What We Did To Grow Productivity With AI

Bindi Norwell, Group Chief Executive of ProCare, shared the real-world experience of bringing AI into one of New Zealand’s largest primary healthcare networks. Rather than starting with technology, her team began with people. “We created a leadership playbook. That’s how we started.” For Norwell, the core challenge was not about access to innovation but building an environment where AI could be integrated sustainably, affordably, and with purpose.

She described how ProCare focused first on internal understanding. Leadership alignment came before implementation. Board members were initially sceptical, but that shifted. “We developed a training programme… and they’ve moved from being sceptics to advocates.” With buy-in secured, the organisation brought in an AI expert to audit the business, identifying areas where automation could support staff and reduce admin.

One of the first gains was in general practice support. “Robots are managing GP inboxes, claiming, recalling patients… this is time they’re not spending with their patients.” AI scribes were trialled using off-the-shelf tools like Nabla and Heidi. “It saves about seven minutes per consult,” she explained. “That’s nearly half of the consult.”

Cost and capability were constant considerations. “We realised that developing robots was extremely expensive.” Instead of trying to scale alone, ProCare created a joint venture called Health Accelerator. This allowed them to test and scale automation across multiple practices and share the infrastructure needed to make it viable.

Norwell explained their decision-making framework in simple terms. “If it’s high strategic value but high capability gap, you should partner. If it’s low capability gap, you should build. If it’s low value, just buy it.”

Ultimately, AI at ProCare is about reducing friction, improving staff satisfaction, and freeing up clinicians to focus on what matters. “We’re a cost leadership business. We want to make things easier for clinicians.” She finished with a quote that captures her approach: “The question isn’t whether AI will transform your business, it’s how.”

Takeaways

1. Leadership alignment is the first step.

“We created a leadership playbook. That’s how we started.”
AI initiatives can easily stall if there isn’t alignment at the top. ProCare deliberately educated its leadership team before adopting any tech, ensuring that priorities, expectations, and vocabulary were shared from the outset.

2. Make AI feel like everyday infrastructure.

“AI is just something we do. We don’t even think about it anymore. Like electricity.”
To ensure sustainability, AI needs to be embedded into the organisation’s fabric. At ProCare, AI is treated not as a project or pilot, but as part of how the business runs, just like payroll, Wi-Fi, or email.

3. Use outside experts to map opportunity.

“We brought in an AI expert to audit all the parts of the business.”
Rather than guessing where AI might help, ProCare commissioned an audit to identify specific, high-impact use cases. This external lens helped prioritise opportunities and avoid wasting time on low-yield ideas.

4. Build staff confidence through informal learning.

“My personal favourite is ‘show and tell.’ That’s how I learn.”
Instead of top-down training, ProCare encouraged peer-to-peer sharing through regular internal demos and informal “show and tell” sessions. This built curiosity and demystified AI, making staff more likely to engage with new tools.

5. Upskill your board to remove barriers.

“We developed a training programme… and they’ve moved from being sceptics to advocates.”
Leadership support extended to the board. Rather than assuming directors would get on board, ProCare created structured learning sessions to help them understand AI’s relevance, build confidence, and ultimately back investment decisions.

6. Target admin, not core clinical work.

“Robots are managing GP inboxes, claiming, recalling patients.”
ProCare deliberately avoided clinical decision-making applications and focused instead on repetitive, low-risk admin functions. This reduced resistance from clinicians and delivered measurable productivity gains without regulatory friction.

7. Share the cost of innovation across partners.

“We created a joint venture… so we can test and scale using this.”
By launching Health Accelerator with other organisations, ProCare spread the cost of AI development and created shared infrastructure that enabled innovation across the wider health ecosystem.

8. Apply a build, buy, or partner matrix.

“If it’s high strategic value but high capability gap, you should partner.”
To avoid overextending internal teams or underinvesting in critical areas, ProCare uses a matrix that helps determine the best delivery model, build internally, buy off-the-shelf, or partner strategically.

9. Stay anchored to your strategic focus.

“We’re a cost leadership business. We want to make things easier for clinicians.”
Every decision about AI flowed from ProCare’s identity as a cost-focused organisation. This ensured that AI was a means to reduce admin time and costs, not a distraction from their core service goals.

10. AI adoption is a cultural shift, not just technical.

“It’s really important that people feel supported… so we’re not doing this to them, we’re doing it with them.”
Change management was a critical focus. ProCare made sure staff felt involved in the process, addressing fears about job loss and making the shift to AI feel collaborative, not imposed.