AI in finance has, however, started to become a little louder lately. I came across a recent article on how finance leaders are embracing automation and analytics with unexpected urgency while reading an overview of how CFOs report AI is transforming finance when strategy leads the way.
What struck me is how consistently C.F.O.s emphasized what most Americans fail to fully grasp: A.I. isn’t magic. It has only paid off when a company knows why it wants to use it in the first place.
What’s curious is how uneven the change has been. Some teams have even begun using predictive models to change the way they think about cash-flow cycles and scenario planning, talking decade-old concepts found in examinations of how modern finance groups are challenging outdated backward-looking metrics with forward-leaning insight,-think pieces including a breakdown on what AI means for experimentation in finance departments.
Others, however, are still juggling with clunky spreadsheets and legacy systems that just won’t die.
It splits weird where half of the team is getting carried away with autonomous prophecy, and the other half is fighting old macros.
One statement that gave me pause and for thought was a more fundamental consideration of how finance roles are being transformed as AI assumes the responsibility for repetitive work, an area that’s also examined in a conversation around how modern finance teams will need analytical and interpretative skills more than ever.
It got me thinking about whether we are prepared for the mindset switch. Numbers have always mattered, but now the story behind the numbers matters more for once and that’s a different muscle altogether.
Another theme throughout all of this is trust. There is also an ongoing debate about how much responsibility AI systems should have in making recommendations to businesses (a concern that was recently raised in the heady analysis of what it means for financial guidance to be automated but human supervised, such as this point of view on scaling AI-driven advice without breaking user trust).
The truth is, I have that worry – speed is good if it isn’t short-circuiting judgment.
From my vantage point, this seems to be a time when finance leaders are trying to run two races at the same time: modernize the engine while driving the car.
And if I were to offer my view, this is it: AI in finance will be amazing when companies quit treating it like a shiny thing, and start regarding as part of the strategic backbone.
Until then, we’ll continue seeing flashes of brilliance interspersed with growing pains.
