Analysis on the need for strong governance in AI implementation
- Sylvain Richer de Forges
- May 19
- 1 min read
AI & sustainability series: AI is moving fast - Governance needs to move faster.
As AI becomes more embedded in the way we operate businesses and make decisions, sustainability professionals must ask tough questions:
Who is accountable when AI systems make decisions that impact people and the planet?
How do we ensure AI-driven solutions align with ESG principles?
Are we embedding ethics and equity in every layer of AI governance?
AI has immense potential to advance sustainability, from predictive analytics for climate risks to optimizing resource use. But without strong governance, we risk creating systems that replicate biases, increase energy consumption, and lack transparency.
A few key governance considerations:
- Ethical frameworks: Align AI development with human rights, climate goals, and social equity.
- Data governance: Ensure data used in AI systems is responsibly sourced, unbiased, and transparent.
- Energy accountability: Track and reduce the carbon footprint of AI infrastructure—especially large language models and data centers.
- Cross-functional oversight: Bring together sustainability officers, data scientists, and compliance teams to shape AI governance holistically.
AI is not just a tech issue—it's a sustainability issue.
Let’s make sure we’re building not only smart systems, but responsible ones.
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