AI is moving from a tool people test into a system that changes how organizations work. Business analysts are using it to prepare meetings, draft requirements, and spot gaps, while banks and consulting firms are reshaping roles around the technology.
The change is easy to see in everyday business analysis. AI can generate a use-case outline in under a minute, turn a simple idea into a basic prototype within an hour, and produce requirements documentation in a fraction of the time it once took. Practitioners can also use it before an elicitation session to prepare questions, organize information, and identify gaps before validation begins.
That speed matters, but it does not remove the central responsibility of the analyst. The analyst’s job is to find out what the customer did not say and keep asking questions until everything surfaces. A faster draft can help with that work, but the important questions still depend on understanding customer needs, product priorities, and business outcomes.
AI Brings Connected Responsibilities Together
AI systems make it possible to bring together responsibilities that depend on the same understanding of customers and business goals. Work that once sat across separate tasks can connect through shared information, from early ideas and use cases to prototypes and requirements documents.
This shift changes the shape of the analyst’s day. Instead of spending most of the time creating a first draft or searching for missing details, practitioners can use AI to prepare a stronger starting point and focus attention on validation. The human role remains tied to judgment, questions, and the meaning behind what a customer wants.
The broader workplace is changing along with it. More than half of organizations had redesigned or redefined roles because of AI, and 78% of HR leaders agreed that workflows and roles would need to change to realize the value of their AI investments. The issue is not only whether an organization buys an AI system. It is whether the organization changes the work around that system.
JPMorgan Builds AI Into Banking Operations
JPMorgan Chase is applying that approach across its asset management unit and wider workforce. The unit announced plans to discontinue using external proxy advisors for shareholder voting in the US and launched an in-house AI platform called Proxy IQ. The platform will aggregate and analyze proprietary data from more than 3,000 annual company meetings.
The move gives JPMorgan a way to bring its own data into a voting workflow that had relied on external advisors. It also fits a wider technology strategy. JPMorgan has an $18 billion technology budget and has rolled out its proprietary genAI platform to over 200,000 employees.
The bank is seeking to reengineer workflows for employees from coders to portfolio managers. Employees can use its in-house AI tools for tasks such as writing year-end performance reviews, showing how the bank is applying the technology to routine work as well as specialized financial tasks.
Jamie Dimon, CEO of JPMorgan, is a “tremendous” user of the bank’s generative AI suite, and he believes JPMorgan’s $2 billion AI investment has already matched its cost in savings. At the same time, Dimon said his bank doesn’t “uniquely benefit from AI” since everyone is now using it. That points to a race centered less on access to AI and more on how well each organization rebuilds its processes.
Job Counts and Skills Are Part of the Shift
Wells Fargo offers a sharper view of the workforce impact. The bank has shrunk its headcount by nearly a quarter since Charles Scharf joined in 2019, and he expects this trend to continue. Scharf said the lower headcount is an outcome of the firm’s focus on areas that are “way too inefficient” and “way too bureaucratic.”
From 2018 to June of this year, Wells Fargo had a $1.95 trillion asset cap, which hindered its ability to grow. Scharf said, “The opportunities that exist in AI are very significant, and anyone who sits here today and says that they don’t think they’ll have less head count because of AI either doesn’t know what they’re talking about or is just not being totally honest about it.”
Consulting firms are also changing what they expect from their people. Mel Wolfgang, Boston Consulting Group’s North America regional chair, wants consultants who can combine technical proficiency with critical-thinking skills. BCG sees its consultants developing technical capabilities that were once concentrated among specialists in areas such as IT architecture and software development.
Across business analysis, banking, and consulting, the same pattern stands out: AI handles more of the first-pass work, while organizations place greater weight on judgment, business understanding, and the ability to connect technology with results. The roles are changing because the workflow is changing.
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