Trusted AI Transformation

Overview

As AI moves from innovation to a core business capability, infrastructure shifts from a background concern to a strategic enabler or constraint. As AI use cases scale and deliver value, organizations must recognize the important differences across AI workloads—from building and adapting models to using them in day-to-day operations—each shaping technology and infrastructure decisions with materially different consequences.

Against this backdrop, data sovereignty, regulatory obligations, and the physical distance between data and compute increasingly influence performance and operating costs, were responsiveness drives differentiation.

Drawing on real-world experience across hyperscalers, neo-cloud/sovereign cloud providers, colocation, and on-premise environments, this roundtable examines how leaders are navigating the trade-offs of workload placement as AI scales.

Key Discussion Points:

1. Aligning AI Investment to Business Outcomes

AI infrastructure decisions are no longer technical—they directly determine how quickly and effectively value is realised.

2. Where Data Lives Now Drives What’s Possible

Data location is becoming a strategic constraint, shaping performance, cost, and the feasibility of real-time use cases.

3. Navigating Sovereignty Without Slowing Delivery

Leaders must meet tightening regulatory demands without compromising speed, flexibility, or innovation.

4. The True Cost Curve of AI at Scale

AI doesn’t scale linearly—cost, performance, and usage patterns create new financial pressures that require active management.

5. Retaining Strategic Control in a Multi-Provider World

Avoiding over-dependence on a single provider is now critical to maintaining negotiating power, flexibility, and resilience.

6. From Capability to Operational Discipline

The shift to production AI requires clear ownership, governance, and infrastructure that can support business-critical reliability

What to expect

• Hours
• Discussions Interactive
• Senior Executives 10+

What we will cover

• Aligning AI Investment to Business Outcomes AI infrastructure decisions are no longer technical—they directly determine how quickly and effectively value is realised.
• Where Data Lives Now Drives What’s Possible Data location is becoming a strategic constraint, shaping performance, cost, and the feasibility of real-time use cases.
• Navigating Sovereignty Without Slowing Delivery Leaders must meet tightening regulatory demands without compromising speed, flexibility, or innovation.
• The True Cost Curve of AI at Scale AI doesn’t scale linearly—cost, performance, and usage patterns create new financial pressures that require active management.
• Retaining Strategic Control in a Multi-Provider World Avoiding over-dependence on a single provider is now critical to maintaining negotiating power, flexibility, and resilience.
• From Capability to Operational Discipline The shift to production AI requires clear ownership, governance, and infrastructure that can support business-critical reliability.

Agenda

• 9:00 am Welcome & Check-in | Arrival, Drinks & Networking(Executive Luncheon) Welcome on arrival. Enjoy a moment to connect informally with fellow attendees before the session begins.
• 9:45 am Opening Keynote Address(Executive Luncheon)
• 10:05 am The Australian Playbook: Enterprise AI Stories from Canva, Optus, & Xero(Executive Luncheon)
• 10:45 am Work AI for the Enterprise (Industry Best Practices)(Executive Luncheon) People: Transforming productivity company-wide (15mins) | Lucas Guslani, Enterprise Account Director, Glean Processes: Transforming workflows and driving rapid ROI (15mins) | Aarushi Arya, Solutions Engineer, Glean Platform: Building the architecture for AI transformation (15mins) | Nathan Catania, Field CTO, Glean Unification for Enterprise Context (15mins) | Will Hiebert, Regional Vice President, Glean
• 11:45 am Better Together | Building the Ecosystem for Enterprise AI with AWS, Snowflake and Mantel Group(Executive Luncheon)
• 0:05 pm Q&A with Leadership(Executive Luncheon)
• 0:15 pm Networking Lunch | Event Concludes | Thank You for Joining Us!(Executive Luncheon)

Partners

• Glean · Acquisition Only Glean is the Work AI platform that connects and understands all your enterprise data, to generate trusted answers and automate work grounded in company knowledge. Using Glean’s powerful search and RAG technology to retrieve the most relevant, up-to-date information, Glean's AI assistant generates highly personalized answers based on your company’s unique enterprise knowledge graph. All answers are secure, private, permissions-aware, and fully referenceable back to source documentation in your enterprise. Glean also empowers users to quickly and securely build multi-step prompts and custom generative AI, agents, and assistants that automate everyday workflows. With over 100 connectors, LLM options, and no need for costly professional services, data training, or manual fine-tuning, Glean delivers turnkey implementation of a complex AI ecosystem on one centralized platform. Founded by Arvind Jain (Google Distinguished Engineer, Rubrik Co-founder), T.R. Vishwanath (Microsoft, Meta), Piyush Prahladka (Google, Uber), and Tony Gentilcore (Google), Glean has funding from Sequoia Capital, General Catalyst, Kleiner Perkins, Lightspeed Venture Partners, and The Slack Fund.

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