Content reviewed and verified by Graham Chee, with 25+ years in accounting, taxation, investment management, governance, risk & compliance. Last reviewed December 2025. Next review scheduled for March 2026.
Introduction
Why this matters for your business
AASB compliance is essential for trust, financing, and informed decision-making, but the requirements are complex and judgement-heavy. AI can help streamline reporting, improve consistency, and surface risks while giving finance teams more time for analysis. In this article, you will learn how AI applies to key AASB areas such as revenue (AASB 15), leases (AASB 16), financial instruments (AASB 9), impairment (AASB 136), consolidation (AASB 10), and disclosures (AASB 101/107/124). We also outline governance considerations, practical use cases, a step-by-step approach, and answers to common questions. The goal is to help you apply AI responsibly to strengthen compliance and support growth.
Key Concepts
Essential points to understand
Know the standards and scope: Australia adopts standards aligned with IFRS, with specific Australian modifications and not-for-profit guidance. Be clear on which standards apply to your entity (e.g., AASB 15, 16, 9, 101, 107, 124, 136, 10) and whether Simplified Disclosures (AASB 1060) are relevant.
Data foundations drive outcomes: AI performs best with clean, well-structured data. Prioritise reliable general ledger mappings, subledger detail, contracts, lease agreements, and policy documents stored in a controlled repository.
Human-in-the-loop is essential: AI can draft logic, calculations, and disclosures, but professional judgement remains critical. Require reviewer sign-offs, version control, and traceability back to source documents and specific AASB paragraphs.
Governance and assurance: Establish controls for access, privacy, and model risk. Document assumptions, keep change logs, validate models, and align with obligations under the Privacy Act and any sector-specific requirements (for example, APRA expectations for regulated entities).
Integration over manual rework: Connect AI tools to your ERP, consolidation, and document systems to reduce rekeying. Aim for structured outputs that feed workpapers, journals, and disclosure notes with clear audit trails.
Respect limitations: AI can misinterpret context or produce unsupported statements if unconstrained. Use approved templates, disclosure checklists, and standard mappings, and test outputs before adoption.
Practical Application
How this works in real businesses
AASB 15 Revenue: AI can analyse customer contracts to identify performance obligations, variable consideration, and principal versus agent considerations. It can propose allocation of transaction price and draft revenue recognition schedules with references to AASB 15 paragraphs for reviewer sign-off. Common benefits include faster contract review and more consistent policies across similar arrangements.
AASB 16 Leases: Document intelligence can extract key terms (lease term, options, CPI escalation, non-lease components) from lease agreements and compute right-of-use assets and lease liabilities. It can generate amortisation schedules, remeasurement entries, and maturity analyses to populate note disclosures. AASB 9 Expected Credit Losses: Machine learning can segment customers, estimate probability of default and loss given default, and produce provision scenarios.
Finance teams retain control to apply overlays, weight macroeconomic scenarios, and document rationale and sensitivity analysis for the workpapers. AASB 136 Impairment: AI can monitor indicators of impairment and assemble value-in-use models by pulling forecast cash flows, WACC inputs, and growth assumptions. It flags inconsistencies and drafts impairment disclosures, including key assumptions and sensitivity ranges, for management review.
AASB 10 Consolidation: Tools can identify potential control indicators from governance documents, assist with group structure mapping, generate elimination entries, and reconcile non-controlling interests, while providing cross-references to policy disclosures. Disclosures and checklists (AASB 101/107/124): Generative tools can draft accounting policies, liquidity risk tables, related party disclosures, and cash flow classification suggestions, cross-referencing to the relevant standard. They also compare current-year notes to prior-year and checklist requirements to flag gaps.
Not-for-profits (AASB 1058/15): AI can help assess whether grant terms are sufficiently specific, determine whether revenue should be recognised under AASB 15 or 1058, and produce documentation to support conclusions and disclosures. Experienced advisors recommend treating AI as an assistant within controlled workflows: formalise your accounting policies, standardise templates, require evidence links, and embed review checkpoints so that outputs are reliable and audit-ready.
Recommended Steps
A structured approach
Assess
Identify your priority standards and pain points (for example, leases, revenue, or ECL). Map data sources and document repositories. Review current controls, audit feedback, and reporting timelines. Define objectives and risk appetite with CFO, Controller, IT, and Internal Audit.
Plan
Select high-impact, low-risk use cases for a pilot. Decide on build versus buy, integration needs with your ERP and document systems, and governance policies for privacy, access, and model validation. Set success criteria and a clear review process with auditors.
Implement
Integrate data flows, configure templates and prompts aligned to your accounting policies, and enable human-in-the-loop review. Document assumptions, cross-references to AASB paragraphs, and exception handling. Train finance staff on new workflows and controls.
Review
Monitor outputs and exceptions, validate models periodically, and update for AASB changes. Capture lessons learned, strengthen controls, and scale to additional standards or entities once governance and outcomes are stable.
Common Questions
What business owners ask us
Q.Where should I start?
Begin with one standard that has structured documents and repeatable logic, such as AASB 16 leases or AASB 15 revenue for a narrow product set. Prove the workflow, then expand to more complex areas.
Q.Will auditors accept AI-assisted workpapers and disclosures?
Auditors focus on evidence, controls, and clarity. Ensure traceability to source documents, documented assumptions, reviewer sign-offs, and a stable process. Share your methodology early and address their requirements for audit trails.
Q.How do we protect sensitive financial and customer data?
Use enterprise-grade security with encryption in transit and at rest, role-based access, data retention controls, and, where required, Australian data residency. Limit training on proprietary data to approved contexts and review vendor security attestations.
Q.What systems can AI connect to?
AI-enabled workflows can integrate with common ERPs and finance systems used in Australia, including Xero, MYOB, NetSuite, SAP, and Microsoft Dynamics, as well as document management tools. Confirm API availability, data quality, and mapping rules before integration.
Q.Do we need data scientists to make this work?
Not necessarily. Many use cases rely on configuration and templates managed by finance teams with support from IT. For advanced modelling (for example, ECL), specialist expertise helps with validation, governance, and documentation.
Conclusion
Next steps for your organisation
AI can help your finance team meet AASB requirements with greater consistency while unlocking insights that inform growth. The key is to combine sound accounting policies, clean data, and strong governance with human review. If you would like tailored guidance on where AI can deliver the most value in your reporting and how to implement it responsibly, contact our team to speak with an advisor.
About the Author
Graham Chee, FCPA, GRCP, GRCA, IAIP, IRMP, ICEP, IAAP
Principal Advisor & Founder
Graham Chee is a highly qualified business advisor with over 25 years of professional experience spanning accounting, taxation, investment management, governance, risk, and compliance. As a Fellow of CPA Australia (FCPA), Graham brings deep technical expertise combined with practical business acumen. His qualifications include Governance Risk and Compliance Professional (GRCP), Governance Risk and Compliance Auditor (GRCA), Integrated Artificial Intelligence Professional (IAIP), Integrated Risk Management Professional (IRMP), Integrated Compliance and Ethics Professional (ICEP), and Integrated Audit and Assurance Professional (IAAP). Graham has advised hundreds of Australian SMEs on strategic planning, succession, business valuation, and compliance matters, helping business owners build sustainable, valuable enterprises.
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