Is your practice ready for AI? Honest questions for health leaders.
If you lead a New Zealand healthcare organisation, whether governmental or non-governmental, for profit or not for profit, the pressure to “do something with AI” is understandably immense. There is work your team would gladly spend less time on, and you want to know whether AI could help. Equally, you don’t want to add another system that needs attention without making anyone’s day easier.
A few honest questions about how your practice works can help you get more value from AI before you invest in a tool. This article will help you recognise the problems AI might inherit and decide what to improve first. The readiness scorecard in our eBook, Before You Invest in Digital and AI, will help you explore those signals with your team and assess where you stand.
AI readiness in healthcare starts with understanding that work. Where does it slow down? What has to be corrected? Which steps exist because your systems don’t quite fit together? You can begin answering these questions and taking relatively simple steps before choosing a complex digital tool.
Three familiar signs worth looking for
Start with the workarounds. Someone downloads a report, changes it in a spreadsheet, and sends it to a colleague. Asked why, they say, “We’ve always done it this way.” There may be a good reason. A workaround can protect against a problem the official process overlooks. Understanding that reason helps you decide what to keep and what to change.
Then look for information being entered twice. A referral arrives, its details go into the patient management system, and some are typed again into a tracking spreadsheet. Each copy creates work and another place where records can disagree. Which version does the team trust?
Finally, think about the person who keeps everything moving. Would a key process still work if they were away for two weeks? Their experience is valuable. If a deadline or an exception is managed entirely from memory, that knowledge needs to be made visible before you can decide how technology should support it.
To be clear, these are useful signals, not a judgement on the people doing the work. They point to places where staff may be carrying the effort of keeping a fragmented process together.
What AI might amplify
In the referral example, an AI tool might extract information and populate both records. That could save typing. But it would still leave two records to keep aligned, and it would not resolve who is responsible for moving the referral forward. If the source information was wrong, the error could now reach both places faster.
This is the amplification problem: technology can extend the reach and speed of whatever process you give it. As Ny Brunenberg, Interim CEO, Collaborative Aotearoa discussed in our podcast and eBook “Where the process works well, that can be valuable. Where it’s confused, AI could simply speed up that broken process and make it worse, faster.”
Understanding the process also helps you see where AI could make a worthwhile difference, such as drafting routine correspondence or identifying missing information. You can define a specific job for the tool and judge whether it helps.
Make data governance part of readiness
For leaders considering AI adoption in healthcare, data governance belongs in this conversation from the start. Do you know which information the tool will rely on, whether it’s complete and current, and who is responsible for its quality? Can you explain where it will go, who may access it and for what it may be used?
Accountability also needs to be clear. Agree who checks the output of the AI tool, what they check, and what happens when it’s wrong. Allow time for that review when estimating any saving. Decide what evidence would make you stop using the tool.
Keep the patient or client perspective in view too. A process can become easier for staff while remaining difficult for people facing language, digital access or other barriers. Ask whose experience you need to understand before changing it, including patients and whānau who may not appear in your usual feedback.
A practical next step
You don’t need to resolve everything at once. The eBook suggests blocking 90 minutes with your practice manager or chief operating officer and one frontline staff member. Follow one patient journey from first contact to outcome, recording each step, tool and handoff as it actually happens.
Use the signs discussed here to guide the conversation. Choose one visible delay or workaround to address, give someone responsibility for the change, and make time to review what improved. That gives your team a useful result now and a clearer basis for deciding where AI will earn its place.
Download Before You Invest in Digital and AI for the full readiness scorecard, practical healthcare examples and key questions to work through before you invest. Use it with your team to turn "Are we ready for AI?" into a clear next step.
