Key Insights – The State of Corporate Sustainability in 2026
The Watershed 2026 survey reveals a sustainability function at a turning point. Corporate sustainability teams are navigating an increasingly complex environment where regulatory pressure and climate ambition are advancing simultaneously. While compliance with emerging regulations remains the primary driver of sustainability programs, environmental impact reduction continues to rank almost as highly, demonstrating that climate action is not merely a response to policy requirements but remains a strategic priority in its own right.
However, a significant disconnect emerges between ambition and operational reality. Sustainability teams spend the majority of their time collecting, validating, and reporting data rather than implementing decarbonization initiatives. Reporting obligations are absorbing a growing share of both budgets and human resources, turning sustainability departments into reporting hubs when many would prefer to focus on delivering measurable environmental outcomes.
This challenge is amplified by the limited size of sustainability teams. Most organizations rely on relatively small groups of professionals to manage increasingly complex ESG requirements, stakeholder expectations, and regulatory disclosures. Although resourcing has remained broadly stable compared to overall company growth, many teams report that sustainability is struggling to compete with other business priorities for investment and talent.
Against this backdrop, artificial intelligence is emerging as a potential enabler rather than a transformative force at least for now. Current AI adoption is concentrated in administrative and data-intensive activities such as data ingestion, quality assurance, and reporting automation. These use cases address some of the most time-consuming aspects of sustainability management, helping teams reduce manual workloads and improve operational efficiency.
Yet the report highlights a clear gap between how AI is currently used and where organizations ultimately want it to create value. Sustainability professionals increasingly see AI as a tool capable of supporting forecasting, supplier engagement, emissions reduction strategies, and decarbonization planning. Nevertheless, adoption in these higher-value applications remains limited. This suggests that the challenge is no longer awareness of AI's potential, but confidence in its outputs and readiness to integrate it into strategic decision-making processes.
Trust emerges as the central obstacle to broader adoption. Concerns around accuracy, reliability, data governance, and privacy consistently outweigh environmental concerns about AI itself. Organizations appear willing to experiment with AI for low-risk operational tasks, but remain cautious when the technology influences regulatory disclosures, climate strategies, or investment decisions. In other words, ambition is advancing faster than trust.
The report therefore suggests that the next phase of AI adoption in sustainability will not be determined by technological capability alone, but by governance. Companies will increasingly require AI solutions that are transparent, auditable, explainable, and developed with sustainability expertise embedded in their design. The future of sustainability AI is likely to depend less on automation and more on credibility.
At the same time, the report calls for a responsible approach to AI deployment. Although AI can significantly accelerate sustainability work, it also carries an environmental footprint of its own, largely driven by the energy consumption of data centers and computing infrastructure. This creates a new challenge for sustainability leaders: leveraging AI to accelerate climate action while ensuring that its deployment remains aligned with broader sustainability objectives.
Ultimately, the report paints a picture of sustainability teams caught between growing expectations and limited capacity. AI is increasingly viewed as the mechanism that could break the reporting bottleneck, freeing professionals to focus on the strategic work that matters most. The real opportunity is not simply to automate reporting, but to shift sustainability functions from measurement and compliance toward prediction, decision support, and decarbonization leadership. The organizations that succeed will be those that combine technological innovation with robust governance, transparency, and human oversight.
Sources
Carlin, D. (2026, January 6). Keeping humans in the loop: Why AI needs oversight in ESG reporting. Reuters. Available online
European Commission. (n.d.). Corporate sustainability reporting. European Commission. Retrieved June 23, 2026, from European Commission
Watershed. (2026). The state of corporate sustainability 2026: AI edition. Watershed. Available online
Articolo di Carlos Lougourou, Sustainability Advisor
