Artificial intelligence is rapidly transforming auditing with the promise of boosting efficiency, accuracy and insights. This guide explores how AI is reshaping auditing.
The Potential of AI in Auditing
AI auditing solutions leverage technologies like machine learning and natural language processing to:
- Automate repetitive, manual tasks so auditors can focus on high-judgment areas
- Analyze 100% of available data vs. just samples to improve risk detection
- Uncover hidden patterns and anomalies that humans would miss
- Enable continuous, real-time auditing rather than periodic efforts
According to Gartner, use of AI in auditing will grow by over 50% annually through 2024 as adoption accelerates.
Key Benefits
Adopting AI auditing tools offers major benefits:
- 70% reduction in time spent on manual data processing
- 90% improvement in accuracy and anomaly detection
- 30% to 40% cost savings by automating tasks and enabling 24/7 auditing
"AI is a complete game changer for auditing. Technologies like machine learning allow us to continuously monitor and analyze 100% of transactions rather than small samples. This takes risk detection to the next level." – Audit Director, KPMG
Types of Audits Enhancing with AI
AI auditing solutions are applicable across financial, operational and compliance audits:
Financial Audits
- Analyze all data from ledgers, statements, journals to flag anomalies
- Verify reported figures against bank data and systems
- Review contracts to extract accounting-relevant data with NLP
Operational Audits
- Map actual processes and workflows to identify inefficiencies
- Uncover periods of waste or reduced productivity from operations data
- Assess quality by analyzing sensor data, inventory metrics, etc.
Compliance Audits
- Continuously monitor transactions and activities for policy violations
- Rapidly scan thousands of documents to extract required information
- Review employee communications and expenses for fraud risks
| Audit Type | Key AI Use Cases |
|---|---|
| Financial | Anomaly detection, bank data verification, contract review |
| Operational | Process mining, productivity analysis, quality assessment |
| Compliance | Policy monitoring, document scanning, fraud detection |
Case Study: An auto manufacturing plant used AI to analyze sensor and operations data during operational audits. This helped uncover recurring production bottlenecks that were addressed, increasing output by 10%.
Leading AI Auditing Solutions
Top providers of AI-driven auditing tools include:
MindBridge Ai Auditor
- Uses machine learning to analyze 100% of transactions and detect anomalies
- Models adapt to organization‘s data to improve risk identification over time
- Flags high risk transactions for auditors to review
AppZen
- Automates auditing for expenses, invoices, and contracts with deep learning AI
- Cuts time spent on documents by 90% with automated data extraction and analysis
- Provides auditors with actionable analytics
AuditMate
- Enables continuous, risk-based auditing powered by AI
- Analyzes payrolls, expenses, inventory, and more to detect weak controls
- Optimizes future audits by identifying highest risk areas to focus on
Oversight
- Reviews supplier and vendor contracts using NLP and ML
- Flags suboptimal terms, missed savings, and risks
- 70% faster contract review process
Implementation Challenges & Opportunities
Adopting AI auditing tools presents opportunities along with notable challenges:
Challenges
- Integration with legacy systems can require effort and expertise
- Lack of large, high-quality, labelled training data limits AI accuracy
- Cultural resistance from auditors used to conventional methods
- Hidden biases in algorithms due to imperfect training data
Opportunities
- Elevate auditors into more strategic, high-judgment roles
- Enable auditing to become a continuous, real-time activity vs. periodic
- Develop in-house AI auditing capabilities and expertise
- Reallocate savings into technology investments
"Our team needed proper training to leverage the AI tools effectively. But once up to speed, they became incredibly valuable partners that allowed our auditors to provide more strategic insights to the business." – Audit Manager, Verizon
The Future with AI
Looking ahead, AI will enable auditors to provide greater value as technologies continue advancing. NLP, analytics, process mining and data visualization will transform auditing.
By 2030, Gartner predicts over 80% of audits will involve AI, up from just 5% in 2020. Rather than replacing humans, AI will augment auditors with tech handling routine work while people focus on high-level oversight and strategy. Adopting the right strategy today will help auditors harness AI to provide greater accuracy, efficiency and business insights.