Artificial intelligence (AI) is gaining traction as a tool for managing personal finances, offering rapid analysis and cost-saving potential, although it currently has limitations in complex financial decision-making. A recent evaluation tested AI’s effectiveness in reducing expenses related to electricity and home loans, highlighting its strengths and weaknesses.
In the case of electricity, the AI system analysed a series of uploaded business electricity bills to identify usage patterns across peak, off-peak, and shoulder periods. Using this data, it accessed Australia’s government-run Energy Made Easy comparison website to generate a ranked list of electricity plans, including estimated annual costs and critical contract features. The AI highlighted nuances such as higher daily supply charges being offset by the absence of seasonal pricing in some plans, providing a comprehensive view beyond surface-level cost comparisons. By following the AI’s recommendation, a switch to a new electricity provider was completed, resulting in an estimated annual saving of about $1,000. While the AI significantly accelerated the research process and delivered clear explanations, the overall outcome was similar to what could be achieved independently, albeit with more time and effort. For this task, the AI received a performance rating of nine out of ten.
The AI’s performance was less consistent when it came to home loan refinancing. After inputting loan details such as balance, interest rate, and offset balances, the AI reviewed multiple loan comparison and lender websites, producing a list of the top ten lenders with associated product details and potential savings. However, subsequent verification revealed some of the rates cited were outdated, failing to reflect recent Reserve Bank of Australia interest rate increases. Additionally, several lenders listed lacked necessary product features such as prepayment options or split loan facilities, making them unsuitable for the borrower’s needs. This highlighted a key drawback of AI in this context: it does not inherently inquire about, or incorporate, personalized preferences and detailed criteria as a human mortgage broker would. Experienced brokers can provide tailored advice based on industry insights, lender reputations, administrative processes, and exclusive offers such as broker-only cashbacks. Consequently, the AI’s usefulness was rated at seven out of ten for loan refinancing, offering valuable information but lacking practical depth.
The AI itself framed its role as a highly efficient research assistant rather than a comprehensive adviser. It cautioned users about the potential for confidently presented but incorrect information and recommended that AI be used for preliminary analysis or less critical financial decisions involving smaller risks. For significant matters—such as home loans or employment contracts—professional advice remains essential, since human advisers can ask detailed questions, negotiate on behalf of clients, and bear responsibility if advice proves flawed.
Regarding data security, users are encouraged to exercise caution by redacting sensitive personal information before inputting data into AI systems and avoiding sharing information in public forums. Most AI platforms offer options to disable the use of personal data for training or product improvement, which typically requires navigating to specific privacy settings.
Financial planning expert James Gerrard noted that while AI can streamline initial research and highlight potential savings, it does not replace the nuanced expertise and accountability that human financial professionals provide. As AI tools continue to advance, their integration as complementary aides rather than replacements for personalized financial advice appears to be the current optimal use case.