Purpose:　The　purpose　of　this　study　is　to　examine　the　impact　of　adopting　artificial　intelligence　(AI)　on　the　quality　of　corporate　sustainability　reporting.　The　role　of　sustainability　committees,　including　specialist　environmental,　social　and　governance　(ESG)　committees,　in　moderating　this　dynamic　is　also　examined.　Design/methodology/approach:　Regression　analysis　is　used　to　analyze　the　quality　of　ESG/sustainability　disclosures　of　listed　Chinese　companies　from　2015　to　2022.　Robustness　is　ensured　through　fixed　effects　analysis,　while　endogeneity　concerns　are　addressed　using　one-year　lagged　measures　and　the　three-stage　least　squares　(3SLS)　approach.　Sustainability　committees　are　categorized　based　on　their　ESG　specific　focus　areas,　and　aligned　with　the　corresponding　ESG　disclosure　pillars.　In　addition,　for　the　governance　pillar,　the　analysis　is　extended　by　segmenting　the　sample　based　on　state　ownership　status.　Stakeholder　theory　and　the　dynamic　capability　view　are　used　to　frame　the　analysis.　Findings:　The　results　reveal　that　AI　adoption　enhances　overall　sustainability　reporting　quality　and　pillar-specific　ESG　disclosure　quality.　This　positive　effect　is　amplified　by　the　presence　of　sustainability　committees.　Examining　the　heterogeneous　impact　of　these　committees　revealed　stronger　associations　between　sustainability　committee　specialization　and　relevant　ESG　pillar　disclosure　quality　(except　for　governance),　suggesting　that　use　of　specialist　committees　can　improve　disclosure　outcomes.　Notably,　within　non-state-owned　enterprises,　governance-focused　committees　positively　moderate　the　AI−disclosure　relationship,　highlighting　a　nuanced　effect　based　on　ownership　structure.　Practical　implications:　The　findings　offer　empirical　support　for　companies　to　leverage　AI　in　sustainability　reporting.　This　study　finds　evidence　to　support　the　creation　of　sustainability　committees,　as　a　key　corporate　governance　mechanism　to　drive　corporate　sustainability　reporting.　The　use　of　specialist　sustainability　committees　can　drive　improvements　in　disclosure　quality　relating　to　specific　ESG　pillars.　The　research　indicates　that　disclosure　over　governance　remains　poor　and　will　require　additional　regulatory　effort　to　encourage　entities　to　provide　higher　quality　governance-related　disclosures.　In　terms　of　ownership　structure,　the　study　found　that　non-state-owned　enterprises　are　more　efficient　in　using　specialist　sustainability　committees　to　improve　disclosure　quality.　Social　implications:　The　findings　highlight　the　potential　of　AI　in　supporting　high-quality　sustainability　reporting　and　the　strategic　role　of　sustainability　committees　in　this　dynamic.　The　publication　of　high-quality　sustainability　reports　is　critical　in　meeting　stakeholder　demands　for　transparency　and　corporate　accountability　on　sustainability.　Originality/value:　The　findings　offer　insights　into　AI’s　role　in　supporting　high-quality　sustainability　reporting.　By　examining　the　moderating　effects　of　sustainability　committees,　the　research　goes　beyond　examining　a　general　impact　to　exploring　how　corporate　governance　mechanisms　impact　this　relationship.　In　addition,　the　unique　data　on　Chinese　companies　highlights　differences　between　state-owned　and　non-state-owned　enterprises,　with　the　latter　exhibiting　greater　potential　to　leverage　specialist　sustainability　committees　for　improving　sustainability　reporting.　©　2025,　Emerald　Publishing　Limited.