SouthernWorldwide.com – Artificial intelligence is rapidly becoming integrated into various aspects of daily life, from work presentations and shopping to scientific research. This begs the question: can AI also be a reliable tool for retirement planning, a complex and crucial financial endeavor?
A growing number of Americans are already seeking financial guidance from AI. A September study by AI company Pearl revealed that approximately 20% of individuals use chatbots for financial advice. This trend is even more pronounced among those who already utilize AI in their professional lives, with about half of them also employing AI for retirement planning, according to a separate study by MissionSquare Research Institute. This is double the rate of workers who do not use AI.
The urgency for retirement planning is underscored by recent findings. Americans now anticipate working an average of four years longer than desired, primarily due to the escalating cost of living and insufficient savings. The median retirement account balance for workers stands at $40,000, a figure significantly lower than the estimated $1.5 million experts suggest is needed for a comfortable retirement. Furthermore, Social Security, a vital financial safety net for millions, faces potential benefit reductions of up to 20% within six years if legislative action is not taken.
How AI Can Assist with Retirement Planning
In light of these financial pressures, many are tempted to ask AI tools like ChatGPT or Claude for direct answers to their retirement concerns, such as whether they can afford to retire at a specific age given their current savings.
Some experts believe that AI can serve as a valuable starting point for addressing fundamental retirement-related inquiries. Luke Delorme, director of financial planning and a Certified Financial Planner at Tableau Wealth, notes that AI is beginning to produce outputs that can be beneficial for individuals.
Delorme shared that he has used AI to generate financial planning ideas and even run Monte Carlo simulations, which assess the potential longevity of retirement savings under various market conditions. While not yet perfect, he believes these AI-generated outputs are becoming increasingly valuable.
A Monte Carlo simulation is a sophisticated mathematical model that explores thousands of possible outcomes for an individual’s retirement portfolio. It considers best- and worst-case scenarios, including market downturns, to project the probability of a person’s savings lasting throughout their retirement years. Delorme views such simulations as ideal tasks for computer programs and anticipates these tools will grow in power over time.
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Limitations of AI in Retirement Planning
Despite its potential for basic financial planning, experts caution that current generative AI models, often referred to as large language models, are not yet equipped to handle the intricate complexities of retirement planning. These issues can range from tax implications to longevity risk.
Laurence Kotlikoff, a distinguished economist at Boston University specializing in retirement, expressed concerns that AI might inadvertently cause more harm than good in providing retirement advice. He argues that these AI applications struggle to grasp the nuances of Social Security and other retirement-related matters. Moreover, they are often trained on traditional financial planning advice that he considers fundamentally flawed.
Kotlikoff explained that AI’s training data is derived from Wall Street’s guidance, which he believes is geared towards asset management rather than providing optimal economic advice. This perspective suggests a potential conflict of interest in the advice generated by AI.
For instance, AI programs typically estimate retirement savings based on average life expectancies derived from actuarial tables, a common practice among financial planners. However, Kotlikoff emphasizes that retirement planning should instead be based on an individual’s maximum potential lifespan to effectively mitigate the risk of outliving their savings.
He has also observed that AI frequently provides inaccurate projections for Social Security scenarios. This is particularly problematic given the vast complexity of the federal program, which is governed by approximately 22,000 pages of regulations. Kotlikoff warns that incorrect analysis can lead to significant financial missteps.
Kotlikoff acknowledges that AI is a popular new technology, and criticism can be met with resistance. However, he asserts that his priority is ensuring people’s financial security, regardless of perceived trends.
Insights from AI’s Responses
Andrew Lo, a finance professor at the MIT Sloan School of Management, highlighted in an April publication that AI systems face challenges with tax optimization and understanding regulatory subtleties. Unlike human financial advisors, AI is not bound by legal obligations such as acting in a client’s best interest.
Lo also stressed the importance of critically evaluating AI-generated retirement advice. He recommends prompting AI to identify its potential errors, assumptions, and uncertainties.
To illustrate AI’s capabilities and limitations, consider a hypothetical 50-year-old single woman earning $70,000 annually. Her retirement savings of approximately $185,000 are primarily invested in S&P 500 index funds. She contributes 12% of her income to retirement and expects to receive about $2,400 per month in Social Security benefits at age 67, her full retirement age.
When presented with this scenario, AI chatbots from Anthropic (Claude), OpenAI (ChatGPT), and Perplexity offered varied assessments. Claude and ChatGPT suggested that retirement at 65 might be possible but would be financially challenging, with a risk of depleting funds. Perplexity was more conservative, indicating that comfortable retirement at 65 would likely require significant spending reductions or income increases.
Upon being asked about their underlying assumptions, the AI chatbots disclosed that their models were based on a life expectancy of 90 years, not the potential maximum of 100 years. They also admitted to not modeling precise tax implications and, notably, not assessing the substantial potential costs associated with long-term care.
Following these disclosures, the AI chatbots revised their initial conclusions. Claude, in particular, acknowledged that its original planning horizon was too short, modifying its assessment from a “tight but doable retirement” to “meaningfully underfunded without course correction.”
A Broader Challenge: Behavioral Barriers
Beyond the technical limitations of AI, a more significant hurdle in retirement planning may be the widespread fear of investing among individuals. This fear can lead to suboptimal decisions, such as holding savings in low-yield options like cash or CDs, which often fail to keep pace with inflation.
Delorme believes that AI could potentially help the roughly two-thirds of Americans who do not work with financial planners to better understand these concepts. However, he remains skeptical that AI alone can overcome the deep-seated anxieties many people have regarding financial matters.
He concluded that the primary obstacle is often behavioral rather than a lack of technical knowledge. Delorme questions whether AI can currently assist individuals in overcoming significant fears, such as the fear of investing, which he identifies as a major impediment to effective retirement planning.
