Crunch time: Let AI work the numbers, but leave the emotional decisions to humans

AI boosts finance, but human judgment remains essential

by · TechRadar

Opinion By Hugh Scantlebury Published 27 July 2026

(Image credit: Getty Images)

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On the surface, the accounting and finance sector appears to be a great test case for AI integration. Work revolves around numerical data, while processes are structured and rules-driven.

It also seems an ideal environment for automation, giving scope for AI to process information at speed and scale. For that reason, it’s already being used to handle some of the sector’s necessary yet repetitive and time-consuming work, such as invoice capture, month-end reporting and anomaly detection.

Hugh Scantlebury

Founder and CEO of Aqilla.

But as confidence in AI grows and is integrated into more accounting and finance software, there’s a risk that organizations once fearful of the technology may go to the other extreme. At that point, there’s a danger that some professionals may lean so deeply into AI that they become detached from the numbers.

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That matters because the decisions that sit behind the figures and spreadsheets are rarely driven by pure logic. Financial strategy is shaped by leadership judgement, organizational priorities, risk appetite, and sometimes (although none of us likes to admit it) internal politics.

That means a surprisingly large proportion of commercial decisions contain a human component that AI cannot, and probably should not attempt to, replace.

For many finance and accounting teams, the solution is to use automation to reduce cognitive load. Individuals are then free to focus on interpretation, creativity and decision-making. It keeps humans in the process exactly where instincts and experience are most needed.

Surfacing the truth

Numbers often create a sense of objectivity and certainty, but financial reporting still involves interpretation, context and judgement. So, when accounting and finance professionals engage with AI tools and automation, it’s important they maintain a firm grasp of their data.

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