The way we live and work is changing very fast. Some days that's exciting. Other days it feels like none of us can keep up.
And it raises bigger questions. What will it mean for our children, our families and the future we're planning for?
As business leaders, we're asking those questions at home too. Our people bring the same questions to work with them, whether they say so or not.
You don't need every answer to take a useful first step. You do need to give people a clearer way forward, and take them with you.
Start by listening
A 2025 University of Melbourne and KPMG study of more than 48,000 people across 47 countries found that 66% were using AI regularly, but only 46% were willing to trust it. Fewer than half of employees (47%) said they'd had any AI training.[1]
Those are global figures, not an Australian workplace survey. But they ring true. People can be interested and unsure at the same time.
A quiet team isn't always a comfortable team. So ask. What's exciting people? What's worrying them? What would actually make their working day better? Then respond to what they actually say.
Be straight with people
Say what you know. Be clear about what hasn't been decided yet, and when people will hear more.
Be careful with "don't worry, it'll make your job easier". If you can't back a promise up, don't make it. People deserve a straight answer, even when that answer is "we haven't decided yet".
Pick one real problem
"We need to do more with AI" gives a team very little to work with. "We spend too long finding information before we can answer a customer" is something people can get stuck into.
Choose something useful enough to matter and small enough to test. Steer clear of anything that affects someone's job, health or access to services until you've learnt a lot more.
Involve the people who do the work
They know where the information is unreliable, which exceptions keep coming up and when a customer needs a person. Bring them in early, including someone keen and someone sceptical. Both will make the result better.
Give them proper paid time to learn and try it. An experiment squeezed into an already full week tells you very little.
Make the rules easy to follow
People need to know which tool they can use, what information stays out of it, who checks the output and how to raise a problem. Australia's National AI Centre guidance makes the same point about accountability and oversight.[2]
Keep the rules simple enough that people remember them.
Measure the whole job
A demonstration makes it all look easy. Real work has scattered information, checking and fixing.
A 2025 study of 5,172 customer-support agents found a 15% average increase in issues resolved per hour, with the biggest gains for less experienced staff.[3] That's one setting. It isn't a promise for every business.
So measure the whole task, including preparing, checking and correcting. Ask the people using it whether their day is actually better. And decide up front what any time saved is for: better service, less overtime, or the work that keeps getting pushed back.
A simple first 90 days
- Days 1 to 15: listen, and pick one problem.
- Days 16 to 30: set up the trial, the rules and the training time.
- Days 31 to 60: run it, with regular feedback.
- Days 61 to 90: review it with the team, then stop, improve or extend.
Stopping is a perfectly good result. It saves money and goodwill before you ask more people to change.
Taking people with us
We can't remove every uncertainty. We can make better decisions about what happens next in our own businesses, and take responsibility for how we bring our people along.
There's a lot to be excited about. People find their own reasons to be excited when they can see the purpose and their part in it.
Where to start
If you're working out where to start, your local, nimble and expert Interfuze team, based right here in Perth, is offering a free one-hour consultation to talk it through. We're also finishing a standard starting roadmap. Reach out now and you'll be among the first to receive it.
If you'd like to go further, we can scope a separate piece of work to understand your business and build a roadmap around it.
Book your free one-hour consultation
Sources
- University of Melbourne and KPMG, Trust, attitudes and use of Artificial Intelligence: A global study 2025. Global, self-reported survey of over 48,000 people in 47 countries, November 2024 to January 2025. Not an Australian estimate. Research summary
- National AI Centre, Guidance for AI adoption: implementation guidance. Practical guidance, not a complete statement of legal obligations. Current guidance
- Brynjolfsson, E., Li, D. and Raymond, L. (2025), Generative AI at Work, The Quarterly Journal of Economics, 140(2). One company's customer-support team, so it may not apply elsewhere. Published paper
The practical steps and the 90-day outline are my own suggestions, not a framework from these studies.
