E27 iconE27Sep 21, 2026

The AI productivity paradox: Why finance must move beyond automation

It can interpret variances, detect anomalies, generate forecasts, test scenarios and recommend actions. For decades, productivity in finance meant closing the books faster, reducing transaction costs and improving reporting.

The AI productivity paradox: Why finance must move beyond automation

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Useful takeaways from this story.

For decades, productivity in finance meant closing the books faster, reducing transaction costs and improving reporting.

Artificial intelligence changes that equation, because it can do more than execute routine work.

It can interpret variances, detect anomalies, generate forecasts, test scenarios and recommend actions.

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The useful part

For decades, productivity in finance meant closing the books faster, reducing transaction costs and improving reporting. Artificial intelligence changes that equation, because it can do more than execute routine work. It can interpret variances, detect anomalies, generate forecasts, test scenarios and recommend actions.

What to take from it

This creates enormous capacity, but capacity is not the same as value.

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