Programme Overview
Across the global economy, the sustainability agenda is accelerating at the same time as corporate AI adoption is scaling fast creating a new Board mandate: governing how AI is used to produce sustainability insight, decisions, and disclosures that investors and regulators can trust. The climate context is stark: global greenhouse gas emissions reached a record 57.1 GtCO₂e in 2023 (a 1.3% increase year-on-year), underscoring why transition planning, data integrity, and execution credibility are now core governance issues rather than CSR conversations.
At the same time, Boards are navigating a rapidly shifting risk environment where information integrity is under pressure. The World Economic Forum’s Global Risks reporting continues to rank misinformation and disinformation among the top short-term threats, while extreme weather remains a leading risk, highlighting how weak information governance can amplify both climate and operational risk. For listed companies, this matters because sustainability narratives and AI-enabled communications can quickly become reputational exposures if claims outpace evidence.
AI adoption is no longer experimental for many organisations and that changes the expectations of Boards. McKinsey’s global survey reported 65% of respondents said their organisations are regularly using generative AI (early 2024), reflecting how quickly AI is entering core processes, including analytics, risk, operations, and reporting workflows. For sustainability functions, AI is increasingly used to support activities such as emissions estimation, scenario analysis inputs, supplier risk screening, anomaly detection in datasets, and drafting narrative disclosures often through a mix of internal tools and third-party platforms.
However, credibility and assurance readiness are becoming the differentiator. PwC’s global investor findings show 94% of investors believe corporate sustainability reporting contains unsupported claims, and in PwC’s 2024 investor survey, 44% said that to a large or very large extent sustainability reporting contains unsupported claims, while 73% want assurance reporting detail comparable to financial audit-style assurance. This sets a clear bar for Boards: if AI is used in sustainability reporting, directors must be confident about data lineage, assumptions, controls, limitations, and audit trails or risk accusations of greenwashing and governance failure.
In Malaysia, this shift is being institutionalised through sustainability reporting reform aligned to ISSB standards. The National Sustainability Reporting Framework (NSRF) phases in adoption of IFRS S1 and IFRS S2 for corporate Malaysia, starting with large Main Market issuers (RM2 billion market cap and above) in 2025, extending to other Main Market issuers in 2026, and ACE Market issuers and large NLCos in 2027. Bursa Malaysia also announced enhanced sustainability reporting requirements aligned to IFRS Sustainability Disclosure Standards in late 2024. Against this backdrop, the Board’s role expands beyond “approving the statement” to governing the systems, controls, and accountability that produce decision-grade sustainability information especially where AI is used to accelerate reporting, analytics, and supplier-risk monitoring.
Learning Outcomes
- Explain why AI is now a Board-level sustainability issue (value creation + risk + disclosure credibility), using current investor and global risk signals.
- Set AI governance expectations for sustainability use cases (decision rights, accountability, policy, third-party oversight and data residency, and escalation thresholds).
- Evaluate AI-enabled sustainability insights and dashboards through a credibility lens: data provenance, assumptions, limitations, and documentation needed for audit/assurance.
- Experience a brief hands-on demo with AI to understand the potential journey of utilising AI in sustainability.
- Identify and prioritise board-relevant use cases (e.g., emissions estimation support, supplier risk sensing, reporting workflow automation) and test whether they are “fit for oversight”.
- Ask sharper Board/Committee questions aligned to Malaysia’s NSRF direction and ISSB-aligned reporting expectations (including readiness checkpoints and governance routines).
- Recognise guardrails for AI to maintain high levels of governance, to mitigate risk and reputational exposure, and direct management toward appropriate controls.
