Day 3 Plenaries

Most organisations are worried about AI. Far fewer have grasped that the risk isn’t only the technology — it’s the people using it. Employees are passing customer data, contracts, financial records and source code into AI tools every day, most of it through personal accounts no one is monitoring. Any one of those moments can become a data-privacy breach, a lost trade secret, or a compliance failure with your organisation’s name on it.

The instinctive response — write a policy, run the annual module — creates a paper trail, not protection. Decades of memory research show that without reinforcement, people forget up to 70% of what they’re taught within a day and as much as 90% within a week. A rule your staff can’t recall is a rule you don’t have.

Genevieve Gilmore has seen this problem from every side. She spent a decade teaching, co-founded 3P Learning and helped scale it to an ASX listing, and served as COO of Learnosity. As CEO & Chief AI Officer of the Global Clarity Foundation, she now studies what actually changes behaviour — and what merely gets ticked off. In this session she shares what Global Clarity’s testing of frontline (BPO) sta2 reveals about how little conventional training is retained, explains the Macquarie University research (supported by Investment NSW) now evaluating this approach, and shows how music, repetition, emotion and AI — including her patent-pending technology — can make safe AI use and data-privacy behaviour genuinely stick.

The session is designed for CEOs, founders, risk and compliance leaders, HR and People teams, L&D, operations and CX leaders — anyone accountable for turning organisational knowledge into consistent, safe behaviour. It is not a product demonstration. It is a practical conversation about the risk hiding in plain sight, and about a measurable way to close it.

Many organizations have successfully experimented with AI. Far fewer have figured out how to make it part of how the organization actually operates.

In this keynote, Dr. Adrienne Heinrich explores what it takes to move from isolated AI projects to an AI-first operating model. She will discuss the foundations needed to deploy AI across products, operations, customer experiences, and the workforce — from data and technology architecture to redesigned workflows, responsible AI, human oversight, and organizational readiness.

The session will challenge technology leaders and developers to think beyond adding AI features and consider a bigger question: How do you design an organization that is built to work with AI at scale?

AI is fundamentally reshaping the economics of global technology delivery. As enterprises increasingly demand business impact, speed, innovation and measurable outcomes – not simply access to talent at lower cost – the basis of competition is changing. At the same time, AI is lowering barriers to entry, creating new opportunities for small and mid-sized technology providers to compete.

This session explores how enterprise expectations are evolving, what the next generation of global delivery ecosystems will look like, and what the Philippines needs to do to capture the next wave of AI-driven technology growth.

Opening & Welcome Remarks

Large language models are widely celebrated as conversational AI — systems that answer questions, summarize documents, and generate code on demand. But what happens when you take the LLM out of the chat window and put it inside an evolutionary search loop? The answer, it turns out, may be one of the most exciting developments in AI-assisted scientific discovery today.

This talk explores a powerful and underappreciated role for LLMs: not as answer generators, but as intelligent mutation engines within evolutionary search frameworks. Drawing on IBM Research’s landmark 2026 paper on LLM-guided quantum error correction code discovery — in which an evolutionary workflow screened over 200,000 candidate codes and identified 465 distinct quantum error correction codes in under 140 hours for approximately US$400 in compute cost — the talk unpacks how this paradigm works, why it is so effective, and where it is headed.

No quantum computing background is required. The talk is structured to be accessible to software developers, project managers, and business leaders, while offering sufficient technical depth to engage researchers and academics.