AASB Reporting and Compliance with AI: A Practical Guide
Essential information and practical guidance for managing AASB reporting and compliance with AI in your business ATO‑ready AASB reporting support from Ding Financial
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
This guide explains how Australian businesses can streamline AASB reporting and strengthen compliance using AI. You will learn where AI adds the most value in the financial close, disclosure drafting, and audit readiness; how to reduce manual errors and accelerate reconciliations; the controls needed to remain compliant with AASB and audit expectations; and how to turn reporting data into insights for growth AI‑powered financial strategy for AASB compliance. The goal is to help finance leaders apply AI responsibly, with clear governance and practical outcomes.
Key Considerations
Essential points to understand
AASB context and scope: AASB standards are largely aligned with IFRS. High-impact areas for AI include AASB 15 Revenue, AASB 16 Leases, AASB 9 Financial Instruments (including ECL), AASB 136 Impairment, AASB 101/107 Presentation and Cash Flows, AASB 108 Accounting Policies, and AASB 124 Related Parties. Keep ASIC focus areas in mind, such as impairment, revenue, and estimates.
What AI can and cannot do: AI can extract data from documents, draft disclosures, reconcile datasets, and flag anomalies. It does not replace management judgement or audit evidence. Human review, approval, and clear responsibility remain essential.
Data governance and privacy: Define what data may be used, who can access it, and where it is processed. Consider the Australian Privacy Act and industry obligations. For sensitive data, prefer private or enterprise-controlled models with Australian data residency where required.
Controls and auditability: Maintain prompts, data sources, model versions, and output logs. Ensure reproducibility, approvals, and change control. Tie AI-generated disclosures back to trial balance line items and cite relevant AASB paragraphs where appropriate.
Integration and data quality: Connect AI workflows to ERP, consolidation, and EPM systems. Good master data, consistent chart of accounts, and clean contract repositories significantly improve AI accuracy. If you use SBR/XBRL filings, plan for tagging consistency.
Risk management and ethics: Set boundaries for acceptable use, manage confidentiality and potential bias, and implement review thresholds for estimates. For APRA-regulated entities, align AI processes with internal risk management and information security expectations.
Practical Application
How this works in real businesses
Revenue (AASB 15): AI can read customer contracts to identify performance obligations, variable consideration, and timing of revenue recognition, then draft note disclosures referencing relevant clauses. Exceptions such as complex modifications are routed to finance for review, with supporting extracts attached. Leases (AASB 16): Document intelligence can extract lease terms (commencement, payments, options) and feed calculators for ROU assets and lease liabilities. The system flags modification triggers and produces maturity analyses and discount rate disclosures for review.
Financial instruments and ECL (AASB 9): AI assists with data preparation, segmentation, and scenario overlays for expected credit loss models. Finance retains control of methodologies and assumptions, and AI produces an audit-ready pack showing inputs, overlays, and sensitivity analyses. Impairment of non-financial assets (AASB 136): AI compiles CGU evidence, collates external indicators, summarises valuation assumptions, and drafts sensitivity disclosures. Management validates key inputs such as discount rates and cash flow forecasts.
Related parties and disclosures (AASB 124/AASB 12): Cross-referencing vendor, payroll, director, and shareholder data, AI flags potential related parties, aggregates transactions and balances, and drafts the related party note for sign-off. Presentation and policies (AASB 101/107/108): AI maps trial balance to note templates, tests consistency of accounting policies year-on-year, drafts a basis of preparation, and highlights classification issues in the statement of cash flows for human review.
Audit readiness: Workpapers include data lineage, prompt history, approvals, and links to source documents. Auditors receive read-only access to evidence packs, helping focus audit time on judgement and estimates rather than document hunting.
Recommended Steps
A structured approach
Assess
Identify reporting pain points, high-effort disclosures, and areas with frequent errors. Inventory data sources (ERP, consolidation, contract repositories) and define compliance requirements, including data residency and access controls.
Plan
Prioritise 2–3 use cases (for example, leases, revenue, or related parties). Choose appropriate AI tools and determine whether a private or enterprise model is required. Design controls for approvals, audit trails, and evidence. Establish a governance framework with finance, IT, and risk.
Implement
Integrate data flows, configure prompts with references to your policies and relevant AASB paragraphs, and build validation rules (tie-outs, variance thresholds, and exception routing). Train the finance team on review procedures and document standard operating processes.
Review
Monitor accuracy, exceptions, and change logs each reporting cycle. Update templates for new or amended AASB standards. Conduct periodic internal reviews and prepare an evidence pack aligned to auditor expectations.
Common Questions
What business owners ask us
Q.Is it acceptable to use AI for AASB reporting?
Yes. AASB standards set reporting outcomes rather than prescribing tools. AI may be used if management retains responsibility, applies proper controls, and maintains sufficient evidence and documentation.
Q.Will auditors accept AI-generated disclosures?
Auditors focus on evidence, consistency, and controls. If you maintain traceability from source data to final notes, keep approval logs, and clearly document assumptions, AI-assisted outputs can be evaluated like any other tool.
Q.What data governance steps are essential?
Define permissible data, access rights, and storage locations. For sensitive information, use enterprise or private deployments with Australian data residency if required. Enable encryption, role-based access, logging, and regular reviews.
Q.Do we need specialist data science skills?
Not always. Many use cases rely on configuration and process design rather than custom modelling. However, complex areas like ECL or impairment may benefit from help by analysts or advisors experienced in modelling and governance.
Q.How do we reduce the risk of AI errors or hallucinations?
Use retrieval from approved sources, structured prompts, and strict templates. Implement automated validation checks and ensure human review of all material outputs, especially estimates and policy judgments.
Conclusion
Move forward with confidence
AI can streamline AASB reporting, reduce manual errors, and improve audit readiness when implemented with strong governance. Start with focused use cases, build the right controls, and help your finance team work smarter while maintaining compliance. Contact our team for tailored guidance on applying AI to your AASB reporting environment, selecting appropriate tools, and designing a control framework that meets your audit and regulatory obligations.
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.
Areas of Expertise:
Get Personalized Advice - Contact Us Today | Comprehensive AI accounting and ATO compliance advisory
Every business situation is unique. Our team can provide tailored guidance for your specific needs.
Trusted by Australian business owners