"AI in Action" Sets a New Benchmark for Responsible AI Use in New Zealand

It was a sell-out crowd for Enlighten Designs and Deloitte’s AI Breakfast Briefing: “AI in Action: From Governance to Real-World Implementation” — an indication that AI is no longer a boardroom curiosity in New Zealand but a strategic mandate. 

Why This Event Mattered 

The meeting brought together AI experts and business leaders at various stages of their AI journey - ranging from curious newcomers to hands-on practitioners, they were connected with a single shared question: How do we capture the upside of AI while managing the risks? 

The answer came early. As Enlighten Designs' Drishti Ratna puts it, "AI isn't a filler that replaces people; it's a multiplier that supercharges workflows, cuts time on repetitive tasks, and lets staff focus on higher-value work." That framing anchored the conversation in execution: where to start, how to govern, and how to build trust moving AI from proof-of-concept to production. 

Event Highlights 

Verne Roberts: Your AI Is Only as Good as Your Data 

Verne Roberts, Principal of Data & AI at Enlighten Designs, opened with the reality check most organisations need to hear: if your data isn't ready, your AI isn't either. 

He didn't sugarcoat it. Messy data, inconsistent architecture, and loose access controls don't just slow projects. Instead, they become a business risk when models hit production. Without solid data foundations, even the smartest models stumble. 

Verne's talk resonated especially with leaders still working through their data maturity journeys. He offered clear, practical steps for building long-term data agility and confidence. Steps that directly determine AI model performance. 

Key takeaway: Every successful AI initiative starts with a strong data strategy and governance first. Get your data foundations right, and model performance improves while your exposure to error, drift, and leakage falls. 

Deloitte: AI Governance as a Growth Engine 

Next up was Deloitte with a deep dive into AI policy, governance, and risk management - presented by Reenesh Bhana, Partner – Risk & Regulatory Practice, Deloitte and Mariette van Niekerk, AI Lead, Deloitte, they said, is not a brake pedal, but rather a steering wheel.  

They walked through what practical governance actually looks like in practice.  

1. Start by defining acceptable use upfront: privacy boundaries, IP protections, confidentiality rules, and third-party data handling. 

2. Then embed assurance early in delivery: shift left on security, bias monitoring, and provenance checks so you're not bolting on controls after launch.

3. Build accountability into the system with model performance dashboards, audit trails, and escalation paths that tie directly into your existing risk management framework. 

4. Make it repeatable with lightweight operating models that handle prioritisation, risk reviews, change management, and continuous improvement. 

This isn't about slowing down, it's about moving fast without breaking trust. If you can't answer "who signs off, who escalates, and where AI risk sits in our enterprise risk framework," you're not ready to scale.  

In a landscape where regulation is evolving and competitive advantage is increasingly digital, balance matters: 

• Leaders who over-index on experimentation without governance will stall at the first sign of risk

• Leaders who over-index on policy without delivery will watch competitors pass them by 

The path between those extremes is clear: align AI to outcomes, operationalise data governance, define accountability, and keep humans firmly in the loop. 

Key takeaway: Governance is an enabler, not an obstacle. Prepare frameworks and guardrails before deploying AI at scale so benefits aren't undermined by avoidable harms. 

Damon Kelly: Making AI Real - A Recruitment Case Study 

To close out the morning, Damon Kelly, CEO of Enlighten Designs, presented a case study that showcased successful AI works in the real world. 

He shared how Enlighten transformed its recruitment process. What once required 290 hours of manual work now takes just 16 hours. This wasn't about replacing recruiters; it was about freeing them from repetitive, time-consuming tasks so they could focus on what matters most: finding candidates with the right experience and cultural fit. 

The case also highlighted fairness. AI eliminated the inherent bias of first impressions and focused purely on experience and expertise, making the process more objective and equitable. 

Key takeaway: When designed with planning and forethought, AI doesn't replace human judgment—it amplifies it. It gives people time to focus where their insight has the most impact. Explore how AI can transform your workflows. 

Your Next Steps: Build Your AI Foundation Now 

The takeaway for executives is straightforward and actionable: it's time to bring AI into your business strategically—if you haven't already. 

Here's how to start: 

1. Conduct a data readiness assessment to understand where your foundations stand

2. Codify your generative AI policy and assurance checks so governance is embedded, not bolted on

3. Select two high-impact, well-governed use cases to productise in the next quarter 

Enlighten Designs and Deloitte can help you translate AI governance and data strategy into shipped, scalable AI capabilities.