A recent study from the University of Georgia warns consumers against relying solely on artificial intelligence for personal financial planning, highlighting significant inconsistencies and demographic biases across major generative AI platforms. Led by Swarn Chatterjee, Bluerock Professor of Financial Planning at the College of Family and Consumer Sciences, the research evaluated how seven leading chatbots, including ChatGPT, Claude, Copilot, DeepSeek, Gemini, Meta AI, and Perplexity, responded to identical financial scenarios. Researchers presented three detailed hypothetical cases involving emergency savings thresholds, retirement withdrawal rates, and a $300,000 low-risk investment allocation. While adjusting only the gender and race of the hypothetical subjects, the study revealed that chatbot recommendations diverged substantially depending on both the AI platform and the demographic profile. Advice was most volatile regarding savings thresholds and investment strategies. Several models advised women and African American individuals to maintain larger emergency funds than their white and male counterparts, with algorithms potentially projecting higher employment barriers for minority groups. Conversely, Claude delivered uniform savings recommendations across all scenarios, while Meta AI steered female users toward conservative equity allocations and DeepSeek suggested African American users hold zero liquid cash. Despite these disparities, the study noted that the core financial principles generated by the models remained largely sound. All seven platforms consistently advised a four percent annual withdrawal rate for retirement assets, aligning with established financial planning standards, and Gemini explicitly recommended consulting a human professional rather than providing direct figures. Chatterjee compared the issue to seeking medical advice online, noting that while AI can synthesize vast amounts of financial data, its outputs are heavily influenced by the biases embedded in its training corpora. He emphasized that a chatbot should serve only as an initial reference point rather than a definitive financial roadmap. The findings underscore a critical need for consumer vigilance in the era of generative AI finance tools. The researchers concluded that algorithmic guidance, though generally accurate, lacks the nuanced personalization required for high-stakes monetary decisions. Users are strongly advised to verify AI-generated strategies against independent data and to consult certified financial planners who can account for individual circumstances, risk tolerances, and long-term objectives. As AI systems become increasingly embedded in everyday consumer services, this study reinforces the principle that synthetic financial advice requires human oversight, data literacy, and a cautious, evidence-based approach before implementation.