Women, AI, and the future of ESG: why diverse perspectives matter

As a young female professional entering the world of Environmental, Social, and Governance (ESG) compliance, I find myself at the intersection of three rapidly evolving domains: technology, sustainability, and regulation. Working at Climate and Decisions, a consultancy that helps organisations navigate Australia's new climate regulations through data, tech, and AI, I have quickly realised how critical diverse perspectives are in shaping the future of ESG.

AI is transforming ESG compliance, making reporting more transparent, automating data collection and identifying risks at a scale previously unimaginable. But as with any technological revolution, the people behind it — those designing, implementing and interpreting AI-driven insights—will determine its success. This is where women's voices must be amplified.

ESG compliance is more than a regulatory checkbox; it is about long-term sustainable decision-making that balances financial performance with environmental and social impact. Research consistently shows that diverse teams make better decisions, particularly critical in the ESG space. Women bring valuable perspectives to risk assessment, governance, and ethical AI development, ensuring that ESG solutions are practical and inclusive.

According to McKinsey, companies with greater gender diversity are 25% more likely to outperform their peers financially. But beyond profit, gender-diverse teams also foster more balanced and ethical decision-making — a crucial factor when developing AI-driven ESG solutions that influence corporate sustainability strategies, compliance frameworks, and investment decisions.

Data and bias

One of AI's greatest strengths in ESG compliance is its ability to process massive amounts of data to detect patterns, predict risks and improve transparency. However, AI is only as unbiased as the data it is trained on. Suppose AI systems are built without diverse input. In that case, they risk amplifying existing biases in sustainability assessments, investment models and corporate reporting.

AI-driven ESG tools rely on historical data to assess corporate sustainability, but if the data reflects past biases, AI models risk reinforcing outdated norms. For example, AI-based ESG rating systems often evaluate governance based on past corporate success. Suppose the data is skewed toward male-dominated leadership teams. In that case, the AI may incorrectly associate them with stronger governance, disadvantaging organisations prioritising diversity.

A similar issue occurred when Amazon built an AI-driven hiring tool trained on past résumés of successful applicants—primarily men. The AI learned to favour male candidates and downranked CVs that included words like "women's" (e.g., "women's chess club") because it did not associate them with past hiring success. Amazon eventually scrapped the tool due to concerns about gender bias (Reuters).

Women in AI and ESG bring a crucial lens to identifying and addressing these biases, ensuring AI models do not reinforce outdated or inequitable norms.

The need for more gender diversity in AI and ESG compliance

Despite AI's growing role in ESG, women remain underrepresented in both fields. "According to a World Economic Forum report, women's representation in AI is only at 30% in the professional realm", and while ESG roles attract more female professionals, leadership positions are still primarily dominated by men. This lack of representation at the decision-making level limits the potential for holistic, inclusive ESG strategies.

• Encouraging more women to enter AI and ESG compliance is not just about equity—it's about improving the quality and impact of decision-making. Women bring unique perspectives in:
• Stakeholder engagement – ensuring AI-driven ESG tools consider social and financial implications.
• Governance and accountability – prioritising ethical AI frameworks that enhance transparency.
• Climate risk assessment – incorporating a broader range of environmental and community impacts into decision-making.

What needs to change

To create a genuinely inclusive ESG landscape driven by AI and data, we need systemic change at multiple levels:

• Education & early career opportunities – More initiatives encouraging women to pursue careers in AI, data science, and ESG compliance.
• Diverse leadership representation – Companies must actively promote women into AI and ESG leadership roles.
• Bias-free AI development – AI systems should be built and audited with gender-diverse teams to mitigate potential biases.
• Policy & regulation – Governments should consider gender impacts when designing AI and ESG compliance frameworks.

As AI continues to shape ESG compliance, ensuring diverse voices—particularly women's—are part of this transformation is crucial.

Our decisions today will influence the sustainability and governance standards of the future. Women in AI and ESG bring perspectives that enhance ethical, transparent, and effective decision-making, ensuring AI-driven ESG solutions serve all stakeholders, not just a select few. By prioritising diversity in AI and ESG compliance, we can build a future where data-driven sustainability decisions reflect the full spectrum of human experiences, not just those of the past.

And in doing so, we create an ESG landscape that is smarter, more just, inclusive and impactful.