Finance has been the biggest IT customer since computers existed.
Banks outspend Microsoft. They outspend Accenture. They have massive budgets because everything they do is digital and everything digital requires infrastructure.
They were the first adopters of mainframes.
First adopters of the internet.
First adopters of cloud computing.
And they will be the first real adopters of generative AI.
But the use case isn’t what most people think.
The killer application isn’t having a fancy chatbot answer questions. It’s solving the data problem that has plagued this industry for decades.
In the past, making two systems talk to each other required establishing protocols. Data schemas. Strict formatting rules. One character out of place and the entire pipeline breaks.
This is expensive.
It cuts out smaller players who can’t afford the infrastructure. It burdens larger players with massive IT budgets just to maintain what they’ve already built.
Generative AI addresses this differently.
It’s flexible. It interprets rather than demands. It remaps data structures on the fly. It adapts to new formats without requiring months of engineering work.
The biggest use case we’re seeing isn’t the flashy stuff. It’s the mundane but critical work of making messy, unstructured data actually usable.
That’s where the real productivity gains live. That’s where billions in IT spending either gets justified or exposed as waste.
Data has always been the bottleneck. AI is finally the release valve.
