This semi-monthly column highlights news, government documents, NGO/IGO papers, conferences, industry white papers and reports, academic papers and speeches, and central bank actions on the subject of AI’s fast paced impact on the banking and finance sectors. The chronological links provided are to the primary sources, and as available, indicate links to alternate free versions.
NEWS
Bloomberg, the OG of financial data firms, has a potent new AI agent. How it built it holds lessons for other companies, Fortune via Yahoo Tech. April 28, 2026. In their battle for enterprise sales, both OpenAI and Anthropic have been targeting financial services firms. That’s not surprising. As that old joke about why criminals rob banks says: It’s where the money is. OpenAI supposedly has a battalion of ex-investment analysts helping to build a yet-to-be-launched agentic AI financial analysis product. Anthropic has been rolling out financial modeling skills for its Claude Code, Cowork, and Claude for Finance products. Startup Samaya AI is building AI tools for the finance sector too. And there are plenty of new financial advisory tools using AI as well, as my colleague Jeff John Roberts has covered in this informative recent feature. The OG of specialized financial data and analysis tools, of course, is Bloomberg. Access to the company’s “terminal,” as it calls its core product (even though its data is no longer delivered through a dedicated machine), is still considered the de rigueur tool of every trader, investment banker, and hedge fund quant. Bloomberg’s tools have seen off lots of rivals since its founding back in 1981. But today, AI is supercharging the competitive pressure on the company, as rivals embrace AI-powered features and use AI models to rapidly ingest and analyze complex data sets, from bond prices to earning transcripts to social media feeds to satellite imagery, that once only Bloomberg consolidated in a single place—and as Bloomberg’s customers can increasingly use AI to perform the kinds of modeling they once needed the terminal to do.
MIT professor says we should be ‘very, very careful’ when asking AI for financial advice — and prompting it correctly is an ‘art – AOL, April 28, 2026.
- Dave Ramsey warns nearly 50% of Americans are making 1 big Social Security mistake — here’s what it is and the simple steps to fix it ASAP
- Robert Kiyosaki issues grim warning for baby boomers. Many could be ‘wiped out’ and homeless ‘all over’ the country. How to protect yourself now
- Taxes are going to change for retirees under Trump’s ‘big beautiful bill’ — here are 4 reasons you can’t afford to waste time
However, less than two-thirds (62%) of people reported trusting AI to spit out “honest, reliable and competent information,” and less than one in five say they’d trust it to “make financial recommendations on its own.” - Maintaining a healthy skepticism aligns with expert thinking.
- “One of the things about [large language models] 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 (2).
- “When it comes to very, very specific calculations of your own personal situation, that’s where you have to be very, very careful,” he said.
The $19.8 Billion Signal: What JPMorgan’s Tech Budget Tells Every Banking CEO. mindit.io. JPMorgan’s technology budget is approaching $20 billion in 2026. AI is expected to generate $2.5 billion in annual value. For every other bank, this isn’t just a competitor’s number — it’s a strategic signal. The Numbers That Should Worry You – JPMorgan Chase’s technology budget for 2026 is approximately $19.8 billion. Their total projected expenses: $105 billion, with $20 billion allocated to technology — a 10% rise from 2025. The bank has 2,000 people working on AI. 40,000 developers using AI coding assistants. AI models scanning over $10 trillion in daily transactions. AI is expected to generate $2.5 billion in annual value through efficiency gains and revenue growth. These aren’t aspirational projections. They’re operational numbers from a bank that processes $12 trillion in daily payments and serves 86 million US customers.
Job Cuts Driven By AI Are Rising On Wall Street – Firms like Bank of America, Citi, Wells Fargo, and others are reporting strong profits while reducing head count and automating more work. The New York Times, April 21, 2026. “All of them credited A.I. to some degree … in areas ranging from the so-called back office, where tens of thousands of employees fill out paperwork to comply with various laws and regulations, to the front office, where seven-figure salaried professionals put together complicated financial transactions for corporate clients,” reports the New York Times. From the report: Less than four months ago, Bank of America’s chief executive, Brian T. Moynihan, volunteered in a TV interview what he would say to his 210,000 employees about the chance of artificial intelligence replacing human work. “You don’t have to worry,” he said. “It’s not a threat to their jobs.” Last week, after Bank of America reported $8.6 billion in profit for the first quarter — $1.6 billion more than the same period a year earlier — Mr. Moynihan struck a different tone. The bank’s bottom line, he said, was helped by shedding 1,000 jobs through attrition by “eliminating work and applying technology,” which he repeatedly specified was artificial intelligence. He predicted more of that in the months and years to come. “A.I. gives us places to go we haven’t gone,” Mr. Moynihan said. The veneer of Wall Street’s longstanding assertion — that A.I. will enhance human work, not replace it — is rapidly peeling away, as evidenced by the current quarterly earnings season. JPMorgan Chase, Citi, Bank of America, Goldman Sachs, Morgan Stanley and Wells Fargo racked up $47 billion in collective profits, up 18 percent, while shedding 15,000 employees. All of them credited A.I. to some degree with helping cut jobs and automate work in areas ranging from the so-called back office, where tens of thousands of employees fill out paperwork to comply with various laws and regulations, to the front office, where seven-figure salaried professionals put together complicated financial transactions for corporate clients. Unlike executives in Silicon Valley, few major financial figures are stating outright that A.I. is eliminating jobs. Citi, for example, has pledged to shrink its work force by 20,000 people through what one executive described to financial analysts last week as the company’s “productivity and efficiency journey.” The bank is paying for A.I. software from Anthropic, Google, Microsoft and OpenAI, to automatically read legal documents, approve account openings, send invoices for trades and organize sensitive customer data, among other tasks, according to public statements by bank executives and two people familiar with Citi’s systems. Among the recent job cuts at Citi were scores of employees who were part of the bank’s “A.I. Champions and Accelerators” program, according to the two people, who were not permitted by the bank to speak publicly. The program involves Citi employees who perform their day jobs while also working to persuade their colleagues to adopt A.I. technologies. Firms like Bank of America, Citi, Wells Fargo, and others are reporting strong profits while reducing head count and automating more work. “All of them credited A.I. to some degree … in areas ranging from the so-called back office, where tens of thousands of employees fill out paperwork to comply with various laws and regulations, to the front office, where seven-figure salaried professionals put together complicated financial transactions for corporate clients..
