Bank of America put 1,000 contractors on patching software flaws exposed by AI models like Anthropic’s Mythos in the second quarter, chief executive Brian Moynihan told CNBC on 14 October 2026. They work alongside 3,000 people already in that area.
The bank spent a “couple hundred million plus” on the software remediation and on regulatory issues related to anti-money laundering compliance in the third quarter, Moynihan told analysts the same day, according to CNBC.
Business Pill · RED TEAMING
A one-minute explainer of red teaming: attacking your own systems to find the flaws before someone else does. It teaches the general idea only and says nothing about any organisation in this story.
The key insight: As we read it, Bank of America has put a headcount and a price on the defensive side of frontier AI: Moynihan named 1,000 contractors and a third-quarter bill of a “couple hundred million plus” that also covers anti-money laundering issues, according to CNBC.
In an interview with CNBC’s Leslie Picker after the bank’s third-quarter earnings release, Moynihan said that earlier this year the company rushed to bolster a wide spectrum of its internal and vendor code using thousands of employees and outside personnel, according to CNBC.
“That risk is real risk,” Moynihan said. When the frontier-type models came out, he said, many at the bank asked: “How do we figure out how to get through this quickly?”
“We put on 1,000 contractors to help us do the patching work in the second quarter, and those people remain here today, helping us, on top of the 3,000 people we have in that area,” he said.
Bank of America added 1,000 contractors to its software patching work in the second quarter, on top of 3,000 people already in that area, chief executive Brian Moynihan told CNBC on 14 October 2026.
What Was Posted on X
BofA says it hired 1,000 contractors in Q2 to support 3,000 internal staff in patching proprietary and vendor software flaws exposed by AI models like Mythos (@hugh_son / CNBC)
(Visit Techmeme dot com for the link and full context!)
Techmeme relayed CNBC’s report on 15 October: Bank of America hired 1,000 contractors in the second quarter to support 3,000 internal staff patching proprietary and vendor software flaws exposed by AI models like Mythos.
Meta isn’t the only one cleaning up after AI models.
Bank of America admits it brought in 1,000 outside contractors to patch flaws that Anthropic’s Mythos dug up, on top of the 3,000 people already on that work.
Headcount is down about 3,000 year over year. The AI story looks great on the headcount line. The labor just moved to the consultant line, at a couple hundred million plus in Q3 remediation alone.
Something tells me that the clean up won’t be a one and done.
Amanda Goodall’s post is her own opinion: she argues the labour moved from the headcount line to the consultant line and that the clean-up won’t be one and done. CNBC put the head count fall at about 3,400, and the “couple hundred million plus” covers remediation and anti-money laundering issues together, not remediation alone.
What It Cost
The “couple hundred million plus” figure covers both the software remediation and anti-money laundering compliance issues in the third quarter, as CNBC reported it; the report does not split the two.
By our arithmetic, 1,000 contractors on top of 3,000 staff puts about 4,000 people on that work. That is our sum of the two figures Moynihan gave.
CNBC described the remarks as some of the first by a major US corporation to specify the manpower and dollars spent to protect software systems from Mythos, which Anthropic released to a small group of banks, technology firms and government agencies in April.
Why Moynihan Expects Patching Costs to Fall
Moynihan sought to reassure investors that the spending increase was temporary, according to CNBC, as the bank’s shares slumped as much as 8% on Wednesday.
“Once you patch, you don’t have to patch as much,” he said. “The pipeline moves through.” He said the bank expects remediation costs to decline over time.
“We’ve got to stay ahead of them, and we’ve got to be mindful that the people doing the software development are the people trying to sell us the services,” Moynihan said.
Where AI Saves Money
Bank of America has about 130 internal AI projects, and savings from those efforts are expected to rise from $300 million this year to $700 million in 2027, Moynihan told analysts, according to CNBC.
The bank’s head count fell by about 3,400 employees in the past year as it cut roughly 5% of managers, he said. CNBC said it is unclear how much of that reduction is attributable to AI.
As we read it, the same models now sit on both sides of the bank’s ledger: CNBC reported the remediation bill alongside savings from about 130 internal AI projects, which Moynihan said are expected to rise from $300 million this year to $700 million in 2027.
As we read it, Moynihan described the cost as a backlog being worked through: he said “Once you patch, you don’t have to patch as much” and that the bank expects remediation costs to decline over time.
As we read it, his remark that “the people doing the software development are the people trying to sell us the services” points at vendors, since the bank’s rush covered vendor code as well as internal code, according to CNBC.
Brian Moynihan to CNBC, 14 October 2026
“That risk is real risk”
Three Implications
BANK OF AMERICA Moynihan said the 1,000 contractors added in the second quarter remain at the bank, on top of 3,000 people in that area, according to CNBC.
INVESTORS Moynihan sought to reassure investors that the spending increase was temporary as the bank’s shares slumped as much as 8% on Wednesday, CNBC reported.
OTHER LARGE COMPANIES CNBC described the remarks as some of the first by a major US corporation to specify the manpower and dollars spent to protect software systems from Mythos.
The framework starts from the claim that AI moved from a CIO line item to a finance question: “In 2026 it became a CFO problem, because the economics finally turned legible โ and unforgiving.”
As we read it, Bank of America’s disclosure puts both AI lines in front of its CFO at once: a remediation cost Moynihan expects to decline and savings he expects to grow. The framework predates the report and is about token spending; it does not discuss Bank of America.
Savings from Bank of America’s about 130 internal AI projects are expected to rise from $300 million this year to $700 million in 2027, Moynihan told analysts on 14 October 2026, according to CNBC.
What Is Not Established
CNBC does not give a split between the remediation spending and the anti-money laundering costs inside the “couple hundred million plus”, and it does not say what the 1,000 contractors cost on their own.
Moynihan referred to frontier-type models and CNBC to AI models like Mythos; the report does not say which of the bank’s flaws were found by Mythos itself, or how many flaws there were. We read CNBC’s report in full; we did not read a transcript of the analyst call.
Business Engineer Framework
The CFO’s Guide to the Token Economy
A Business Engineer framework on how AI spending turned into a CFO problem.
Bank of America added 1,000 contractors in the second quarter to patch flaws exposed by AI models like Anthropic’s Mythos, on top of 3,000 people already in that area, Moynihan told CNBC.
He told analysts that third-quarter remediation and anti-money laundering costs came to a “couple hundred million plus”, said the bank expects remediation costs to decline over time, and said savings from its AI projects are expected to reach $700 million in 2027.
A note on sourcing. We read CNBC’s 14 October 2026 report in full; every quotation and figure comes from it, including Moynihan’s interview with CNBC’s Leslie Picker and his remarks to analysts as CNBC reported them. We did not read a transcript of the analyst call. The 4,000 is our arithmetic. The Mythos tiers and forward deployed engineer references link to our own earlier reporting.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur, HackerNoon and Search Engine People. Find him on LinkedIn and Substack. See how we source.
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