Banking giant JPMorgan Chase & Co. is asking its roughly 65,000 engineers and technicians to use AI tools as part of their regular workflow. business insider Managers reported tracking how often staff use these tools. Its use may also affect performance evaluation.
The report states that employees are encouraged to use tools such as ChatGPT and Claude Code when writing code, reviewing documents, and handling daily tasks. Internal systems then classify employees based on their level of usage. Some users are classified as “light users” while others fall into the “heavy user” category.
JPMorgan uses it for fraud detection and risk analysis. What stands out here is not the technology itself, but how it is integrated into the day-to-day expectations of staff.
According to internal documents cited by business insidermanagers are paying close attention to how their employees are using AI tools.
JP Morgan demonstrates AI implementation in banking
Many companies have spent the past two years rolling out AI tools across departments. In most cases, adoption is uneven. Some teams experiment a lot, while others stick to existing workflows.
JPMorgan is treating AI as a standard part of its work. This creates a more even level of adoption within the team. Previously, performance reviews focused on output and accuracy. Now, it may also include how employees can effectively use AI tools to achieve results.
This poses practical problems for large organizations. If AI can reduce the time required for a particular task, should employees be expected to produce more work in the same amount of time?
Respond to changes within your company
By tracking usage, banks may be trying to avoid common problems in deploying enterprise software. Tools are being introduced, but adoption has been slow and impact has been limited. Making AI a part of performance reviews creates a strong incentive to engage with the technology. It also suggests that AI literacy is becoming a baseline skill, just as spreadsheets and code tools have become the norm over time.
An emerging challenge is that employees feel pressure to use AI even when it doesn’t clearly improve outcomes. There is also the question of how to measure “appropriate” use rather than just frequent use.
Improving AI risk and efficiency at JPMorgan
Banks operate in a regulated environment, and the need for oversight will increase as AI is introduced into more workflows.
Tools like ChatGPT and Claude Code are useful for summarizing information and generating drafts, but they can also produce inaccurate or incomplete results. This means that employees still need to validate the output before using it for decision-making or customer-facing tasks.
JPMorgan has developed internal controls for AI systems in areas such as trading and risk. Expanding its use to broader employee groups may require similar safeguards, creating a situation where banks want to improve efficiency, but also need to ensure that increased use of AI does not introduce new risks.
It is likely that other financial institutions are also paying close attention. If tying the use of AI to performance leads to measurable productivity gains, similar models could become popular in this space.
The bank’s approach could reshape the way companies hire and train employees, with skills such as on-the-fly writing and output checking potentially becoming part of standard job requirements. JPMorgan’s approach suggests that this change is already underway, at least in the banking industry.
(Photo provided by IKECHUKWU JULIUS UGWU)
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