The AI output most likely to go unchecked is the one that confirms what your team already believes.
When a model produces an unexpected result, people investigate. They check the data, the assumptions, and the pipeline.
When it produces the number everyone hoped for, they sign off.
That's how unverified AI enters a business: not through obvious failures, but through results that confirm existing expectations.
Financial forecasting gets treated like a data problem.
It is not.
It is a workflow problem.
The data is already there. Every company has it.
What kills them is the loop: collect it, clean it, structure it, analyse it, build the report, send it out, then do the entire thing again next month. That is where the hours go.
ELECTE was built on that observation. Not another dashboard. A system that runs the loop for you.