Artificial intelligence (AI) skills are increasingly becoming the central theme in terms of influencing pay and promotion decisions on Wall Street.
As per a survey by financial-services recruitment firm Selby Jennings, nearly a quarter of financial firms linked employees’ proficiency with the technology to salary increases, bonuses or career advancement.
There has been a monumental change in financial institutions assessing the returns on their AI investments.
Instead of simply encouraging employees to experiment with new tools, firms are beginning to examine whether the technology’s use translates into measurable improvements in productivity and business performance, the survey found.
Some 30% of surveyed financial firms have made it mandatory for their employees to disclose their use of AI tools during formal performance reviews, while 42% of survey respondents have introduced formal criteria to assess AI skills.
A further 30% have established dedicated teams or roles to monitor whether AI investments are delivering results, noted Selby Jennings.
Selby Jennings surveyed 500 executives across the financial-services industry.
“Companies are no longer just seeing if their employees are using AI tools but are also monitoring its impact on output and contribution to business results,” Dylan Gomez, the firm’s executive director, told Reuters.
Although there is no established formula for linking compensation to AI usage and performance, Gomez expects the practice to become more clearly defined by 2027.
Selby Jennings’s findings also discovered another trend: a growing emphasis on employee productivity while Wall Street grapples with a second question: how to profit from the enormous investment needed to build the infrastructure underpinning AI.
Major technology companies have committed billions of dollars to data centres, chips and computing capacity needed to train and operate increasingly sophisticated models.
The spending also presents banks with opportunities across investment-grade debt, leveraged finance and other lending businesses, but the question about whether the returns will be worth taking the risk remains unanswered.
Goldman Sachs Chief Executive David Solomon, for example, said this week that the pace at which demand for capital and computing power would evolve remained unclear.
He also stressed the importance of monitoring the risks associated with the activities banks finance.
Citigroup CEO Jane Fraser, meanwhile, said higher interest rates had not yet slowed investment across the AI ecosystem, pointing to continued shortages of computing capacity.
Bank of America CEO Brian Moynihan said AI-related capital expenditure was important to the bank’s investment-grade debt and leveraged finance businesses.
However, the scale of the spending is raising questions about whether demand for computing power will justify the industry’s expansion plans. Financing costs, supply-chain pressures and local opposition to data-centre developments could also affect project returns.
Wells Fargo CEO Charlie Scharf recently described the AI investment cycle as a significant macroeconomic force, bringing both opportunities and risks because of the leverage used to fund projects and pressure on prices in some industries.
“Higher borrowing costs could become a particular concern if interest rates remain elevated for longer than expected, making data-centre projects pricier to finance and debt harder to service,” he noted.
While Wall Street has linked employees’ AI skills with their pay and promotion decisions, banks are facing pressure to ensure that competition for AI-related business does not weaken their lending standards.
Morgan Stanley Chief Financial Officer Sharon Yeshaya told Reuters that the bank was being selective about the risks it assumed, particularly as other lenders pursued financing opportunities.
CEO Ted Pick has described the bank’s involvement in AI financing as “existential,” underscoring the sector’s strategic importance.
While banks, beyond financing the AI buildout, are aggressively deploying the technology to reduce organisational costs, accelerate product development and improve customer service, the financial benefits are not equally visible across the industry.
JPMorgan Chase Chief Financial Officer Jeremy Barnum said AI’s impact could take time to show up clearly in the quarterly results of an institution of the bank’s size.
Citi, however, has reported more immediate gains. Fraser said AI had helped the bank develop products at a lower cost and up to 40% faster.
“Coding tools had also eased software development and reduced technology-vendor expenses by 30%,” she added.
The bank has been using AI and automation to reduce manual processes and improve response times in client service. Fraser said the financial benefits from these initiatives had significantly outweighed the investments made so far this year.
Security remains another concern as AI agents gain the ability to act autonomously, creating new risks alongside existing cyber threats.
JPMorgan CEO Jamie Dimon said the bank was developing tools to deal with the difficulties associated with agentic AI.
For Wall Street, the stakes are therefore twofold: AI must deliver measurable productivity gains inside financial institutions, while the banks financing the wider technology boom ensure that ambitious investment plans do not turn into costly credit exposures.