It’s hot. Everyone’s talking about it. But alongside the rising temperature is another subject demanding attention: how we navigate the rapid rise of AI.

Today, we launch the first in a series of blogs exploring how businesses can deploy AI in ways that serve people, strengthen society, and support a more sustainable future.

Throughout this series, we will explore the pillars of our Framework for Using AI to help organisations approach this transformative technology with greater reflection, confidence and purpose.

We begin with sustainability.

Climate cooperation in a fragmented world

With soaring temperatures in London this week, the topic feels both immediate and relevant. This sense of urgency is also reflected in London Climate Action Week, whose theme this year –Climate Cooperation in a Fragmented World – points to a central challenge: how we work together to address shared issues in a period of rapid technological, political and social change.

AI is becoming an increasingly important part of that conversation, and its impact will depend on how it is developed, deployed and governed.

AI’s sustainability paradox

From one perspective, AI may offer significant potential to help address some of our most pressing environmental challenges. For example, it is improving climate modelling capabilities, optimising energy systems, and enabling organisations to reduce emissions, manage resources more efficiently, and make more informed, data-driven decisions about their environmental impact.

At the same time, AI’s growing capabilities come with rising environmental costs. Training and running advanced models demand significant energy, water and infrastructure, while expanding data centres place increasing strain on natural resources. The hardware that powers AI also drives demand for critical minerals and contributes to growing volumes of electronic waste.

This creates a fundamental paradox: the same technology that may help address environmental challenges can also contribute to them.

For organisations embracing AI at scale, the challenge is therefore not simply how to maximise its benefits, but how to do so while understanding and actively managing its environmental and social costs.

Stewardship matters

The sustainability pillar of our framework is centred on stewardship – a principle that encourages organisations to think beyond short-term gains and consider the broader impact of their decisions.

A stewardship approach invites leaders to reflect on how AI affects not only business outcomes, but also employees, communities, future generations and the environment. Crucially, this mindset recognises that businesses cannot outsource responsibility entirely to governments or regulators. Companies have significant influence over how AI is designed, implemented and governed – influence that carries both opportunity and responsibility.

Sustainability cannot be an afterthought to AI adoption; it must shape the conversation from the outset.

Choosing the future we want

AI and sustainability present a similar challenge: balancing short-term opportunity with long-term impact. Both require organisations to look beyond immediate benefits and consider wider effects on people, communities and the planet, raising important questions about responsibility and accountability.

A stewardship mindset can help address this challenge by shifting the focus from what AI can do to how it is used and the outcomes it may create.

At its core, stewardship sees businesses as custodians of resources, relationships and capabilities. Applied to AI, this suggests using technology in ways that are more likely to support long-term wellbeing, rather than focusing solely on efficiency or growth.

AI may contribute to environmental sustainability and human wellbeing, but these outcomes are not assured. They will depend on the values, governance and choices that shape its use.

The sustainability question

Ultimately, the question is no longer just whether AI can transform our world, but how we ensure that transformation serves both people and planet.

Can AI be adopted at scale in a way that is human-centred, environmentally responsible, socially beneficial, economically viable and sustainable over the long term? How can we ensure that it complements human capabilities and strengthens the institutions and relationships on which society depends?

There are no simple answers. But organisations can begin by asking better questions: not simply how AI creates value, but what kind of value it creates, for whom, and at what cost.