in an informal setting to wrap up the session.

Partners

• Canva

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