ClearPoint Product Owner and Senior Experience Designer, Aleksandra Ovalle shares her insights from the recent M2 AI Summit on AI adoption, human enablement, and product strategy for leaders navigating emerging technologies.
Earlier this month, Aleksandra had the pleasure of attending the M2 AI Summit in Auckland – a full-day event packed with local and global speakers exploring the real-world impact of AI across industries. As someone who's spent the past year weaving AI into design and product workflows, she was particularly interested in hearing what themes would emerge from the people shaping this space.
There was plenty to take away. Whether you were deep in data infrastructure or just starting to explore AI's potential for your business, there was something for everyone. Here are five big themes Aleksandra took away, shaped by ClearPoint's position as a sponsor and her own lens as a Product Owner and Senior Experience Designer.
1. Human Enablement & AI as a Co-Pilot
Across multiple talks, the clearest message was this: AI should empower people, not replace them.
We heard from ProCare's Bindi Norwell about reducing admin for frontline clinicians using AI scribes and digital assistants. Annie Johnson drove home the power of enablement – removing roadblocks between decisions, not just automating workflows. Humaneer showcased how AI can enhance collaboration without removing the human touch. Dr. Peter Catt framed it perfectly, "The tools are here, what's missing is confidence.”
Many businesses feel stuck not because they lack technology, but because they don't yet trust it. This is where good design, change management, and product thinking come in.
Why it matters: If you're a leader trying to empower your teams or customers with AI, you're not alone. Start small, build trust, and keep humans at the centre.
2. Trust, Consent & Transparency
Dermot Butterfield's talk made something very clear: the era of opaque data practices is ending.
New regulations (like New Zealand’s upcoming CDD, Customer and Product Data Bill) mean organisations must design consent into the flow of data use, especially when AI is involved. This isn’t just about compliance – it’s about earning trust.
Examples like explainable AI models, adaptive credit scoring, and clear consent dashboards were highlighted as emerging best practices.
Why it matters: If your product touches sensitive data, you’ll soon need to prove not just what you do, but why. Design for transparency now, before customers demand it.
3. Buy, Build or Partner?
Bindi Norwell offered a simple but powerful framework for AI investments: use a value vs readiness matrix to decide when to build, buy, or partner.
This approach helped ProCare roll out five AI "robots" to reduce clinician admin, while also working with external partners when needed. It's a practical lens for any business trying to stay focused.
Why it matters: Not every AI idea needs a custom build. Sometimes the most brilliant move is to test quickly with an off-the-shelf tool, learn fast, then decide where to go deeper.
4. Creative Use of Emerging Tools
From retail agents to broadcasting to autonomous UX assistants, the showcase of AI-powered experiences was broad and exciting.
We saw and heard:
- TVNZ creating personalised ad experiences from live content.
- Wych working on hyper-personalised financial journeys with consent-first data design.
- Leni Ayoub talking about AI agents that know your preferences and let you own your data.
Natural language input, multi-modal interactions, and integrated agents are fast becoming the norm.
Why it matters: This is no longer theory. As product teams, we must experiment and design with these tools to stay ahead.
5. A Kiwi Opportunity to Do It Differently
The surprise final speaker of the day, Professor Michael Witbrock, offered a refreshing shift in tone.
Rather than focusing on productivity alone, he challenged us to think about AI for social good — urging New Zealand to lead not by scale or speed, but by ethics, empathy, and collaboration. He highlighted our unique conditions: a connected population, strong public systems, and a culture that can balance ambition with fairness.
Mark Bregman echoed this sentiment, emphasising that innovation is deeply human. His call was clear: New Zealand has the ingredients to be a global leader in meaningful innovation — not just because of tech talent, but because of our collaborative culture. He encouraged us to turn up the dial on generosity, trust, and openness, pointing out that real breakthroughs come when we stop treating others as competitors and start treating them as co-creators. He said this phrase that resonated with me: "Innovation is human in depth.”
Together, their message was energising: we don’t need to copy Silicon Valley — we can forge our own path. If we design intentionally, New Zealand could lead the way in creating AI systems that not only optimise outcomes, but reflect the kind of society we want to live in.
Why it matters: This is a powerful call to action. If we can lead with values and collaborate across disciplines, New Zealand could become a model for how to build an AI-enhanced society — not just AI-powered tools.
Final thought
The M2 Summit made it clear: AI is no longer just the domain of engineers or early adopters. The tools are here. The conversations are shifting from hype to how.
Whether you're leading a team, advising clients, or building new ventures, this is a moment to explore boldly and design with care.
If you're not sure where to start, that's okay. Start by asking better questions. We're all learning as we go.
