Waipā held its second Tech Series meetup for 2026 last month, tackling one of the biggest shifts facing local businesses right now: how to make AI genuinely useful without getting overwhelmed.
Held at Bridges Church in Cambridge, the session brought together a strong mix of founders, operators and advisors, all looking for practical ways to apply AI in their businesses today.
Facilitated by Rocketspark CEO Grant Johnson, the panel featured three practitioners working at the sharp end of AI adoption.
KL Chan, CEO of Deep Knowledge, challenged the audience to look past automation and cost savings. While those benefits matter, he emphasised that the greater opportunity lies in how AI can enhance products and services, create new offerings, and deliver deeper value to customers.
In particular, he pointed to businesses’ ability to turn their existing data and expertise into meaningful, customer-facing insights. This is a move that can quickly create differentiation and long-term competitive advantage.
When done well, he said, AI doesn’t just make businesses faster or cheaper. It makes them more valuable.
Jordan McFadyen, founder of Done By Nine, brought a practical marketing lens to the conversation and highlighted a common challenge many businesses are already encountering.
As teams adopt AI tools individually, often using their own preferred platforms or prompts, the result can be fragmented communication, inconsistent tone of voice, and more work rather than less.
He shared a real-world example from a workshop with Vic Health in Melbourne, where a 15-person communications team had each developed their own way of using AI tools. The outcome was a disjointed brand voice and significant time spent manually correcting content before it could be published.
The solution wasn’t to pull back from AI, but to be more intentional about how it is used.
Jordan’s advice was to systemise AI within organisations: building shared structures such as custom GPTs, Claude projects, or centralised prompt libraries that allow teams to work from the same context and guidelines.
In short, if AI is part of your workflow, it needs to reflect your brand just as much as your people do.
Jeremy Johnson, co-founder and Chief Product Officer at Rocketspark, shared how AI is fundamentally changing the way software is built.
One of the biggest shifts has been in how quickly teams can move from an idea to something tangible. Product managers and designers are now able to build fully interactive prototypes without needing to write code, allowing ideas to be tested with real customers before any engineering time is invested.
This not only speeds up development, but also reduces the risk of building the wrong thing.
He also highlighted the growing role of AI in capturing and applying team knowledge. At Rocketspark, project meetings are transcribed and combined with decisions, specifications and current status updates, creating a shared, centralised context. AI sits over this as a kind of “digital brain” for each project, helping shape development and keep teams aligned.
As Jeremy noted, having strong context dramatically improves the effectiveness of AI tools, and in some cases, the AI ends up with a more complete picture of the project than any single individual.
Importantly, he reinforced that AI is not replacing developers. If anything, their role has become more critical, acting as quality gatekeepers across code, security, privacy and long-term performance.
While the shift has been exciting, it hasn’t been without its challenges. Historically, the gap between product teams and developers could feel significant, but AI is beginning to close that divide.
The Q&A session surfaced another theme many in the room were grappling with: the question of control.
As AI tools become more embedded in day-to-day work, concerns around privacy, data security, and appropriate use are growing. Many businesses are still working out how to ensure staff use AI tools safely, particularly when it comes to sensitive company or customer information.
There was strong agreement that policies, guardrails, and education are still lagging in adoption, and that closing this gap is an important next step for most organisations. While not always easy for smaller businesses, taking the time to develop clear policies is essential. Encouragingly, AI tools themselves can help draft and shape these policies.
Alongside this sits a broader challenge: the AI knowledge gap. While some teams are moving quickly, others are still unsure where to start, creating uneven capability within organisations.
Despite the complexity, the overall tone of the evening was pragmatic and encouraging. The panel reinforced that businesses don’t need large budgets or technical teams to make progress with AI. What matters more is starting with clear use cases, being deliberate about how tools are introduced, and putting simple structures in place early.
Attendees stayed on well beyond the scheduled close, continuing conversations, sharing how they’re already experimenting with AI, and comparing notes on what’s working and what’s not.
It’s a strong signal that while AI can feel complex, the appetite locally is not just to understand it, but to actively use it.