IMPACT OF ARTIFICIAL INTELLIGENCE ON AUDIT QUALITY: PROFESSIONAL JUDGEMENT, RESPONSIBLE AI GOVERNANCE, AND THE INDIAN AUDIT CONTEXT

Abstract

Artificial intelligence (AI), including machine learning, document intelligence, generative AI and advanced analytics, is reshaping the way audit teams identify risk, analyse transactions and evaluate evidence. Yet greater analytical capacity does not automatically produce higher audit quality. AI outputs may be incomplete, difficult to explain, biased by source data or accepted too readily by time-pressured professionals. This conceptual paper develops a framework for understanding how AI-enabled auditing may influence perceived audit quality in India, with professional judgement positioned as a key conditioning mechanism. Drawing on the Technology-Organisation-Environment perspective, the Technology Acceptance Model, agency theory and research on automation bias, the paper integrates technological capability with governance, competence, scepticism and accountability. It proposes that AI-enabled auditing is more likely to support audit quality when data and models are reliable, use is aligned with audit objectives, and auditors independently evaluate AI-generated outputs. Professional judgement is expected to strengthen the positive association between AI-enabled auditing and audit quality, while automation bias and weak governance may attenuate it. The paper does not report primary-data findings; instead, it offers propositions, a research-ready measurement framework and a rigorous empirical agenda. The Indian context is timely given the Institute of Chartered Accountants of India's AI Innovation Summit in 2026 and the Government of India's risk-aware AI governance direction. The contribution is a practical, testable account of how audit firms can combine AI capability with human responsibility without confusing automation, efficiency and audit quality.