ChatGPT can help with a lot of things, from searching to generating images to planning outlines. But when it comes to financial advice, it's probably best to leave it to the (human) experts.

Nearly half (47%) of respondents to an Experian survey from October 2024 said they had tried using AI chatbots for financial advice — but a new study from the broker analysis site, Investing in the Web, found that tools like ChatGPT might not be very good at it.

One in five Americans is making 2025 the year they save more money, and there is a growing trend of asking generative AI technology for advice on how to achieve personal finance goals. But is using ChatGPT or Gemini to improve your personal balance sheet the right move? Experts say it’s complicated.

Economic challenges like inflation, recession fears and geopolitical uncertainty are top of mind for many as 2024 draws to a close. A recent Deloitte report found that 73% of respondents globally are concerned about rising prices, reflecting the financial strain on households around the world. Against that backdrop, generative artificial intelligence is emerging as a popular tool in personal finance, reflecting the evolving ways in which people think about budgeting, investing and financial planning.

However, while the technology is advancing rapidly, experts caution that these AI tools should complement — not replace — traditional strategies.

Arynton Hardy, a wealth manager in Los Angeles, uses artificial intelligence daily.

"Almost every single meeting I have with a client, I utilize an AI summarizer that gives me notes, gives me follow-ups, gives me to-dos," Hardy said. His employer, Savvy Wealth, is a tech startup focused on providing AI innovations to its growing roster of financial advisors and high-net-worth clients.

Hardy said AI tools regularly save his team hours on data entry, portfolio monitoring, and other back-office tasks, giving him more time to meet with clients.

If I asked Dall-e to draw me a picture of a cat juggling nine balls in the style of a French impressionist, it would do so in seconds. And once done, that painting would be far better than anything I could possibly hope to do. But, it wouldn’t be perfect – because it would appear that Chat GPT’s artistic side is too right-brained to actually count balls.

Artificial Intelligence (AI) is advancing at an unprecedented pace, transforming various industries and redefining traditional roles. The mortgage intermediary profession will be no exception. As AI systems continue to develop, they are outperforming humans in specific tasks, compelling professionals to rethink their strategies and adapt to these technological shifts. If someone invents the steam powered weaving loom, learn how to work the loom, don’t be a weaver.

A new MIT study by professor Andrew W. Lo and co-author suggested that while large language models (LLMs) like ChatGPT are fairly new developments for financial advisors, they could be trained to adapt to simulate both the predictive and empathetic behaviors of human advisors. "To achieve performance that rivals the best human advisors, we will need to incorporate some notion of selection, evolution, and fitness into the ongoing training of LLMs," the study said, and, "if LLMs can be made safer and more robust, they have the potential to transform our financial lives."

MIT has debuted a new platform designed to help the enterprise decide how to invest in cybersecurity.

By securely aggregating sensitive data from cyber-attacks, the SCRAM platform from MIT CSAIL can quantify an organization’s level of security and suggest what to prioritize.

THE STOCK MARKET appears strangely indifferent to Covid-19 these days, but that wasn’t true in March, as the scale and breadth of the crisis hit home. By one measure, it was the most volatile month in stock market history; on March 16, the Dow Jones average fell almost 13 percent, its biggest one-day decline since 1987. To some, the vertigo-inducing episode also exposed a weakness of quantitative (or quant) trading firms, which rely on mathematical models, including artificial intelligence, to make trading decisions.

Andrew W. Lo, Ph.D., Professor and Director of the Laboratory for Financial Engineering at MIT Sloan School of Management, believes the biggest barrier, from an investor perspective, are new business models. “That, to me, is the one thing that we can be thinking about differently that we aren’t right now. People are already focused on scientific collaborations, new types of biological mechanisms and targets, genomics, transcriptomics, proteomics, and all the other -omics. But the one omics they haven’t focused on is economics, new ways of structuring biopharma businesses and financing them. This challenge also offers tremendous opportunities for applying the tools of modern financial engineering to biomedicine and getting investors to think differently…. By adopting a portfolio approach to biomedical R&D, we can lower the cost of capital, increase the amount of funding, and get new and better therapies to patients faster and cheaper.”

When someone says that another person is intelligent, you pretty much assume that this is a praising of how smart or bright the other person might be.

In contrast, if someone is labeled as being stupid, there is a reflexive notion that the person is essentially unintelligent. Generally, the common definition of being stupid is that stupidity consists of a lack of intelligence.

This brings up a curious aspect.

Suppose we somehow had a bucket filled with intelligence. We are going to pretend that intelligence is akin to something tangible and that we can essentially pour it into and possibly out of a bucket that we happen to have handy.

Upon pouring this bucket filled with intelligence onto say the floor, what do you have left?

On August 5, 2016, Cathay Pacific Flight 905 from Hong Kong was heading for an on-time arrival at Manila’s Ninoy Aquino International Airport when something unexpected occurred. The pilots radioed air traffic controllers and said they had lost GPS (Global Positioning System) guidance for the final eight nautical miles to “runway right-24.” Surprised, the controllers told the pilots to land the wide-body Boeing 777-300 using just their own eyes. The crew members pulled it off, but they were anxious the whole way in. Fortunately, skies were mostly clear that day. The incident was not isolated. In July and August of that year, the International Civil Aviation Organization received more than 50 reports of GPS interference at the Manila airport alone.

Los profesores de negocios y finanzas que preparan a sus estudiantes para futuras carreras en la banca también están viendo la tendencia. Científico de datos es la "función más importante" ahora para los empleadores, asegura Andrew Lo, director del Laboratorio de Ingeniería Financiera de MIT en Cambridge, Massachusetts.

On the Thursday, January 24 edition of Bloomberg Baystate Business we spoke with Bloomberg Intelligence gaming and lodging analyst Brian Egger about MGM-Springfield, the latest on the Wynn saga, and sports betting. Rob Almeida of MFS stopped by to talk about the markets. Bloomberg News endowments reporter Michael McDonald joined us to talk about his story on Baupost Group’s Seth Klarman, who sees opportunity in the markets. Boston Business Journal real estate editor Catherine Carlock talked about the commercial real estate market in Boston. Finally, MIT’s Andrew Lo talked about technology, finance and investing. Hosts: Peter Barnes, Janet Wu and Pat Carroll. Producer: Dan Pierce.

BOSTON — Cold weather this week didn’t matter to the crowds at the AI World conference here, as activity around artificial intelligence continues to heat up. Over three days, more than 2,200 attendees learned about the latest advances in machine learning, deep learning, and the industries being affected by AI.

While most of the conference focused on AI’s impact on the healthcare, pharmaceutical, and enterprise software markets, a few sessions discussed industrial automation efforts, including the Industrial Internet of Things (IIoT), manufacturing, and autonomous vehicles.

Here are six themes from this year’s AI World, as observed by Robotics Business Review editors attending the event: