Finance
JPMorgan Chase rolls out AI assistant powered by ChatGPT-maker OpenAI
JPMorgan Chase has rolled out a generative artificial intelligence assistant to tens of thousands of its employees in recent weeks, the initial phase of a broader plan to inject the technology throughout the sprawling financial giant.
The program, called LLM Suite, is already available to more than 60,000 employees, helping them with tasks like writing emails and reports. The software is expected to eventually be as ubiquitous within the bank as the videoconferencing program Zoom, people with knowledge of the plans told CNBC.
Rather than developing its own AI models, JPMorgan designed LLM Suite to be a portal that allows users to tap external large language models — the complex programs underpinning generative AI tools — and launched it with ChatGPT maker OpenAI’s LLM, said the people.
“Ultimately, we’d like to be able to move pretty fluidly across models depending on the use cases,” Teresa Heitsenrether, JPMorgan’s chief data and analytics officer, said in an interview. “The plan is not to be beholden to any one model provider.”
The move by JPMorgan, the largest U.S. bank by assets, shows how quickly generative AI has swept through American corporations since the arrival of ChatGPT in late 2022. Rival bank Morgan Stanley has already released a pair of OpenAI-powered tools for its financial advisors. And consumer tech giant Apple said in June that it was integrating OpenAI models into the operating system of hundreds of millions of its consumer devices, vastly expanding its reach.
The technology — hailed by some as the “Cognitive Revolution” in which tasks formerly done by knowledge workers will be automated — could be as important as the advent of electricity, the printing press and the internet, JPMorgan CEO Jamie Dimon said in April.
It will likely “augment virtually every job” at the bank, Dimon said. JPMorgan had about 313,000 employees as of June.
ChatGPT ban
The bank is giving employees what is essentially OpenAI’s ChatGPT in a JPMorgan-approved wrapper more than a year after it restricted employees from using ChatGPT. That’s because JPMorgan didn’t want to expose its data to external providers, Heitsenrether said.
“Since our data is a key differentiator, we don’t want it being used to train the model,” she said. “We’ve implemented it in a way that we can leverage the model while still keeping our data protected.”
The bank has introduced LLM Suite broadly across the company, with groups using it in JPMorgan’s consumer division, investment bank, and asset and wealth management business, the people said. It can help employees with writing, summarizing lengthy documents, problem solving using Excel, and generating ideas.
But getting it on employees’ desktops is just the first step, according to Heitsenrether, who was promoted in 2023 to lead the bank’s adoption of the red-hot technology.
“You have to teach people how to do prompt engineering that is relevant for their domain to show them what it can actually do,” Heitsenrether said. “The more people get deep into it and unlock what it’s good at and what it’s not, the more we’re starting to see the ideas really flourishing.”
The bank’s engineers can also use LLM Suite to incorporate functions from external AI models directly into their programs, she said.
‘Exponentially bigger’
JPMorgan has been working on traditional AI and machine learning for more than a decade, but the arrival of ChatGPT forced it to pivot.
Traditional, or narrow, AI performs specific tasks involving pattern recognition, like making predictions based on historical data. Generative AI is more advanced, however, and trains models on vast data sets with the goal of pattern creation, which is how human-sounding text or realistic images are formed.
The number of uses for generative AI are “exponentially bigger” than previous technology because of how flexible LLMs are, Heitsenrether said.
The bank is testing many cases for both forms of AI and has already put a few into production.
JPMorgan is using generative AI to create marketing content for social media channels, map out itineraries for clients of the travel agency it acquired in 2022 and summarize meetings for financial advisors, she said.
The consumer bank uses AI to determine where to place new branches and ATMs by ingesting satellite images and in call centers to help service personnel quickly find answers, Heitsenrether said.
In the firm’s global-payments business, which moves more than $8 trillion around the world daily, AI helps prevent hundreds of millions of dollars in fraud, she said.
But the bank is being more cautious with generative AI that directly touches upon the individual customer because of the risk that a chatbot gives bad information, Heitsenrether said.
Ultimately, the generative AI field may develop into “five or six big foundational models” that dominate the market, she said.
The bank is testing LLMs from U.S. tech giants as well as open source models to onboard to its portal next, said the people, who declined to be identified speaking about the bank’s AI strategy.
Friend or foe?
Heitsenrether charted out three stages for the evolution of generative AI at JPMorgan.
The first is simply making the models available to workers; the second involves adding proprietary JPMorgan data to help boost employee productivity, which is the stage that has just begun at the company.
The third is a larger leap that would unlock far greater productivity gains, which is when generative AI is powerful enough to operate as autonomous agents that perform complex multistep tasks. That would make rank-and-file employees more like managers with AI assistants at their command.
The technology will likely empower some workers while displacing others, changing the composition of the industry in ways that are hard to predict.
Banking jobs are the most prone to automation of all industries, including technology, health care and retail, according to consulting firm Accenture. AI could boost the sector’s profits by $170 billion in just four years, Citigroup analysts said.
People should consider generative AI “like an assistant that takes away the more mundane things that we would all like to not do, where it can just give you the answer without grinding through the spreadsheets,” Heitsenrether said.
“You can focus on the higher-value work,” she said.
— CNBC’s Leslie Picker contributed to this report.
Cybersecurity and enterprise software stocks have been market dogs in 2026, with fears that AI will wipe out a wide range of companies in the enterprise space dominating the narrative. But they snapped a brutal losing streak this past week, joining in the broader market rally that saw all losses from the U.S.-Iran war regained by the Dow Jones Industrial Average and S&P 500.
Cybersecurity has been “a victim of some of the AI-related headlines,” Christian Magoon, Amplify ETFs CEO, said on this week’s “ETF Edge.”
It wasn’t just niche cybersecurity names. Take Microsoft, for example, which was recently down close to 20% for the year. Its shares surged last week by 13%.
A big driver of the pummeling in software stocks was a rotation within tech by investors to AI infrastructure and semiconductors and some other names in large-cap tech, Magoon said, and since cybersecurity stocks and ETFs are heavily weighted towards software companies, they were left behind even as those businesses continue to grow on a fundamental basis.
But Wall Street now has become more bullish with the stocks at lower levels. Brent Thill, Jefferies tech analyst, said last week that the worst may be over for software stocks. “I think that this concept that software is dead, and then Anthropic and OpenAI are going to kill the entire industry, is just over-exaggerated,” he said on CNBC’s “Money Movers” on Wednesday.
“Big Short” investor Michael Burry wrote in a Substack post on Wednesday that he is becoming bullish about software stocks after the recent selloff. “Software stocks remain interesting because of accelerated extreme declines last week arising from a reflexive positive feedback loop between falling software stocks and changes in the market for their bank debt,” he wrote.
The Global X Cybersecurity ETF (BUG), is down about 12% since the beginning of the year, with top holdings including Palo Alto Networks, Fortinet, Akamai Technologies and CrowdStrike. But BUG was up 12% last week. The First Trust NASDAQ Cybersecurity ETF (CIBR) is down 6% for the year, but up 9% in the past week.
Piper Sandler analyst Rob Owens reiterated an “overweight” rating on Palo Alto Networks which helped the stock pop 7% — it is now down roughly 6% on the year. Its peers saw similar moves, including CrowdStrike.
Performance of Global X cybersecurity ETF versus S&P 500 over past one-year period.
Magoon said expectations may have become too high in cybersecurity, and with a crowding effect among investors, solid results were not enough to to push stocks higher. But the down-and-then-back-up 2026 for the sector is also a reminder that when stocks fall sharply in a short period of time, opportunity may knock.
“Once you’re down over 10% in some of these subsectors, you start to see the contrarians start to say, ‘well, maybe I’ll take a look at this,'” Magoon said.
He said AI does add both opportunity and uncertainty to the cybersecurity equation, increasing demand but also introducing new competition. But he added, “I think the dip is good to buy in an AI-driven world,” specifically because the risks to companies may lead to more M&A in cyber names that benefits the stocks.
For now, investors may look for opportunity on the margins rather than rush back into beaten-up tech names. “I think investors are still going to remain underweight software,” Thill said.
But Magoon advises investors to at least take the reminder to keep an eye on niches in the market during pronounced downturns. “The best-performing are often the least bought and do the best over the next 12 months versus late-in-the-game piling on,” he said.
While that may have been a mindset that worked against the last investors into cybersecurity and enterprise software in mid-2025 when the negative sentiment started building, at least for now, it’s started working for the stocks in the sector again.
Meanwhile, this year’s biggest winner is also a good example of what can be an extended trade in either a bullish or bearish direction. Last year, institutional ownership of energy was at multi-year lows, Magoon said, referencing Bank of America data. “Reverse sentiment can be a great indicator,” he said.
But he cautioned that any selective buying of stocks that have dipped does have to contend with the risk that there is a potentially bigger drawdown in the market yet to come in 2026. That is because midterm election years historically have been marked by large drawdowns. “If you think it is bad right now, it could get a lot worse,” Magoon said. But he added that there’s a silver-lining in that data, too, for the patient investor. The market has posted very strong 12-month returns after midterm election drawdowns end. So, for investors with a longer-term time horizon and no need for short-term liquidity, Magoon said, “stick in there.”
Sign up for our weekly newsletter that goes beyond the livestream, offering a closer look at the trends and figures shaping the ETF market.
New innovation in the exchange-traded fund industry could come at a cost to investors during extreme conditions.
According to MFS Investment Management’s Jamie Harrison, ETFs involved in increasingly complex derivatives and less transparent markets may be in uncharted territory when it comes to violent downturns.
“Those would be something that you’d want to keep an eye on as volatility ramps up,” the firm’s head of ETF capital markets told CNBC’s “ETF Edge” this week. “As innovation continues to increase at a rapid pace within the ETF wrapper, [it’s] definitely something that we advise our clients to be really front-footed about… Lack of transparency could absolutely be an issue if we’re going to start seeing some deep sell-offs.”
His firm has been around since 1924 and is known for inventing the open-end mutual fund. Last year, ETF.com named MFS Investment Management as the best new ETF issuer.
“It’s important to do due diligence on the portfolio,” he said. “Having a firm that has deep partnerships, deep bench of subject matter experts that plays with the A-team in terms of the Street and liquidity providers available [are] super important.”
Liquidity as the real issue?
Harrison suggested the real issue is liquidity, particularly during a steep sell-off.
“We’ve all seen the news and the headlines around potential private credit ETFs. That picture becomes much more murky,” he added. “It’s up to advisors, to investors [and] to clients to really dig in and look under the hood and engage with their issuers.”
He noted investors will have to ask some tough questions.
“What does this look like in a 20% drawdown? How does this liquidity facility work? Am I going to be able to get in? Am I going to be able to get out? And if I’m able to get out, am I able to get out at a price that’s tight to NAV [net asset value], and what’s the infrastructure at your shop in terms of managing that consideration for me,” said Harrison.
Amplify ETFs’ Christian Magoon is also concerned about these newer ETF strategies could weather a monster drawdown. He listed private credit as a red flag.
“If your ETF owns private credit, I think it’s worth taking a look at, kind of what the standards are around liquidity and how that ETF is trading, because that should be a bit of a mismatch between the trading pace of ETFs and the underlying asset,” the firm’s CEO said in the same interview.
Magoon also highlighted potential issues surrounding equity-linked notes. The notes provide fixed income security while offering potentially higher returns linked to stocks or equity indexes.
“Those could potentially be in stress due to redemptions and the underlying credit risk. That’s another kind of unique derivative,” Magoon said. “I would very closely look at any ETF that has equity-linked notes should we get into a major drawdown or there be a contagion in private credit or something related to the banking system.”
What that means for consumer loans
Checks and Balance newsletter: Of God and MAGA
Why software stocks, 2026’s market dogs, have joined the rally
Armanino adds Strategic Accounting Outsourced Solutions
New 2023 K-1 instructions stir the CAMT pot for partnerships and corporations
