Businesses are rapidly incorporating artificial intelligence (AI) into operations, particularly to manage regret bias. Based on a game with three financing options (bank financing, guarantee financing and direct financing), we investigate how AI influences financing preferences among e-commerce supply chain participants, which involve one capital-constrained and regretful SME, one e-commerce platform, and a bank. Firstly, our findings reveal that the impact of AI is not a clear-cut matter. AI may not consistently boost platform profitability under guarantee financing, platform needs to consider the production scale effect brought by AI against the potential default risk. Similarly, in direct financing, SME must strike a balance between the increase in output resulting from AI development and the potential impact of platform adjusting interest rates. Secondly, from the perspective of financing strategy space, it’s evident that AI can be a positive force in encouraging all supply chain participants to enjoy platform financing services. Specifically, SME prefers direct financing over guarantor financing when the unit regret bias cost and production cost is low but the commission fee is high. Platform is more inclined to provide direct financing if unit production cost is low and unit commission fee is high. Otherwise, bank financing is preferred. As regret bias cost diminish, the strategy space for bank financing contracts. For the whole supply chain, all three types of financing may be options. Guarantee and direct financing gradually become more popular as SME uses AI at higher levels. Moreover, conclusions remain robust when SME is fully credit-constrained or platform is fully financially constrained. These results not only underscore the critical role of AI in regret bias and financial management but also shed light on the innovative possibilities in financing within the e-commerce supply chain.