How AI is likely to impact the Chief Sustainability Officer’s job

Chief Sustainability Officer roles appear safe from automation – but AI is already changing CSOs' mandate.

With AI rapidly transforming workplaces, it’s easy to focus on the jobs most at risk. Analysis published last March by the Institute for Public Policy Research (IPPR) warned that up to 8 million UK jobs could be in jeopardy from AI in the coming years, particularly those involving routine and repetitive work. 

But there is some solace for sustainability teams, after a recent study revealed that environmental and sustainability experts are among 12 job areas it believes that automation is unlikely to replace in the UK.

The study by CV builder LiveCareer UK says they are likely to survive the AI cull due to their core strengths and reliance on complex human qualities, which include environmental expertise, ethics and big-picture analysis. Tackling climate challenges requires ethical oversight, systems thinking, and human accountability, the report says.

A complex role anchored in empathy

In fact, these roles – anchored in creativity, empathy, and complex human judgment – are expected not only to survive but to actually thrive in the AI era. The report is based on insights from Deloitte, the World Economic Forum, Oxford Martin School, IPPR, and other leading research on the future of work and automation.

“Adapting to environmental changes, sustainability planning, and community engagement depend on local expertise and creative problem-solving. These professionals translate complex data and scientific findings into actionable policy, which often requires negotiation and consensus-building among diverse stakeholders,” the report says.

However, to assume that AI will have no impact on sustainability jobs would be at best naïve and at worst foolhardy.

Professor Fatima Annan-Diab is Executive Dean at Royal Docks School of Business and Law, part of the University of East London. She believes AI is increasing demand for sustainability professionals, though the nature of roles is shifting. “Global labour data shows demand for green skills consistently outpacing supply, with projections from the ILO and World Economic Forum indicating job creation linked to both the green transition and digital technologies,” she says. 

Less reporting, more integration

Regulatory requirements including the ISSB standards, the EU’s Corporate Sustainability Reporting Directive (CSRD) and the UK’s forthcoming Sustainability Reporting Standards (SRS) are accelerating demand by requiring investor-grade sustainability reporting and assurance, Annan-Diab says.

While AI-enabled platforms are being deployed to automate data collection, improve reporting efficiency, and model risks such as carbon exposure and supply chain vulnerabilities, the CSO role is shifting away from producing disclosures to taking the lead on enterprise-wide sustainability data strategies, she adds. 

“CSOs are also addressing challenges: ensuring data quality, maintaining audit trails, and integrating sustainability considerations into AI governance frameworks. This includes evaluating the ethical and environmental impacts of AI, such as the carbon footprint of data-intensive technologies.”

Within sustainability teams, new skills and responsibilities are emerging and demand for hybrid profiles that blend sustainability knowledge with data and risk management skills are on the rise. The skills to focus on include AI and data literacy, regulatory fluency, carbon and climate analytics expertise, and assurance readiness is rising, Annan-Diab believes. 

“Teams are increasingly responsible for ESG data governance, supplier due diligence, automation roadmaps for carbon accounting, and cross-functional change management.” Rather than spend weeks manually analysing supplier audits, expertise can now be redirected towards higher-value tasks including change management and stakeholder engagement.

CSOs need to become more AI-proficient

Vanezza Scanlon, Affiliate Professor of Social Impact and Sustainability at ESCP Business School London, believes AI is opening up new possibilities to tackle complex challenges at scale, but it also raises hard questions about impact, equity, and responsibility. 

AI is not ‘green’ by default, many CSOs aren’t trained in AI, and many data scientists don’t fully understand the social and environmental systems they’re modelling, Scanlon warns. “It needs governance, transparency, and ethical boundaries, which means asking hard questions about environmental footprint, embedding circularity from the start, checking for bias, and reporting openly on benefits and trade-offs. 

“CSOs don’t need to be AI experts overnight, but they do need to be curious, collaborative, and bold enough to experiment, while staying grounded in human judgement and compassion," Scanlon says.

Read also: What we know – and what we don't – about AI emissions

Yannick Chaze, Co-Founder and Chief Technology Officer of sustainability data platform Sweep says AI is reshaping the sustainability landscape, redefining what CSOs and their teams can achieve, against a backdrop of mounting pressure to meet carbon reduction and other ESG goals. 

“AI isn’t eliminating sustainability managers. It’s expanding their scope, skillsets and accountability,” Chaze says. “By reducing time spent on manual data tracking, teams can focus on strategy, regulatory alignment and actual emissions reduction.

“As a result, the Chief Sustainability Officer’s role is moving from reporter to strategist, and their teams are being asked to deliver insights that will generate value for the business as a whole, not just numbers.”

'It's important to emphasise the human dimension'

Kevin Franklin, CEO of EiQ and Chief Product Officer at LRQA believes for full impact, AI should be layered alongside the deep, technical, human experience within the organisation. “AI can automate significant aspects of due diligence, but with AI becoming embedded in sustainability reporting, supply chain monitoring and risk management, it’s important to emphasise the human dimension.”

Understanding local supplier relationships, union dynamics or ethical trade-offs are the essential elements that AI cannot replicate. The most successful teams will be those that blend human expertise with AI-enabled efficiency, Franklin says.

“CSOs must now act as change managers, guiding their organisations through the cultural and ethical considerations of AI adoption. They must also ensure due consideration is given to the importance of governance frameworks, like ISO 42001 for AI management, to ensure responsible and ethical AI development, deployment and governance.”