From novelty to daily financial assistant
Artificial intelligence has quickly evolved from a curiosity into an everyday utility. What once felt experimental is now part of routine life, whether generating meal ideas, planning workouts, or suggesting entertainment. Increasingly, Americans are also turning to AI for financial guidance.
According to FNBO’s 2025 Financial Wellbeing Study, nearly half of Americans have used AI tools such as ChatGPT to assist with personal finance decisions, and about half say they trust AI-generated financial advice. That shift highlights how rapidly AI has integrated into decisions that once required in-person conversations or specialized software.
How AI is already embedded in your finances
Even people who have never opened a chatbot may already be relying on AI. Banks and fintech platforms routinely deploy artificial intelligence to power fraud detection systems, analyze spending behavior, generate credit scores, recommend financial products, and enable multi-factor authentication.
Direct-to-consumer platforms such as ChatGPT and Gemini extend similar capabilities into personal hands. Users can request budget templates, debt payoff strategies, savings breakdowns, or scenario comparisons within seconds. With accurate inputs, AI can evaluate cash flow, identify inefficiencies, and simulate long-term outcomes.
As certified financial planner Andrew Latham notes, financial planning follows a structured process. Reviewing income and expenses, stress-testing goals, and comparing tradeoffs are analytical tasks that AI can increasingly perform when given proper context. However, he also emphasizes that human advisors still provide emotional guidance, accountability, and behavioral coaching that algorithms cannot fully replicate.
The risks behind personalization
The same data that fuels personalization also introduces risk. The more detailed the financial information shared with an AI system, the more tailored the output becomes. Yet sharing sensitive data raises privacy and security concerns.
A PYMNTS.com study in 2024 found growing anxiety about technological dependence and data misuse. A 2025 IBM report added measurable evidence: 13% of organizations experienced breaches involving AI systems, while 8% were uncertain whether such systems had been compromised.
Security experts warn that rapid adoption can outpace oversight. Without proper safeguards, sensitive information and model integrity may be exposed to manipulation or unauthorized access. As AI systems integrate further into financial infrastructure, governance and cybersecurity protections become essential rather than optional.
Guidelines for responsible use
AI can serve as a powerful support tool, particularly for individuals without access to professional advisory services. However, thoughtful usage reduces exposure to unnecessary risks.
Review privacy settings: Examine the platform’s terms and data policies. Some services allow users to disable conversation history retention or prevent data from being used for model training.
Avoid sharing personally identifiable information: Names, dates of birth, account numbers, and highly specific financial records should remain private. Generalized figures often provide sufficient context for scenario planning.
Use AI as a framework, not a final authority: Artificial intelligence can help compare mortgage structures, evaluate savings rates, or explore retirement projections. But final decisions should reflect personal objectives, risk tolerance, and independent verification. AI expands perspective. It should not replace judgment.
