The Comptroller and Auditor General of India said the next phase of audits will use artificial intelligence and machine learning. These tools will help identify risks and anomalies in public governance with better precision. The CAG wants to build a citizen-centric institution that provides reliable accounts through data-driven audit processes.
Synopsis
The Comptroller and Auditor General of India aims to enhance audits by adopting advanced technologies, including artificial intelligence and machine learning. This integration will allow for more precise identification of risks and anomalies in public governance. Data-driven audits will improve the overall efficiency and effectiveness of the auditing process. CAG intends to create a technology-enabled, citizen-centric institution, providing timely and reliable government accounts.
New Delhi: The next phase of audit will be characterised by deeper integration of technology, the Comptroller and Auditor General (CAG) of India has said. In its report on adding value to public governance 2025-26, the auditor said this will need expanding use of analytics-driven audits, artificial intelligence, machine learning and population-level transaction analysis will enable auditors to identify risks, anomalies and control weaknesses with greater precision and timeliness.
“Increased utilisation of data from digital platforms will support more comprehensive and evidence-based assurance,” the report said.
The experience gained from data-driven social sector audits, remote-hybrid public works audits and data-led establishment audits demonstrates the potential for scalable, technology-enabled approaches that significantly improve audit coverage, detection capability and resource efficiency.
CAG also said it wants to transform its organisation into a technology-enabled, citizen-centric institution that provides timely, risk-based audits, reliable government accounts and seamless entitlement services. This requires expanding artificial intelligence, machine learning and data analytics to examine transactions, detect anomalies and identify control weaknesses.
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