AI meets Climate: Can technology save the planet or make it worse?

Artificial Intelligence is everywhere, from powering chatbots to predicting climate patterns. At the same time, ESG (Environment, Social, and Governance) has become a yardstick for whether businesses are building a sustainable and fair future. Put them together and you get one of the most powerful and controversial combinations of our time.  

Can AI truly help us fight climate issues, protect biodiversity, and build more inclusive societies? Or will it deepen the inequalities, drain resources, and erode trust?

As organisations race to embrace AI, ESG practitioners face a critical question: Is AI the ultimate sustainability accelerator or a new risk we can’t afford to ignore?

What is AI & Why does it matter for ESG?

According to OECD, Artificial Intelligence (AI) is a machine-based system that, for explicit or implicit objectives, infers from the output it receives how to generate outputs such as predictions, content, recommendations, or decisions that influence physical or virtual environments. 

To better understand AI, let’s break it down into categories:

• Narrow AI systems are designed and trained to perform a specific task, like facial recognition.

• General-purpose AI systems that are designed and trained to handle a broad range of tasks and are therefore flexible, like Microsoft Copilot.

• Gen AI is a subset of general-purpose AI that develops AI models with the capability to generate content such as images, texts, and other media, like ChatGPT.

Beyond these, there is Responsible AI (RAI), a practice that ensures AI is developed and used in ways that benefit individuals, society, and the environment, while minimising risks such as bias, privacy violations, and unintended harm.

And this is where ESG comes in. As organisations push forward with the adoption of AI, the real question is not what AI can do, but how it can be used to accelerate sustainability and social impact without creating new risks.

How AI is Powering Sustainability

With the world racing towards net zero by 2050, time is our scarcest resource. Achieving global sustainability goals requires action at a speed and scale that traditional methods alone cannot deliver. This is where AI jumps in as a game-changer.

By harnessing vast amounts of data, AI can accelerate and scale ESG outcomes, from cutting carbon emissions and protecting the ecosystem to improving inclusion and safeguarding communities.

• Climate Action & Energy Efficiency

AI is helping energy systems become smarter and more efficient. In the United States, AI tools are being used to optimise existing electricity grids, freeing up an estimated 100 gigawatts of capacity, approximately 13% of peak demand. That means lower emissions, fewer blackouts, and faster integration of renewables like wind and solar.

• Protecting Nature & Biodiversity

AI-enabled satellite imagery and geospatial mapping are transforming how we monitor deforestation, soil health, and water systems. In Australia, a collaboration between CSIRO, Google, and The Nature Conservancy is using AI to restore giant kelp forests, which can capture up to 20 times more carbon per acre than land forests. This is a powerful reminder of how AI can amplify nature-based solutions.

• Social Good and Inclusion

AI isn’t just about the environment; it’s also tackling hidden social issues. On the accessibility front, apps like Be My Eyes connect blind and low-vision users with corporate representatives through AI-powered platforms, making customer service more inclusive.

From optimising energy grids to protecting vulnerable communities, AI is proving it can scale sustainability solutions faster than ever before. But as we’ll see next, the same technology that can accelerate progress also introduces new risks that ESG practitioners cannot ignore.

The Dark Side of AI: Risks ESG Practitioners must watch

AI has the ability to scale rapidly, process massive volumes of data, and deliver insights at unprecedented speed. But this very power also comes with a long list of risks. From bias and privacy infringements to hallucinations (false outputs), surveillance, fraud, human rights abuses, job dislocation, and even business model disruption, the downsides are both real and material.

• Bias & Human Rights Concerns

AI systems are only as good as the data they are trained on. Poor-quality or biased datasets can reinforce discrimination, whether in hiring, credit decisions, or access to healthcare. At its worst, AI can also be misused for surveillance and censorship, infringing on basic human rights.

• Environmental Costs of AI

Ironically, while AI is deployed to tackle climate change, it also contributes to environmental strain. Training large AI models consumes enormous amounts of energy and water, while the hardware behind them creates mounting e-waste. In 2019, the world generated 53.6 million tonnes of e-waste, but less than 20% was properly recycled, a challenge ESG teams will need to factor into reporting. 

• Rising Regulatory & Transparency Pressure

Government and regulators are stepping in to set guardrails. The EU has passed an Artificial Intelligence Act, mandating trustworthy and human-centric AI. Australia has introduced its Voluntary AI Safety Standard. Companies will soon be expected to disclose not just their sustainability performance but also how they use AI responsibly.

In short, AI can be both a catalyst and a risk multiplier. The challenge for ESG professionals is to embrace the opportunities while putting safeguards in place, a balance that lies at the heart of Responsible AI.

Responsible AI - The Bridge to ESG

Australia has been proactive in shaping the conversation around Responsible AI. The government has released a Voluntary AI Safety Standard and embedded AI Ethics Principles that emphasise human-centered values, fairness, accountability, and environmental well-being. These principles align strongly with ESG, giving organisations a clear framework to ensure AI serves society and the planet, not just efficiency and profit. 

It’s important to note that Responsible AI is not a technology; it is a practice. It’s about how organisations design, deploy, and govern AI systems so they deliver benefits while minimising risks. In other words, Responsible AI is the discipline of applying ethical, social, and environmental considerations to technology through its lifecycle.

This makes it a natural extension of ESG, which already deals with balancing opportunity and risk for long-term value creation.

Why ESG Practitioners are Key

ESG professionals are uniquely equipped to guide the responsible use of AI. Their skills in human-centred design, systems thinking, and stakeholder trust are exactly what’s needed to embed Responsible AI practices into corporate culture. By applying the same frameworks they use for climate risk or supply chains, ESG teams can help organisations govern AI with credibility.

Responsible AI is ESG in action. It turns abstract ethics into measurable governance, safeguards against harm, and ensures technology supports, not undermines, sustainability goals.

Where do we go from here?

AI is not a passing trend; it’s a permanent part of how organisations will operate in the future. For ESG practitioners, this means embracing AI not just as a tool, but as a responsibility. The challenge ahead is to harness its potential while ensuring it aligns with the sustainability values. 

Here are a few practical steps that companies can take today:

1. Build Awareness and Transparency

Start the conversation inside your organisation. Map where AI is being used and openly communicate its potential risks and benefits. Transparency builds trust with employees, investors, and communities. 

2. Integrate AI into ESG Reporting

Treat AI just like any material issue. Consider its environmental footprint (energy, water, e-waste), social risks (bias, accessibility), and governance challenges (accountability, disclosures). Make it part of your sustainability reporting, not a separate silo.

3. Adopt Responsible AI Practices

Follow frameworks such as Australia’s AI Ethics Principles or the EU’s AI Act. Develop internal guardrails for fairness, accountability, privacy, and environmental well-being. Responsible AI should become a governance practice embedded in business strategy.

4. Use Tools like AI Impact Navigator

Frameworks such as the AI Impact Navigator (developed by Australia’s National AI Centre) can help organisations assess the positive and negative impacts of AI across four dimensions:

• Social licence & corporate transparency 

• Workforce & productivity 

• Community impact 

• Customer experience & rights

AI Won’t Save The Planet Alone, But ESG Can Make Sure It Helps

AI is here to stay. It can accelerate the progress on climate action, biodiversity, inclusion, and governance, but it can easily deepen risks if left unchecked.

That’s why ESG practitioners have a unique responsibility: to make sure AI serves people, planet, and prosperity, not just profit.

The future isn’t about choosing between AI and ESG; it’s about making them work together.