With　rising　energy　consumption　and　environmental　awareness,　AI　offers　both　challenges　and　opportunities　for　energy-intensive　enterprises＇　low-carbon　transition.　This　paper,　grounded　in　green　innovation　theory,　develops　an　assessment　method　to　evaluate　the　pressure　on　energy-intensive　enterprises’　green　innovation　transformation,　focusing　on　three　dimensions:　R&D　cost　savings,　innovation　level　enhancement,　and　environmental　sustainability　promotion.　Additionally,　this　paper　examines　the　impact　of　AI　adoption　and　public　environmental　concern　on　the　green　innovation　transformation　of　these　enterprises.　The　study　finds　that　the　pressure　for　green　innovation　transformation　in　energy-intensive　enterprises　primarily　arises　from　R&D　cost　savings　and　environmental　protection.　Both　AI　adoption　and　public　environmental　concern　negatively　affect　the　efficiency　of　green　innovation,　but　AI　adoption　can　mitigate　the　negative　impact　of　public　environmental　concern　on　green　innovation　efficiency.　AI　adoption　primarily　reduces　green　innovation　efficiency　by　increasing　the　pressure　for　R&D　cost　savings,　whereas　public　environmental　concern　reduces　efficiency　by　increasing　both　R&D　cost　savings　and　carbon　reduction　pressure.　Finally,　the　results　of　heterogeneity　under　different　transformation　pressure　characteristics　further　prove　this　point.　This　study　not　only　challenges　existing　literature　but　also　provides　practical　significance　for　the　strategic　adjustment　of　green　innovation　transformation　paths　in　energy-intensive　enterprises.　©　2024　Elsevier　Ltd