AI in accounting is used most in work with clear rules, repetition and volume: data analysis and reporting, invoice and payment processing, and payables and receivables. In an ACCA survey of more than 900 accounting leaders already using AI, 33% had implemented AI solutions in data analysis and reporting, 28% in invoice and payment processing and 24% in accounts payable and receivable. According to Eurostat's 2025 data, 23.1% of EU enterprises that use AI apply it to accounting, controlling or finance management.
Work that needs judgement stays with the professional. The ACCA report says outputs of generative AI cannot be fully relied upon for accuracy and recommends human oversight and validation for tasks requiring high accuracy. Under Turkish Law No. 3568, the subject of the profession covers bookkeeping and preparing documents as well as examination, audit, written opinions and reports.
In brief:
- Automating: reading document data, invoice and payment processing, reconciliation matching, report preparation (ACCA 2024).
- Staying with the professional: resolving exceptions, opinions and reports, review and responsibility (ACCA 2024; Law No. 3568, Art. 2).
- Changing: the role moves from routine compliance and reporting toward judgement, interpretation and ethical oversight (ICAEW 2026).
Where is AI used in accounting?
The ACCA report of August 2024 rests on a survey of more than 900 accounting leaders who had implemented AI at least in part. It ranks the areas with implemented solutions: data analysis and reporting 33%, financial planning and analysis 31%, invoice and payment processing 28%, office productivity 28%, accounts payable and receivable 24%. Because only organisations already using AI took part, these shares describe the mix among users, not how widespread AI is.
Eurostat covers prevalence. In 2025, 19.95% of EU enterprises with 10 or more employees used AI; of those that did, 34.7% used it for marketing or sales and 23.1% for accounting, controlling or finance management. Across all enterprises the accounting and finance share is about 4.6%. For the marketing side, see AI in marketing and sales: getting measurable results.
Which accounting tasks suit automation?
Those with clear rules, repetition and volume. The ACCA report says computer vision in document processing can extract data from invoices, receipts and financial statements automatically, reducing manual entry time and errors. In one of its case studies, a large IT services company uses a tool that reads payment details in emails and PDF attachments for collections reconciliation; the tool matches 70% of collections by value automatically. Accuracy reached 70% after two to three months of learning in use, and the unmatched 30% is still reviewed by the team.
The example shows two sides of automation. Most of the workload is solved by rules and patterns; the remainder is exceptions, and people resolve exceptions. For which finance processes pay back fastest, see Automation in finance: which processes pay back in 9-10 months?.
Which tasks stay with the professional?
Exceptions, interpretation and responsibility. Under Law No. 3568, Art. 2, the subject of the accounting and financial advisory profession is to keep books, to prepare balance sheets, profit and loss statements and declarations under generally accepted accounting principles and legislation, to set up and develop accounting systems, to examine, analyse and audit on the basis of documents, to give written opinions and to prepare reports. Part of this (recording, preparing) suits automation; opinions, reports and audit are the professional's work.
The ACCA report adds a caution: outputs of generative AI cannot be fully relied upon for accuracy, and tasks requiring high accuracy need human oversight and validation. According to the report, about half of the organisations using AI consider their own risk and control measures sufficient, which shows that AI-specific risks are still being learned. The law contains no provision specific to AI; how AI output is treated in terms of professional liability should be put to a lawyer.
How is the profession's role changing?
From routine work toward judgement. In ICAEW's 2026 research on mid-tier accountancy firms (managing partners and CEOs of 35 firms, February-March 2026), 86% of firms said their technology strategy explicitly includes AI adoption and 95% expect AI use to increase over the next three years. ICAEW forecasts that the accountant's role will pivot from routine compliance and reporting to judgement, interpretation and ethical oversight by 2030. In the same research, 17% of firms believe they can assess the impact of AI on their workforce. This is a small sample in the United Kingdom and not a benchmark for Türkiye.
Where should AI in accounting start?
With data. The ACCA report names data management among the main themes of successful adoption; for how e-document data is used in reconciliation, see From the e-invoice mandate to end-to-end digital finance. The sequence below is a practical suggestion, not a sourced standard:
- Pick a repetitive process with written rules (invoice posting or bank reconciliation).
- Take the current error and time measurements; compare against the same measures after automation.
- Define the exception queue and the person who approves it up front.
- Set the scope of data inputs; for documents containing personal data, see Generative AI in the company: an internal policy.
- Plan training for the staff's new role.
For the decision-quality side, see AI in finance: from productivity to decision quality.
Conclusion
AI in accounting creates value in high-volume work such as posting, matching and report preparation; opinions, exceptions and responsibility stay with the professional. To assess which of your accounting and finance tasks suit automation, you can reach us through the contact page.
This article is for general information only and does not replace legal, financial or tax advice.
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