AI Adoption in Corporate Sustainability Functions Reveals Significant Value Despite Implementation Challenges

September 20, 2025

Source: BSR Corporate Sustainability Report, 17th September 2025

Story Synopsis

A new research brief from BSR (Business for Social Responsibility) reveals that corporate sustainability teams implementing artificial intelligence are discovering substantial productivity gains, novel insights, and strategic value. The research, based on interviews with 20 corporate sustainability teams across various industries and regions in August 2025, indicates that most sustainability leaders anticipate AI will significantly transform their work within the next 12 months.

However, these benefits are emerging unevenly across organisations, with numerous challenges persisting around data quality, responsible use protocols, and internal capacity. The majority of sustainability leaders expressed concern about their teams’ readiness, with only a minority believing they currently possess the necessary skills to fully leverage AI capabilities.

Industry Impact Analysis

The research highlights a growing divide between organisations with advanced AI implementation in sustainability functions and those just beginning their journeys. Early adopters are gaining competitive advantages through enhanced reporting capabilities, more sophisticated scenario planning, and deeper stakeholder engagement.

Harvard Law School’s Forum for Corporate Governance has ranked AI as the tenth most important corporate sustainability priority for 2025, reflecting its growing significance despite mixed perspectives on implementation challenges. The research indicates substantial variation in both understanding and access to appropriate tools across organisations.

The sustainability data foundation appears to be a critical differentiating factor. Companies with robust sustainability data infrastructure can rapidly leverage AI capabilities, while those with fragmented or inadequate data systems struggle to realise meaningful benefits despite similar technology investments.

This emerging capability gap has implications for regulatory compliance, particularly as reporting requirements become more stringent and data-intensive. Organisations with AI-enhanced sustainability functions demonstrate greater agility in responding to evolving disclosure mandates.

Business Implications

For sustainability teams, the practical implications are substantial. Those successfully implementing AI report significant efficiency gains in compliance reporting, allowing reallocation of resources toward more strategic initiatives. Enhanced data analysis capabilities enable more sophisticated risk assessment and opportunity identification.

However, implementation challenges remain significant. Many organisations lack sufficient training programmes and supportive cultural environments for AI adoption. The research indicates that teams encouraging experimentation, embracing AI tools, providing consistent feedback, and creating safe learning environments achieve faster uptake.

Governance frameworks emerge as critical success factors, with leading organisations establishing responsible AI guidelines based on ethics, human rights approaches, or combinations thereof. These principles-based frameworks provide flexibility in responding to rapidly evolving technology while maintaining appropriate safeguards.

Talent implications are particularly noteworthy, with sustainability teams increasingly requiring hybrid skill sets combining domain expertise with technological literacy. This is driving changes in recruitment strategies, professional development programmes, and organisational structures within sustainability functions.

Stratagem Partners Perspective

The uneven adoption of AI across sustainability functions reveals a critical insight: technological implementation alone is insufficient. Organisations achieving the greatest value demonstrate a thoughtful integration of technology, process redesign, and cultural adaptation.

The persistent data quality challenges highlight the importance of foundational work before advanced AI implementation. Organisations should prioritise establishing effective sustainability data infrastructure—including standardised metrics, integrated systems, and clear data governance—before extensive AI deployment.

Most compelling is the potential for AI to elevate sustainability from a compliance function to a strategic value driver. By automating routine reporting and improving analytical capabilities, sustainability teams can shift focus toward scenario planning, innovation opportunities, and strategic partnerships that create competitive advantages through sustainability leadership.

The emerging governance frameworks for responsible AI use in sustainability functions offer valuable models for other organisational domains. By establishing principles-based approaches that balance innovation and ethical considerations, sustainability teams are creating governance templates that could inform broader organisational AI strategies.

For more information contact Gabriel D'Arcy Ray Nulty Ankit Kumar Das Rita Barcoe Smriti Das