Artificial intelligence has ceased to be an experimental tool and has become a daily support in personal finance management. According to Arturo Bernal, a professor at the business school of the Tecnológico de Monterrey, AI analyzes millions of data in real time and facilitates faster and better-informed decisions in money management, particularly through mobile banking applications and digital platforms based on machine learning. These applications learn from user behavior patterns to organize expenses, anticipate risks, and offer practical recommendations, from alerts for high spending to savings or investment scenarios. In an environment where long-term planning is increasingly relevant, the combination of technology, financial education, and informed decision-making emerges as the true differentiator. Participants describe these tools as on-demand financial tutors, useful for understanding concepts, comparing products, and evaluating scenarios. In practice, this translates into concrete actions: requesting the creation of a monthly budget, simulating progressive savings goals, or analyzing adjustments in spending categories. In this context, chatbots are consolidating as an accessible entry point for those seeking initial support in budget creation or defining financial goals. The impact is especially visible in savings planning. A 2026 academic study published in ScienceDirect, based on a survey of 2,170 adults in South Korea, found that 48.2% of users of language models like ChatGPT use them to plan savings and 47.6% to manage their budget. The perceived complexity of finances, lack of attention, or fear of making mistakes often hinder action. Platforms like ChatGPT, Google Gemini, and Meta AI are recurrently used for these purposes. From the perspective of behavioral economics, this support can help reduce common frictions. The challenge is not to reject these tools, but to use them with discernment. In the same vein, Erika Rasure, director of financial wellness at Beyond Finance, points out that AI allows asking questions at any time without fear of judgment, which facilitates a more open relationship with money. However, there are limits. Research on algorithmic biases, such as those disseminated by The Decision Lab in its Reference Guide, warns that AI systems are not neutral and can reproduce errors if the training data is incomplete or biased.