51% of U.S. Consumers Expect AI to Replace Financial Advisors – CreditOne. When financial uncertainty arises, people look for guidance. For decades, that meant a call to a financial advisor or a conversation with someone they trust. Now, artificial intelligence (AI) is entering that decision-making process. New survey data shows that 26% of U.S. consumers have sought financial advice from an AI-powered app or chatbot in the past year. Even more telling, 20% say they have made a significant financial decision primarily based on an AI tool’s recommendation. The findings reflect a broader national conversation about artificial intelligence in everyday life. Consumers are experimenting with AI tools for everything from budgeting to investing, yet concerns about privacy and accuracy continue to shape how deeply they engage. Recent industry moves suggest that AI financial advisors are moving out of theory and into practice. In April 2026, OpenAI acquired Hiro Finance, a startup that helps users model financial decisions and plan their money using AI. While the company has not outlined specific plans for consumer finance, the move could signal a growing interest in expanding AI-powered financial tools and capabilities. So even though the technology is gaining ground, trust is still being negotiated. Key Findings
- 63% sought financial advice from family or friends in the past year
- 26% used an AI-powered app or chatbot for financial advice
- 34% of millennials used AI tools for financial advice
- 20% made a significant financial decision based primarily on AI
- 36% of U.S. consumers cite data privacy as their biggest concern about AI financial planning
- 60% are more likely to trust advice backed by a major financial institution
- 51% believe AI will replace most financial advisors within 10 years
PAPERS
NBER
Understanding Firms’ AI Efforts and Their Economic Impact. Working Paper 35123. DOI 10.3386/w35123. Issue Date April 2026.
This paper reviews firm-level data on artificial intelligence and the emerging evidence on AI’s economic effects. It argues that measurement is central: different AI datasets capture different objects (including invention versus use, internal capability building versus outsourcing, and realized activity versus investor perceptions) and can therefore lead to different conclusions. The paper develops a framework for choosing among these measures and surveys available data sources on firm AI efforts. It synthesizes evidence on AI’s effects on firm growth, valuation, productivity, risk, labor, competition, financial markets and applications. The paper concludes by suggesting some ideas for future research.
Bank for International Settlement (BIS)
The geography of AI firms. BIS Working Papers | No 1343 | Kumar Rishabh and Vatsala Shreeti. 20 April 2026
In this paper, we trace the geography and economic characteristics of firms that produce artificial intelligence (AI) products and services. Many economies around the world are evaluating their strategic priorities in AI, yet relatively little is documented about the global distribution of AI production. We construct a new database that identifies 1,246 AI-producing firms across 32 economies. We map these firms in each economy into the five layers of the AI supply chain: compute, cloud and related infrastructure, data tools, AI models and AI applications. The biggest markets for AI production are China and the US. Most economies specialise only in a few supply chain layers and many focus largely on compute. AI firms in all economies exhibit strong home bias in investment activity, with a focus on downstream applications. Finally, we find that venture capital inflows are strongly correlated with the presence and density of AI firms in a given economy.
Federal Reserve Bank of New York, Liberty Street Economics
Use of Gen AI in the Workplace and the Value of Access to Training – Ali Hashim, Gizem Kosar, and Wilbert van der Klaauw – The rapid spread of generative AI (AI) tools is reshaping the workplace at a remarkable rate. Yet relatively little is known about whether workers have access to these tools, how the tools affect workers’ daily productivity, and how much workers value the training needed to use the tools effectively. In this post, we shed light on these issues by drawing on supplemental questions in the November 2025 Survey of Consumer Expectations (SCE), fielded to a representative sample of the U.S. population. We find that adoption of AI tools at work is heterogeneous, that a sizable share of workers see AI training as important, and that a significant share of employers are nonetheless not yet providing access to AI tools or training on how to use them.