How AI May Increase Jobs, Not Replace Them

Dr. Jeffrey Roach | Chief Economist


Last Updated: May 21, 2026

From the April payroll report released on May 8, we realize that not all industries are equally impacted by AI. Diagnostic imaging centers, an area where AI is thought to replace humans, have increased demand for workers, whereas bookkeeping demand has declined in recent years. William Jevons, a British economist born in the same town as the Beatles but less famous, explained that increased efficiencies may spark additional demand and that this concept may help us understand the potential AI impacts on the job market.


The Jevons paradox suggests that when technology makes the use of a resource more efficient, demand for that resource can rise rather than fall because lower costs unlock new uses and broader adoption. Applied to AI and the labor market, this means AI may reduce the time and cost required to perform many tasks, but that does not necessarily imply a proportional decline in labor demand. Instead, by making tasks, software development, customer service, research, and operations more productive, AI can expand the volume of work organizations are able to undertake and create demand for new roles, new products, and new business models. Or in the case of diagnostic imaging centers, as mentioned above, the lower cost of the service is a catalyst for a spike in demand, and so a firm hires more workers to meet the shift in demand.


The implication is that AI’s labor-market impact will likely be less about the wholesale elimination of jobs and more about the reallocation of tasks across workers, firms, and industries. Some routine or automatable tasks will be displaced, and certain occupations will face pressure. But as AI lowers the cost of service, demand may increase for workers who can use AI effectively, improve workflows, and apply human judgment. In this sense, AI could follow a Jevons-like pattern: greater efficiency may increase the overall demand for AI-enabled work, even as it changes the composition of employment and raises the premium on adaptability, digital fluency, and higher-value human skills. And AI may end up being the antidote to a shrinking labor force.

Percent of Working-Age Population Will Shrink

Source: LPL Research, Bureau of Labor Statistics 05/13/26


Policymakers and investors increasingly see AI as a way to offset the economic drag from aging populations, especially in developed economies where the workforce is starting to shrink. As more people move into retirement and a larger share of the population is over 70, fewer workers are available to support overall growth. AI is viewed as a way to fill that gap by boosting how much each worker can produce rather than relying on a larger workforce. It can automate repetitive tasks, enhance decision-making, and allow smaller teams to generate the same or greater output. That dynamic matters for governments as well, since slower workforce growth puts pressure on tax revenue while spending on healthcare and pensions is rising.


From an investor perspective, AI is also tied to long-term profitability in a world where labor is becoming scarcer and more expensive. Companies that adopt these technologies can reduce their dependence on hiring while improving efficiency and output, which helps protect margins. This encourages more spending on technology and capital investment as businesses look to substitute machines for labor. Over time, many investors believe AI could drive a sustained increase in productivity similar to earlier technological shifts. In that sense, it is being treated as a structural solution to demographic challenges, one that could extend the growth trajectory of aging economies while supporting returns even as population dynamics become less favorable.


AI is likely to reshape rather than simply eliminate jobs, with efficiency gains potentially increasing demand for AI-enabled work while raising the premium on adaptability and human judgment.


For more ways AI will shape the outlook for economic growth, inflation, and the job market, check out this month’s Economic Navigator.

July 9, 2026
Melanie Weischwill | Partner & Financial Advisor  July 8, 2026
July 9, 2026
Greg Iacurci@GregIacurci | Personal Finance Reporter  Published Tue, Jul 7 202612:21 PM EDT Key Points A new study in the Journal of Financial Planning found that artificial intelligence programs can provide inconsistent, inaccurate or biased recommendations when it comes to personal finance. Researchers prompted seven AI programs — ChatGPT, Claude, Copilot, DeepSeek, Gemini, Meta AI and Perplexity — with questions about emergency savings, asset allocation and withdrawals from a retirement portfolio. The findings align with those of other experts, who recommend using AI as a starting point for financial questions but not as a final authority. When it comes to personal finance, artificial intelligence gives advice that can be inaccurate or demographically biased, and can range widely depending on the particular program that consumers use, according to a new academic research study. The research — which studied seven “widely available” generative AI platforms — found “significant variation” in how GenAI answered prompts about emergency savings, asset allocation and withdrawals from a retirement portfolio. Researchers examined free-access versions of ChatGPT, Claude, Copilot, DeepSeek, Gemini, Meta AI and Perplexity. “GenAI-driven responses may sound confident but can still be incomplete, misleading, or incorrect,” according to the paper, published last month in the Journal of Financial Planning and authored by finance professors at the University of Georgia and University of Rome Tor Vergata in Italy. Its “suboptimal” or biased outputs raise questions “about the consistency and fairness of GenAI-driven recommendations,” according to authors Swarn Chatterjee, Brenda Cude and Gianni Nicolini. The findings come as a large share of Americans are turning to AI to help manage their money. Two out of three Americans — 66% — who have used GenAI said they’ve leveraged it for financial advice, according to an Intuit Credit Karma survey published in September. The share is higher for Gen Z and millennials, at 82% for each cohort. Experts said that AI is generally good at providing high-level overviews of financial topics: For example, why it’s important to diversify investments, or why exchange-traded funds may be better than mutual funds in some cases but not others. However, it has limitations that mean users shouldn’t trust its output blindly, they said. For one, the programs can also provide wrong answers due to so-called “hallucination” of the algorithm, experts said. “One of the things about LLMs that I find particularly concerning is that no matter what you ask it, it’ll always come back with an answer that sounds authoritative, even if it’s not,” Andrew Lo, director of MIT’s Laboratory for Financial Engineering and principal investigator at its Computer Science and Artificial Intelligence Lab, told CNBC in an interview in March. “When it comes to very, very specific calculations of your own personal situation, that’s where you have to be very, very careful,” Lo said. In addition, AI is sensitive to how users write their prompts, meaning small differences in input can lead to variation in its recommendations. AI also doesn’t owe a fiduciary duty to users, meaning it doesn’t legally need to provide financial advice in users’ best interests. Other research studies have also pointed to the limitations of AI for personal finance. In one 2024 study, for example, researchers examined ChatGPT’s ability to provide financial advice. They found it could be a “first stop” for households seeking financial advice, but ultimately found its recommendations to be “generic,” often overlooking certain pertinent information. “We believe that ChatGPT can serve as a starting point in giving and finding financial advice, but its recommendations should be carefully scrutinized and assessed,” according to the study, published in the Journal of Risk and Financial Management. The latest study, in the Journal of Financial Planning, queried the seven GenAI platforms in August 2025 with the same set of prompts. Researchers prompted the platforms with three identical financial scenarios, related to emergency savings, the optimal withdrawal rate from retirement savings and the recommended composition of an investment portfolio. They then used the same prompts, but changed the race and gender of the hypothetical individual to learn if the GenAI recommendations would change. They found “substantial variation in guidance” across platforms relative to emergency savings and asset allocation. “Although the tools often produced recommendations that broadly aligned with generic financial planning principles, such as the 4 percent retirement withdrawal rule, there were significant differences across platforms in suggested emergency savings and portfolio allocations,” researchers wrote. “The findings suggest that GenAl may serve as a helpful starting point for consumers but should complement, not replace, professional financial advice,” they said. Of course, GenAI tools are “still evolving,” and future studies may find different results, they said. And, outputs from the paid GenAI models may differ from those of the free versions that were assessed. Securities and advisory services offered through LPL Financial, a registered investment advisor. Member FINRA/SIPC. CNBC, South Star Wealth Management and LPL Financial are separate entities.
June 9, 2026
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Additional content provided by Tucker Beale, Sr. Analyst, Research. 
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