I just got back from the Google Cloud Summit Sydney 2026, bursting with ideas, a head full of tech, and a very bright pink ‘Human Agent’ t-shirt… Everywhere you looked at the summit, the tech world was racing to showcase autonomous digital agents, next-gen models, and breakneck deployment speeds. It's pretty exciting stuff; however, it's important to note that the biggest gap in AI right now isn’t access to the technology, It’s the discipline to point it at the right problems.
As I took the stage to talk about the people side of technology and how It’s incredibly easy to get caught up in the "new shiny toy" syndrome, my message was clear: you cannot optimise technology until you understand the humans using it. They are the most volatile, unpredictable, and crucial part of the puzzle.
The paradox of the digital magpie
Let's be honest: Humans are weird. But in the context of change management, we are wonderfully weird.
I’ve spent my career working with organisations navigating massive technological shifts, and I’ve noticed a fascinating paradox. Humans are digital magpies. If a tool looks cool and makes our lives easier, we will secretly sign up for it before the IT department can even finish their morning coffee. We love change when we lead it. Yet, the moment a new tool is mandated from the top down, we freeze. We resist change when it happens to us.
Why do we do this? Because deep down, we are intense creatures of habit.
Imagine walking into your local supermarket, and every single aisle has been rearranged. The milk is now by the laundry detergent and the bread is next to the pet food. Your brain doesn't think, "Oh, I love this change!" Instead, it instantly triggers a literal "fight or flight" response. Unfamiliarity breeds immediate fear and distrust.
Now, bring that into the workplace. A well-meaning executive mandates a complex new AI platform. The user’s brain panics, and they quietly retreat to what feels safe: that random, free AI tool their mate showed them over the weekend. They use it because it’s easy, and just like that, you have a Shadow AI crisis. Data starts leaking out of your business simply because the mandated corporate tool feels like a chore and there wasn’t a clear reason why it should be used.
Built-In, not bolted on
One of my favorite takeaways from the summit was a reminder to stop hunting for the next new standalone AI tool. Instead, we need to look at what we already have access to (and are already paying for) and see how it is evolving.
This is exactly why Gemini for Google Workspace is such a game-changer. It doesn’t feel like a forced corporate mandate; it feels like a natural extension of the Docs and Gmail your teams already live in. The AI is built-in, not bolted on.
But deploying the tool is only step one. A digital agent is only ever as good as the Human Agent guiding it. To turn AI from a scary chore into a trusted teammate, you have to tackle three core challenges:
Education: AI doesn't just save time, it fundamentally changes how we spend it. Your team will spend less time generating work and much more time verifying it. If we don't train them to critically check results, we are just automating mistakes at scale.
Data: From research to data science, your AI is only as good as the data you feed it. Building a solid, integrated data foundation on Google Cloud ensures your team gets results they can actually trust.
Trust: If a team doesn't understand the "why" behind a tool, they will ignore it, bypass it, or actively sabotage it. Our job is to make the right way the easy way.
Giving power back to the user: Me, We, Them
To bridge the trust gap, we have to start by changing our language. When I work with companies, the first thing I do is banish corporate buzzwords like "efficiency." To an executive, "efficiency" sounds like profit. To an employee, it sounds like: "You're going to fire me," or "You're going to double my workload."
Instead, we give power and agency back to the users by breaking their workflow down into the Me, We, Them concept, which I first learned about from Prosci:
Me: What work do you want to keep? You are the expert at your job. This protects their professional identity and human agency.
We: What work do you want to keep doing, but need a helping hand with? This identifies the perfect spots for collaborative AI.
Them: What "boring" work do you want to completely hand off to the machine? This eliminates the administrative drag they already hate.
By treating your people like the experts they are, you build true AI Fluency. AI Fluency is less about prompt engineering and much more about professional judgment. It’s about ensuring your team knows exactly where the corporate guardrails are while still giving them the freedom to innovate.
Moving Forward at Speed
The teams winning at implementing new tech right now aren't the ones building the fastest. They are the ones who got clear on what NOT to build, put safety first in high-risk domains, and moved at speed with the right, AI-fluent people on the team.
You can't ban AI, and you can't fight human nature. If your enterprise tools are harder to use than the free public ones, your people will choose the free ones every single time. Your only real option is to provide a safer, better, more intuitive experience.
When you pair a human-centric change management framework with a robust data foundation, you stop fighting human nature and start leveraging it. You empower your users to safely innovate, and you finally unlock the true productivity everyone else is just chasing.
How is your team handling the shift to AI? If you're ready to move past the "shiny toy" phase and build a real, human-centric AI strategy, get in touch with us at Dynamo6. Let’s chat about how to map out your specific Gemini journey.
