Earlier this month, the internet made viral a money prompt from influencers like Mel Robbins, encouraging followers to use AI models to “take control of your money” by sharing documents such as bank and debt statements, bills, and income information. But the prompt emphasized the painful consumer need for judgment-free, actionable advice to control their money amid the overwhelmed, ashamed, or behind outlook they face.

As a finance educator who focuses on financial trauma, I found the prompt alarming for many reasons, including cybersecurity concerns and the behavioral and overall impact this may have on women in particular, who make up the largest portion of Robbins’s audience. This has prompted me to research and treat this more than a simple viral social media moment, examining the deeper question it has sparked: Should consumers upload the most intimate details of their financial lives into AI tools in exchange for convenience?

The Privacy Trade-Off Women May Not Be Aware Of

A 2025 survey by the American Bankers Association found that 51% of consumers said they use AI for financial advice or information, while another 27% said they have not but are considering it. Interestingly, the same report said 71% of consumers felt the price of goods was rising faster than their income, creating mixed ground for consumers to use the tools to potentially overcome challenges posed by the economic situation.

The appeal of the viral prompt is as emotional as it is practical. It begins from a place many consumers recognize, such as feeling overwhelmed, behind on payments, or ashamed about money, which aligns with Credit Karma’s 2025 data showing that 75% of generative AI users said the technology lets them ask financial questions they are too embarrassed to ask others. A place where you can go at your own pace, ask questions, and hand over everything you may not understand at a time, to give you a “solution” without judgment, may sound ideal, but cybersecurity experts say the most concerning part of the advice is not asking AI to explain a budget but encouraging users to upload sensitive financial documents before they understand how that data may be stored, reviewed, protected, or used.

“For someone who has an audience of over 12 million followers, encouraging people to upload sensitive financial documents into AI tools feels like a significant oversight,” Win Myat Nwe Khine , Senior Information Security Officer , told me in an interview. “Financial independence and privacy were not historically guaranteed rights, especially for women… Given how recently people gained autonomy over their own finances, it is worth questioning why we are now so willing to hand deeply personal financial information over to AI companies in exchange for convenience,” she added.

In the U.S., for instance, women gained federal protection against sex- and marital-status discrimination in credit through the Equal Credit Opportunity Act of 1974 . Race, color, and national-origin protections were added through amendments in 1976, meaning women of color faced overlapping barriers in systems that had long limited access to credit, mortgages and wealth-building tools. In the U.K., the Sex Discrimination Act 1975 addressed sex- and marriage-based discrimination, while the Race Relations Acts of 1968 and 1976 targeted racial discrimination in services, housing, and employment.

Bank statements can show where someone lives, where they work, how much they earn, what debts they carry, where they shop, whether they travel, which doctors or pharmacies they visit and whether they are under financial stress. In other words, they show an identity and behavioral map from a 30-day snapshot. “Users often underestimate how much behavioral insight can be inferred from financial data alone,” Myat said. “Spending habits, income level, health indicators, lifestyle choices, relationship status, travel patterns and even emotional states can be derived from transaction history.” she added.

The privacy protections vary widely depending on the tool, account type and settings. In this case, Robbins named Microsoft Copilot as the tool to use. However, Microsoft says conversations with Copilot are saved by default, though users can view and manage conversation history. It also says prompts, responses and data accessed through Microsoft Graph are not used to train foundation large language models (LLMs) for Microsoft 365 Copilot commercial customers.

If we examine ChatGPT by OpenAI, it says that users can turn off model training in data controls, and Temporary Chats are not used to train its models. The problem is that a user who uploads a bank statement may not know whether they are using a consumer product, a business product, a protected enterprise environment or a version with different data controls.“Most users consent to these practices without fully understanding the terms and conditions and while companies may claim that data is anonymized or handled responsibly, the reality is that the more sensitive data users provide, the more predictive and valuable that data becomes.” Myat added.

Financial records are valuable because they can make fraud more convincing and trigger the same financial trauma or stress consumers may be looking to avoid when turning to AI in the first place. During a recent session I attended at the Money20/20 Event in Amsterdam, it was discussed that anti-fraud companies are currently examining the profiles of fraudsters, identifying different profiles that all benefit from as much information as possible to create identities they can profit from. For instance, a scammer who knows someone’s bank, debt load, salary range, recent purchases, or the history of purchases over the last 30 or 90 days can craft more personalized phishing messages, impersonation attempts, or social engineering attacks.

The Federal Trade Commission said U.S. consumers reported losing $12.5 billion to fraud in 2024, a 25% increase from the prior year. Similarly, the FBI’s Internet Crime Complaint Center reported losses exceeding $20 billion in 2025. “No platform is immune to cyberattacks,” Myat said. “Even highly mature organizations with strong security programs experience breaches. Financial documents are among the most valuable forms of personal data because they can be used for identity theft, fraud, phishing campaigns, extortion, and social engineering,” she explained.

The Behavioral Component AI Can Not Solve

People avoid bills, overspend, delay asking for help, or remain in debt for reasons that are often emotional, social and/or structural. Thus, promising to ultimately “Take control over your money” by simply handing all the information to AI is inaccurate, as it leaves out important pieces of the lack-of-control puzzle, including but not limited to habit formation, routine setting, lifestyle, access to opportunities, and funding.

An AI tool can support categorization, summarization, and explanation of the difference between fixed, variable, and discretionary expenses, analyze different strategies to pay off debt, and even help you develop some important financial skills . But financial control is not only about the lack of information; it is also about how that lack of information keeps fueling the individual and systemic behavior that got the person there, and that is where AI’s limits become more important.

When a person works with a financial professional to take control of their financial life, they review a financial picture while also understanding the context, emotional variables, financial trauma, disparities, and unique situations that make up the complete picture, based on lived experiences, other clients’ experiences, and professional experience. For instance, a 40-year-old person who is looking to gain control over their money because they fear they will not have enough for retirement, as they can barely make it on their paycheck right now, may use AI with relative figures to understand different possibilities out there on how to maximize their income and reduce expenses. However, this person will gain control over their financial life when they put those lessons into action and are able to stick to them, based on their adherence and lifestyle. If this person works with a financial professional, they may have the accountability needed to keep showing up during the hard moments they may face while adjusting their lifestyle, and they may also have someone who understands the unique needs this particular person may have.

For consumers who feel ashamed about money, the promise of a platform that offers guidance that perhaps doesn’t make people feel isolated or criticized doesn't mean it's risk-free. “The more people outsource financial analysis and decision-making to AI, the less they may engage critically with their own financial literacy and judgment,” Myat said.

From a financial expert's perspective, AI can support your understanding of your financial situation if consumers understand how to use AI as a tool to help organize spending, explain debt strategies, and make financial information feel less intimidating. But it cannot fully solve the behavioral, emotional, and structural reasons people struggle with money. For women, especially women of color, the trade-off with AI regarding their financial data, behavior, and identity requires an intentional assessment of whether to surrender sensitive financial records to feel empowered. The real promise of AI in personal finance is not that it can take control for us, but that it can help people ask better questions and hopefully make more informed decisions while keeping control where it belongs.

Alejandra Rojas is the founder of Brown Way To Money , a financial education platform, and the host of the Brown Way To Money podcast . Alejandra blends financial strategy with a trauma-informed approach to guide business owners toward financial stability.

The information in this article are not intended to replace professional financial, tax, or accounting advice.