The Role of the Sustainability Team in Responsible AI

Introduction

As AI adoption accelerates, companies across sectors face growing expectations to ensure its responsible development and use. AI has the potential to accelerate progress on sustainability efforts, but it also introduces significant environmental, social, and governance risks for companies. The business case is clear: companies that fail to address these impacts face increasing regulatory, reputational, operational, and stakeholder risks, while companies that adopt a responsible approach to their development and use of AI can strengthen stakeholder confidence, reduce barriers to adoption, and create long-term business value.

This FAQ outlines why Responsible AI is a critical sustainability issue and how Chief Sustainability Officers and sustainability teams can influence AI governance at their companies.

What is Responsible AI?

“Responsible AI” refers to a set of practices that companies undertake to ensure that AI technologies benefit society and that risks to people and the environment are addressed.

These practices are informed by two major forces:

The growing number of voluntary AI principles, frameworks, and standards that organizations are adopting globally;
The rapidly evolving regulatory landscape, with governments introducing new laws and requirements related to AI governance, transparency, accountability, and risk management.

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BSR believes that a responsible approach to AI considers the potential benefits and adverse impacts of AI on people and the environment across the company’s value chain over the short, medium, and long term.

Social and environmental impacts are at the core of Responsible AI. These impacts can be the main drivers of corporate risks and opportunities; addressing them is essential to build a meaningful approach to Responsible AI.

What is the connection between Responsible AI and sustainability?

AI presents both significant opportunities and risks for sustainability across social and environmental dimensions:

On the opportunity side, AI can accelerate climate action, improve resource efficiency, and strengthen risk management of complex supply chains.
At the same time, AI introduces real social and environmental risks, including rising energy and water use, job loss, bias and discrimination, and impacts on privacy.
In addition to introducing new risks and opportunities, AI use can also amplify or reshape a company’s existing material sustainability issues. For example, AI-enabled hiring tools may reinforce or exacerbate existing risks of bias and discrimination in recruitment and workforce management.

Like many other technologies, AI can have both positive and negative impacts. The specific impacts that it will have for a particular company depend on how it is designed, developed, deployed, and governed. For this reason, BSR believes AI should be treated not only as a technology issue, but also as a sustainability and governance issue.

Why should sustainability leaders care about Responsible AI?

AI is already influencing sustainability performance across industries, whether companies are actively managing it or not.
AI can help organizations accelerate sustainability goals and processes (e.g., data collection and disclosure), but it can also amplify existing risks and create new impacts that affect workers, communities, consumers, and the environment.
As the capabilities and use cases of AI expand, policymakers, investors, workers, civil society organizations, and customers are increasingly expecting companies to demonstrate responsible governance and oversight, including understanding the impacts, risks, and opportunities associated with AI on the company and the communities where it operates.
Sustainability leaders are well-positioned to help organizations understand environmental and societal impacts and integrate AI into broader company strategies.

What is the role of the sustainability team in Responsible AI?

Responsible AI initiatives are often led by cross-functional groups that include legal, compliance, cybersecurity, and technical teams.

Sustainability teams should also be part of these initiatives, as they bring significant value:

Sustainability professionals bring expertise in identifying and managing strategic impacts on people and the environment, which is central to Responsible AI.
Sustainability teams also have existing tools and processes that can be adapted to AI governance, including materiality assessments, human rights due diligence, stakeholder engagement, grievance mechanisms, foresight to see impacts across different time horizons, as well as ESG reporting and disclosure.
Responsible AI, like sustainability, is inherently cross-functional and requires coordination across procurement, human resources, legal, IT, product, communications, and leadership functions. Sustainability teams have experience coordinating across functions and can bring in learnings to help Responsible AI initiatives succeed.

The role of sustainability teams is to help ensure that Responsible AI governance incorporates environmental and social considerations across different time horizons, and is embedded in broader company priorities.

How can sustainability teams get involved in Responsible AI?

Sustainability teams can begin by identifying whether Responsible AI or AI governance initiatives already exist within the company and seek opportunities to participate.

If no initiative exists, sustainability teams can help convene a cross-functional effort to build out Responsible AI governance. They can leverage existing sustainability and human rights frameworks, which provide a strong foundation for Responsible AI governance.1

Sustainability teams can also support Responsible AI efforts by integrating AI considerations into existing sustainability strategies, materiality assessments, due diligence processes, and business impact and reporting frameworks.