We’re big on AI. It’s helped us (and our clients) run smoother, smarter businesses without the admin overload.
We use it every day - ChatGPT, automation tools, smart schedulers - to tidy up systems, write more engaging content, and get time-wasting tasks off the to-do lists of our clients. If you’ve followed us for a while, you’ll know: we’re not shy about our love for AI!
But there’s something that’s starting to get the attention it deserves: the environmental cost of all that AI power.
AI doesn’t just float around in the cloud. Every time you run a prompt, that request travels to a data centre - basically a massive warehouse of servers that never sleep.
These machines chew through electricity and need constant cooling. Think row after row of humming servers, powered by huge energy systems and cooled with thousands of litres of clean water. It’s easy to forget what’s going on behind the scenes.
And it’s not just about running these systems, it’s about training them too.
Training OpenAI's GPT-3 used around 1,287 megawatt-hours of electricity - about the same as 120 average Kiwi homes use in a year. It also pumped out over 550 tonnes of CO2. That’s like flying from Auckland to London and back… 550 times.
GPT-4, which we use now, is even bigger and more complex. OpenAI hasn’t shared the numbers, but it’s safe to say it uses even more.
So why are we bringing this up?
Because most of the electricity fuelling all this still comes from fossil fuels. And the water used to keep it cool? That’s clean, drinkable water. The kind communities rely on.
We’re helping more business owners than ever bring AI into their day-to-day - setting up smart systems that run in the background and cut down the manual grind. But the more we all use it, the more important it is to understand the impact. And to use it on purpose.
So, we’re doing something about it.
Each month, we donate to environmental projects through the Clean Earth Bundle with B1G1. It’s not a perfect solution, but it’s a step that grows alongside our AI use.
The projects we support, like clean energy, water protection, and ecosystem restoration, directly address the real-world impact AI creates.
We’ll keep using AI, we’ll keep helping our clients do the same, and we’ll keep doing what we can to balance out the load.
You can love AI and still care about the footprint it leaves. In 2025? We reckon you probably should.
Want to be part of the change? Start here:
Back the right causes. Look for projects that actually balance the kind of impact AI makes: clean energy, water restoration, and improving the way digital tools are powered and maintained.
Pick your tools with care. Some companies are leading the way, like DeepMind and Anthropic. And if you're using ChatGPT, keep an eye on what OpenAI is doing to improve how it's built and run.
Use AI where it counts. Automate the repetitive stuff. Speed up the bits that slow you down. Focus your energy where it actually drives growth, and leave the rest out of AI.
Talk about it. Chat with your team. Mention it to your clients. The more we all understand what’s happening, the better our decisions get.
You don’t need to overhaul everything. Just make one smart choice and build from there.
