Internal audit has evolved significantly over the decades as a business process, transitioning from being just a compliance-driven function to a strategic partner focused on managing risks, enhancing governance and improving business efficiency.
In recent years, advancements in technology, particularly artificial intelligence (AI), have been crucial in transforming the internal audit (IA) landscape.
AI has become a key enabler for modern audit practices, streamlining processes and adding depth to risk assessment and control evaluation.
AI offers significant opportunities to revolutionize IA by automating routine tasks, improving accuracy and enhancing the overall effectiveness of the audit process.
What is AI and how is it used in internal audit?: Disruptive technologies like AI, machine learning and cloud computing have been around for some time now.
Companies across industries have been using algorithms and automation to process transactions, enhance customer service and support executive decision-making for years. What is new is the pace of change.
AI refers to the use of algorithms and machine learning models that simulate human intelligence to perform tasks such as data analysis, decision-making, pattern recognition and language processing.
AI tools enable organizations to process vast amounts of data more efficiently, identify anomalies and uncover trends that might be missed using traditional methods.
In IA, AI can be applied to various tasks, from automating repetitive procedures to enhancing predictive risk assessments, detecting fraud and providing real-time monitoring of other business processes, thereby reducing the risk of human error.
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