AI in audit and accounting: what is changing, and what is not

Few subjects generate as much discussion in the profession right now as artificial intelligence. For accountants and auditors, the conversation is not abstract: analytics tools, automation and, more recently, generative AI are already changing how routine work is done. It is worth stepping back from the noise to ask two practical questions — where does this technology genuinely add value, and what remains the responsibility of the professional regardless of the tools used?

What the technology does well

Much of accounting and audit work involves handling large volumes of structured data, and this is precisely where analytics and automation are strong.

• Full-population testing. Where an auditor once tested a sample of transactions, analytics can examine the entire population — every journal entry, every invoice — to identify unusual items for closer review. This does not replace judgment, but it focuses it.
• Anomaly detection. Patterns that are hard to see manually — duplicate payments, entries posted at unusual times, round-sum figures, or transactions that breach an internal control — surface quickly through rules and models.
• Document handling. Extracting figures from invoices and contracts, matching them across systems, and reconciling large data sets are tasks that automation performs faster and more consistently than manual review.
• Drafting and research support. Generative tools can help draft routine documentation and summarise material, provided the output is reviewed and verified by a professional.

What does not change

It is equally important to be clear about what technology does not alter. An audit is an exercise in professional judgment and skepticism. The auditor forms an opinion on whether financial statements give a true and fair view, and that opinion carries weight precisely because of the auditor's independence, competence and responsibility. A tool can surface an anomaly; it cannot decide whether the anomaly is a misstatement, assess management's explanation, or weigh the sufficiency of evidence. Those judgments remain the auditor's.

The framework also does not change. Audits continue to be conducted under the Standards on Auditing issued by the Institute of Chartered Accountants of India, supported by the firm's quality-control obligations under SQC-1 and the ICAI Code of Ethics. Where technology is used, it is used within that framework: the auditor remains responsible for the evidence obtained, the conclusions drawn and the report signed.

The risks to manage

• Data governance. Analytics is only as reliable as the data it runs on. The completeness and integrity of the data set must be established before conclusions are drawn from it.
• Over-reliance. A tool that flags — or fails to flag — an item is an input to judgment, not a substitute for it.
• Explainability. The basis on which a tool reaches a result should be understood well enough to be reviewed and, if necessary, explained.
• Confidentiality. Client information is subject to strict confidentiality under the ICAI Code of Ethics. Any tool that processes client data must be assessed for where that data goes and how it is protected.
• Quality control. The use of technology needs to sit within the firm's quality-control system: how tools are selected, validated, supervised and reviewed.

What it means for the profession

The direction of travel is clear. Routine, high-volume processing is increasingly automated, and the professional's time shifts toward the work that requires judgment — risk assessment, the evaluation of evidence, the interpretation of results and advice to management and those charged with governance. For firms, this makes two things important: thoughtful adoption of tools that fit the engagement and are used under proper supervision, and continued investment in the skill and judgment of the team.

A grounded view

Artificial intelligence is a genuine change in how accounting and audit work is done, and it brings real gains in coverage, consistency and efficiency. It does not change what an audit is for, who is responsible for it, or the standards under which it is conducted. Used within that framework — with attention to data, confidentiality and quality control — technology strengthens the work. Used without that discipline, it introduces risk. The distinction lies not in the tool, but in the judgment applied around it.

This article is provided for general understanding only and should not be treated as professional advice. Please consult a qualified professional before acting.