JPMorgan Chase deploys GenAI tools to boost employee productivity, streamline tech workflows, and build a scalable, data-ready AI foundation.
JPMorgan Chase deploys GenAI tools to boost employee productivity, streamline tech workflows, and build a scalable, data-ready AI foundation. While most banks hesitated on GenAI, JPMorgan Chase moved early—now operating over 450 active GenAI use cases, mostly focused on internal efficiency. The bank launched EVEE, a GenAI assistant in call centers, to reduce lookup time for agents handling complex inquiries. Instead of combing through policy docs, staff now ask EVEE and get immediate, accurate responses—speeding up resolutions and improving satisfaction.
Another major rollout is LLM Suite, Chase’s proprietary GenAI platform, which supports 200,000 employees. It helps with content generation, document queries, and day-to-day knowledge access. New hires use it to learn fast, while experienced staff rely on it to streamline internal processes. This has sparked experimentation across teams, increasing adoption and idea generation.
For tech teams, GenAI also powers code creation and conversion, cutting repetitive development tasks and boosting productivity by 10% to 20%. These tools are helping Chase reduce software delivery timelines and optimize costs, with clear performance metrics tracked via test-control experiments and KPIs. The firm’s “learn by doing” approach gets GenAI tools directly into employees’ hands.
Now Chase is preparing to scale firm-wide. It’s investing in data readiness, prioritizing structured and unstructured data cleanup to fuel smarter GenAI outputs. Meanwhile, as user behavior evolves, so must the models—requiring ongoing iteration. Front-office deployment remains cautious but is under evaluation, with data protection and governance taking top priority.