With recent advancements in generative AI, there is a discussion about whether AI writing can be further applied to news production that requires more opinions and creativity. Economic and financial news commentary, which is a typical genre of economic journalism characterized by standardization, subjectivity, logicality, serves as an apt news genre to explore the application boundaries of AI writing. Based on the Heuristic-Systematic Model (HSM), this study investigated the impact of AI involvement in the production of financial commentary on the perceived expertise of the content through two sets of scenario experiments (N1=110; N2=582). Study 1 examined the perceived expertise differences between AI-generated and human-written financial commentary without prompting the audience to pay attention to the author. The results indicated that when readers processed the financial commentary vias systematic approach, they found it difficult to distinguish the expertise level between content written by AI and that by human journalists. Study 2 employed a 2 (actual author: human vs. AI) × 3 (author attribution: human journalist vs. AI vs. anonymous) online experiment, to explore the mechanisms of the different perception of financial commentary written by different author under heuristic processing. The findings showed that when the audience was aware of the author's identity, financial commentary attributed to AI could enhance perceived expertise through authority heuristics and machine heuristics. Moreover, the audience’s attitude toward AI writing significantly strengthened the effect of machine heuristics on perceived content expertise. Considering the research conclusions, the authority and expertise that professional financial media have relied on to survive are also facing great challenges in the current AI era. Therefore, it is necessary to fully rebuild the authority and expertise of financial media to cope with the impact of AI writing.