Клиент: AuditBoard, Inc.
Формат: Проектный документ
Размер: 1,3 МБ
Язык: English
Дата: 16.12.2025
How to get started with AI in audit: The essential guide
Are you equipped to leverage AI in your audit work? This KPMG and AuditBoard guide is your must-have roadmap. Learn how to use automation and large language models (LLMs) to gain a comprehensive view of your risk environment and enable you to focus on strategic advisory work. The guide includes 12 examples of use cases and a clear six-step plan to begin your journey today.
AI is fundamentally changing the role of technology in audit, risk, and compliance. The question is no longer if you’ll use AI in internal audit, but how. GRC activities have historically relied on highly manual processes. AI capabilities in automation, data analysis, machine learning (ML), large language models (LLMs), and natural language processing (NLP) can help practitioners do this work more efficiently. AI tools also enable broader audit coverage and deeper risk assessments, providing a more comprehensive picture of risk than ever before.
Internal audit’s ability to “connect the dots” to help management understand risks, issues, and root causes in context has always been among the profession’s key value propositions. Now, AI tools can connect more “dots” than human auditors can see. But it’s the auditors who can translate AI’s results into a discernible picture of how a given risk could impact the entire business. This more complete view of risk is hugely valuable, enabling internal auditors to provide insights that help management improve risk management and decision-making. Further, AI will enable auditors to dedicate more time to strategic advisory work, propelling the profession towards the IIA’s 2035 vision.
Internal auditors should embrace this opportunity to rethink and enhance their methodologies. It’s time to give AI the low-value, high-intensity work and let the humans focus on what has always been the most meaningful part of the role: providing the risk and strategic insight and assurance that helps our organisations protect, create, and enhance value.
The hardest parts now are (1) proving that AI can be relied upon and (2) upskilling ourselves and our teams in using AI effectively. That’s why this guide is focused on practical use cases you can try both today and as you advance your capabilities. Download your copy and get started!
AI is fundamentally changing the role of technology in audit, risk, and compliance. The question is no longer if you’ll use AI in internal audit, but how. GRC activities have historically relied on highly manual processes. AI capabilities in automation, data analysis, machine learning (ML), large language models (LLMs), and natural language processing (NLP) can help practitioners do this work more efficiently. AI tools also enable broader audit coverage and deeper risk assessments, providing a more comprehensive picture of risk than ever before.
Internal audit’s ability to “connect the dots” to help management understand risks, issues, and root causes in context has always been among the profession’s key value propositions. Now, AI tools can connect more “dots” than human auditors can see. But it’s the auditors who can translate AI’s results into a discernible picture of how a given risk could impact the entire business. This more complete view of risk is hugely valuable, enabling internal auditors to provide insights that help management improve risk management and decision-making. Further, AI will enable auditors to dedicate more time to strategic advisory work, propelling the profession towards the IIA’s 2035 vision.
Internal auditors should embrace this opportunity to rethink and enhance their methodologies. It’s time to give AI the low-value, high-intensity work and let the humans focus on what has always been the most meaningful part of the role: providing the risk and strategic insight and assurance that helps our organisations protect, create, and enhance value.
The hardest parts now are (1) proving that AI can be relied upon and (2) upskilling ourselves and our teams in using AI effectively. That’s why this guide is focused on practical use cases you can try both today and as you advance your capabilities. Download your copy and get started!
