Your AI Footprint: A Growing Challenge Enterprises Can't Ignore

The rapid rise of AI is bringing incredible innovation, but it also comes with a significant and escalating environmental cost.  

Did you know data centres in Ireland already consume over 20% of the country's electricity?

And the carbon emissions from AI chip manufacturing skyrocketed in 2023 alone. Globally, some estimates suggest AI's energy consumption could rival a country the size of the Netherlands by 2027.

This isn’t just a distant concern. Closer to home, New Zealand's energy emissions have been rising. Data centre demand is expected to surge, with one report forecasting a 50% increase in global power needs by 2029, mostly driven by AI. Meanwhile, the country’s renewable energy mix is becoming less reliable, with hydro electric output falling and coal usage rising during dry or high-demand periods.

As our digital infrastructure grows, so does its environmental footprint.

Why Your Digital Strategy Has a Carbon Cost

For enterprises committed to sustainability, this is not just an IT problem. It is a strategic imperative.

Digital transformation is often viewed as inherently efficient, but every digital process carries a carbon cost. This is especially true when those processes are powered by AI. Each model trained, each data-heavy workload, each tool integrated into your systems adds to your emissions profile.

Yet most organisations are not even measuring this impact. That means they are missing a key opportunity to align their technology strategy with their climate goals.

What AI Emissions Look Like in Practice

If your business uses AI models licensed from external providers (like OpenAI, AWS, or Azure), the emissions from their compute power fall into your Scope 3 footprint. Measuring this often involves tracking API calls, inference requests, or usage metrics provided by the cloud provider.

This footprint expands further when you factor ininternal use of AI tools embedded in everyday workflows. From Microsoft Copilot to AI-powered CRM and marketing platforms, these systems may be invisible in your reporting today, but they generate emissions that matter.

Without visibility, you are likely underestimating both your environmental impact and your opportunity to reduce it.

How to Measure and Manage Your AI Footprint

Businesses need to be actively measure and manage their AI emissions:

1. Be Aware & Measure:

• First, understand your AI's carbon emissions and water use. You can't improve what you don't measure!
• Be open about your impact and set goals to shrink it.

2. Smarter AI Models:

• Keep it Lean: Use smaller, simpler AI models when possible. They need way less power than huge, complex ones.
• Fine-tune, Don't Start Over: Instead of building new AI from scratch, take existing models and tweak them for your needs. It's much more efficient.
• Efficient Training: Stop training models as soon as they're good enough. Every extra minute wastes energy.

3. Choose Green Infrastructure:

• Renewable Energy: Pick cloud providers and data centres that run on 100% renewable energy.
• Smart Scheduling: If you can, run big AI jobs when the energy grid is "cleanest" (e.g., when there's lots of solar or wind power).
• Efficient Hardware: Use specialised AI chips that are designed to do more with less energy.
• Water-Saving Data Centres: Push for data centres with advanced, water-efficient cooling systems.

4. Build a Green AI Culture:

• Educate Teams: Teach your AI developers and data scientists about sustainable practices.
• Make it a Priority: Encourage and reward teams that build more environmentally friendly AI solutions.
• Work Together: Collaborate with partners and suppliers to reduce AI's impact across your entire business.

Turning Awareness Into Action

AI is transforming the way businesses operate, but it's also reshaping your emissions profile. If you're not measuring the environmental impact of your digital tools, including AI, you're missing a critical part of your carbon footprint.

The good news is that you can take action. Start small, focus on what you can measure, and build toward smarter, cleaner AI use across your organisation. Sustainability and innovation can work together, but only if you make it a priority.

Your AI footprint is already growing. Let's make sure it's measured and managed.

Talk to us about building it into your decarbonisation plan.