JPMorgan Chase has been systematically embedding generative AI into both internal operations and client-facing products, backed by an $18 billion annual technology budget and 450 AI use cases in production. The effort has drawn industry recognition within its payments business: J.P. Morgan Payments has received Snowflake’s 2026 AI Innovator in Financial Services Award for its Merchant Services unit, three awards at The Digital Banker’s Global AI Innovation Awards (Best AI Payments Initiative, Best AI Powered Platform for Payments, and Best AI Transformation Initiative in Payments) for its internal Turbo platform, and Celent’s 2025 Model Bank of the Year for its use of technology to deliver integrated payments and treasury solutions.
The Internal Platform
The centerpiece of the effort is LLM Suite, a proprietary portal that connects large language models from OpenAI and Anthropic to the bank’s internal data and applications. About 250,000 JPMorgan employees have access to the platform — the entire workforce except for branch and call center staff. Half of them use it roughly every day, according to Chief Analytics Officer Derek Waldron.
“When we rolled out LLM Suite to all our employees in 2024, uptake was viral. Most employees would say 2024 was the year they developed a personal relationship with AI. I would describe it as nothing short of a cultural transformation for the bank.”
Derek Waldron, JPMorgan Chase’s chief analytics officer
The system is updated every eight weeks as the bank feeds it more from its databases and software applications. “The broad vision that we’re working towards is one where the JPMorgan Chase of the future is going to be a fully AI-connected enterprise,” Waldron said.
The platform’s applications span divisions. Lawyers use LLM Suite to analyze contracts. A coding assistant has produced a 10% to 20% productivity increase for technology teams. In investment banking, Waldron demonstrated the system generating a five-page presentation, including the latest news, earnings, and a peer comparison, for a hypothetical meeting with Nvidia’s CEO and CFO in about 30 seconds. “You can imagine in the past how that would have been done; we would’ve had teams of investment banking analysts working long hours at night to do this,” Waldron said. The bank is also training AI to draft confidential memos it produces for prospective M&A clients.
The call center tool EVEE Intelligent Q&A improved resolution times through context-aware responses. In payments, the Turbo platform uses large language models to translate natural language requirements, such as those from Jira tickets, into structured, executable components for development, validation, and implementation, enabling faster validation of complex payment flows across a business that processes more than $10 trillion in transactions daily across 160 countries.
Cumulatively, the initiatives have saved the bank nearly $1.5 billion through fraud prevention, personalization, trading, operational efficiencies, and credit decisions.
Organizational Structure
In February 2026, JPMorgan reshuffled its commercial and investment bank to “maximize the impact of AI,” naming Guy Halamish as COO of the unit. The memo, signed by CIB co-CEOs Doug Petno and Troy Rohrbaugh, tasked Halamish with overseeing the effort to “harness the power of our data and fully leverage rapidly evolving AI capabilities.”
Under the new structure, each of the CIB’s four principal businesses: global banking, markets, payments, and securities services, will appoint its own chief data and analytics officer, reporting both to Halamish and their respective business heads. The CIB generated $25 billion in net income in 2024 out of a firmwide total of $58.5 billion.
Client-Facing Applications
In wealth management, AI tools supercharged the speed at which bankers could provide research and investment advice to wealthy clients during the market turmoil that followed U.S. tariff announcements in April 2025.
“Our advisers are finding the right information up to 95% faster — which means they spend less time searching and more time engaging in meaningful conversations with clients,” said Mike Urciuoli, chief information officer at JPMorgan asset and wealth management.
JPMorgan Asset & Wealth Management said gross sales between 2023 and 2024 increased by 20%, with GenAI-driven tools helping teams focus more effectively on high-impact client work. The bank projects that AI will enable advisers to expand their client rosters by 50% over the next three to five years.
In payments, J.P. Morgan Payments launched a client-facing virtual assistant for its Commerce Center reporting platform, powered by generative AI and available to clients 24/7. Built using a Retrieval-Augmented Generation framework, the assistant handles queries such as “how do I create a new report” and “which reports will show me post-funded data?” A separate solution, Cash Flow Intelligence, provides corporate treasury clients with AI-powered forecasting capabilities and an advanced analytics workbench for financial visibility and liquidity optimization.
Workforce Implications
Waldron acknowledged a “value gap between what the technology is capable of and the ability to fully capture that within an enterprise.” Companies “do work in thousands of different applications, there’s a lot of work to connect those applications into an AI ecosystem and make them consumable,” he said.
JPMorgan’s consumer banking leadership has indicated operations staff could fall by at least 10% over the next five years due to AI deployment. Waldron said that “as those agents become increasingly powerful in terms of their AI capabilities and increasingly connected into JPMorgan, they can take on more and more responsibilities.”
