A recent academic study warns consumers against relying on generative artificial intelligence for personalized financial guidance, highlighting significant inconsistencies, potential demographic biases, and algorithmic inaccuracies across leading platforms. Conducted by finance professors at the University of Georgia and the University of Rome Tor Vergata, the research was published in the Journal of Financial Planning and evaluated free versions of ChatGPT, Claude, Copilot, DeepSeek, Gemini, Meta AI, and Perplexity. Researchers tested the platforms using identical prompts regarding emergency savings, retirement withdrawal rates, and portfolio composition, systematically altering the demographic profile of the hypothetical user to assess bias. The findings revealed substantial divergence in recommendations across models. While most tools adhered to broad financial planning conventions, such as the standard four percent withdrawal rule, outputs varied widely in specific allocation strategies and emergency fund suggestions. The study concludes that generative AI responses often sound authoritative while remaining incomplete or misleading, raising serious concerns regarding the consistency and fairness of algorithmic financial advice. The research underscores several structural limitations inherent to large language models. Experts note that AI systems are highly sensitive to prompt phrasing, where minor wording changes can drastically alter output. Additionally, these tools frequently suffer from hallucination, generating plausible but factually incorrect information without self-awareness. Andrew Lo, director of MIT Laboratory for Financial Engineering, emphasized that algorithmic outputs should never be accepted uncritically, particularly for individualized financial planning. Compounding these technical risks is the absence of a fiduciary duty; generative AI platforms are not legally obligated to prioritize user interests or provide regulated financial counsel. Despite these caveats, consumer adoption remains high. An Intuit Credit Karma survey indicates that sixty-six percent of American generative AI users have sought financial guidance through these tools, a figure that rises to eighty-two percent among Gen Z and millennials. Recognizing this trend, researchers and industry experts advise treating AI as an introductory resource rather than a substitute for professional advisory services. While the technology effectively summarizes foundational concepts like investment diversification, it routinely overlooks critical personal financial variables and produces generic recommendations that require rigorous human verification. The authors note that generative AI capabilities are rapidly evolving, and future iterations may yield more reliable outputs. Results from premium, subscription-based models could also differ from the free versions assessed in this study. Until regulatory frameworks and algorithmic reliability mature, financial professionals stress that consumers must cross-reference AI-generated insights with certified advisors to mitigate risks associated with bias, inaccuracy, and unregulated guidance.