The banking sector has shown an uneven embrace of gen AI since its emergence in 2022. Core regional banks are ahead of other institutions in adopting gen AI, particularly in the ideation and planning stages, according to findings from a McKinsey survey. While megabanks also show significant activity in this initial phase, Senior Partner Kevin Buehler and coauthors find that fewer megabanks’ gen AI use cases reach full deployment compared with those of their peers.
Image description:
A bubble chart scatterplot compares the average delays and overruns for life science projects versus other industries, with the size of each bubble representing the average investment size. The chart plots capital expenditure overrun as a percentage of original quoted capital expenditures on the y-axis against additional delay as a percentage of the original schedule on the x-axis. The life sciences industry is represented by a gray bubble, positioned at around 110% on the y-axis and 45% on the x-axis, indicating significant delays and overruns. Other industries, represented by light blue bubbles, are scattered around the chart, with some experiencing lower delays and overruns, such as transport corridors, and others experiencing higher delays and overruns, such as roads and railways. Notably, 95% of life sciences projects did not meet their authorized cost and schedule, as indicated by an annotation on the chart.
Note: This image description was completed with the assistance of Writer, a gen AI tool.
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To read the article, see “Banking on gen AI in the credit business: The route to value creation,” July 8, 2025.