A lot of occupations made up of routine tasks (and a lot made up of tasks that are less routine) are looking likely to be greatly impacted by generative AI. One occupation that I thought might be severely impacted is accountancy. However, things might not be so dire for accountants (or accounting students).
This new working paper by Jung Ho Choi (Stanford University) and Chloe Xie (MIT) looks at the impact and integration of generative AI in the accounting profession, using data from a panel of 277 professional accountants. Nine of those accountants work for a firm that Choi and Xie are partnered with, while the others are almost entirely comprised of users of the partner firm's software. The data from accountants at the partner firm allow Choi and Xie to look in detail at task-level impacts of generative AI. The broader sample provide survey-based data on AI adoption, work patterns, and attitudes to generative AI. The surveys were conducted in November 2024 and March 2025, so this is almost up-to-the-minute results.
Choi and Xie find that generative AI contributes to a significant productivity improvement for accountants:
On average, AI-using accountants support 55% more clients per week compared to non-users, enabling them to broaden their client service scope. These accountants also log more billable hours, indicating that AI helps convert previously non-productive time into client-facing work. Importantly, we find evidence of task reallocation facilitated by AI. Routine tasks like data entry and transaction coding consume a smaller share of time for AI adopters – an 8.5 percentage point reduction in time spent on data entry for extensive AI users, equivalent to approximately 3.5 hours per week, assuming a standard 40-hour work week, freed from manual entry. Accountants appear to re-allocate this saved time to higher-value activities: we observe corresponding increases in time spent on client communication and quality assurance tasks for those using AI. In other words, AI is augmenting accountants’ capacity by taking over low-level tasks and allowing them to focus more on advisory and analytical work.
One interesting aspect is that the experienced accountants used generative AI in different ways to the less-experience accountants. Choi and Xie found that:
...more experienced accountants tend to utilize Generative AI tools more for simple tasks, such as transaction characterization, but less for complex tasks such as accounting for accruals. A 1 standard deviation increase in accounting experience... is associated with a 6 percent increase in the utilization of AI in transaction categorization and a 3 percent decrease in its use for accruals.
So, the use of generative AI improved productivity and shifted the tasks that accountants engaged in. A valid concern, also raised during their surveys, is whether the productivity improvements come at a cost of lower quality work. After all, generative AI has been prone to hallucinations, and that would lead to inaccuracy and error in the accounting context. Fortunately, that doesn't appear to be the case. Choi and Xie report that they find:
...improvements in financial reporting quality associated with AI usage. Firms where accountants deploy Generative AI show significantly more detailed and timely accounting records. In our sample, AI adoption is linked to a 12% increase in general ledger granularity, as measured by the number of unique accounts used to categorize transactions. This finer granularity suggests that AI-enabled accountants can capture transactions in more specific accounts, enhancing the informational richness of financial reports. Moreover, AI usage correlates with faster reporting cycles: on average, accountants using AI close the books 7.5 days sooner at month-end than those who do not use AI.
That last point doesn't sound grand, but is actually very dramatic, because:
On average, for each month, accountants require about 7.6 days (in addition to two weeks) to close the books for the previous month... accountants that use Generative AI on average close the books 7.5 days faster, effectively closing their books almost immediately after month-end.
When you consider the two weeks plus the 7.6 days, that means 21.6 days to close the books on average, but with generative AI this decreases to 14.1 days, a 35 percent decrease. Choi and Xie also report on a pilot incentivised field experiment, where they find that:
...randomly assigned AI-assisted participants have higher accuracy in terms of their categorization of accounts. Participants who received AI assistance completed their tasks faster and more accurately compared to those without AI assistance.
Given that this was a pilot experiment, it is likely that there are more results to come in the future. So, the improved productivity and quality are shown in survey-based results, in task-based data, and in a field experimental setting.
Given the productivity and quality improvement with generative AI, does this mean that there will be less demand for accountants in the future? Not necessarily. It is more likely that the role of accountants will change, with less routine data entry tasks, and more client-facing work. Not every accountant will agree, but I think this is a win, since the client-facing work is the more interesting stuff!
[HT: Marginal Revolution]
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