AI for AASB: Boost Valuation and Growth with Smart Compliance

Essential information and practical guidance for managing AI-enabled AASB reporting and compliance in your business

Graham Chee
Graham CheePrincipal Advisor & Founder
FCPA
GRCP
GRCA
IAIP
IRMP
ICEP
IAAP
Published 28 December 2025
Expert Content Verification

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

Strong AASB compliance is more than a reporting requirement. It underpins earnings quality, reduces perceived risk, and supports confident decision-making by boards, lenders, and buyers. AI-powered tools can help standardise data, enhance controls, and give finance teams the time and clarity to focus on what drives value.

This article explains how AI can support AASB reporting, where it adds practical value, and how to adopt it responsibly. You will learn key concepts, see how it applies in real businesses, and get a structured approach to move forward with confidence.

Key Considerations

Essential points to understand

Reporting quality drives valuation: Consistent, well-supported AASB reports improve confidence in your numbers, which can reduce perceived risk and strengthen valuation narratives during funding, banking, and exit discussions.

Data foundations and audit trails: AI works best with clean, structured data and clear evidence. Design for auditability with version control, justification logs, and reproducible calculations.

High-impact AASB areas for AI: Revenue recognition (AASB 15), leases (AASB 16), expected credit losses (AASB 9), fair value and impairment (AASB 13 and AASB 136), provisions (AASB 137), income taxes (AASB 112), and presentation/disclosures (AASB 101, AASB 107, AASB 108).

Controls, governance, and explainability: Use AI as decision support with human review. Establish policies for materiality, thresholds, model approval, and documentation so outputs are explainable to management, auditors, and regulators.

Integration and change management: Plan how AI will connect to your ERP, general ledger, and source systems (e.g., Xero, MYOB, NetSuite, SAP, Oracle). Align roles, responsibilities, and approval workflows.

Risk, privacy, and vendor due diligence: Assess data security, storage location, access controls, and vendor certifications. Confirm how models are updated, monitored, and governed to avoid drift or bias.

Practical Application

How this works in real businesses

Lease accounting (AASB 16): AI can extract lease start/end dates, options, CPI clauses, and incentives from contracts, propose classification, and calculate right‑of‑use assets and lease liabilities. It can flag potential modifications, remeasurements, and impairment indicators, while maintaining an audit trail of assumptions and discount rates.

Revenue recognition (AASB 15): For businesses with subscriptions, projects, and support services, AI can analyse contracts to identify performance obligations, variable consideration, and timing of revenue. It can propose allocation of transaction prices and generate supporting documentation for management review and auditor queries.

Expected credit losses (AASB 9): AI can segment receivables, incorporate forward‑looking information, and calibrate ECL models with governance around overlays. Finance can review recommended provisions, stress test scenarios, and document rationale in line with policy.

Fair value, impairment, and provisions (AASB 13, AASB 136, AASB 137): Tools can assist with data gathering, comparables screening, and assumption consistency checks. They help standardise impairment testing models (cash‑flow integrity, growth and discount rate consistency, and sensitivity analysis) and support provision estimates with scenario evidence and controls.

Consolidation and close: AI can match intercompany transactions, flag anomalies, and suggest eliminations with references to supporting entries. Disclosure checklists can be auto‑mapped to your trial balance and notes, highlighting gaps before audit.

Governance and audit readiness: Every AI‑assisted recommendation should come with an explanation, inputs, and links to source data. Approvals, overrides, and thresholds are captured in a control log, improving preparedness for auditor walkthroughs and due diligence reviews.

Valuation lens: By strengthening policies, standardising calculations, and improving disclosure quality, AI‑enabled finance functions can present more predictable earnings, clearer cash conversion, and tighter working‑capital discipline—factors that institutional investors and acquirers examine closely.

Recommended Steps

A structured approach

1

Assess

Identify your material AASB areas (e.g., AASB 15, 16, 9, 13/136). Map current policies, pain points, data sources, and control gaps. Prioritise 2–3 use cases with measurable compliance and governance benefits.

2

Plan

Design target processes, data pipelines, roles, and approval workflows. Define success criteria, documentation standards, model oversight, and auditor touchpoints. Select technology that fits your ERP and security requirements.

3

Implement

Integrate data feeds, configure models and thresholds, and establish human‑in‑the‑loop reviews. Pilot with a contained scope (such as leases or ECL), validate results against policy, and formalise controls and evidence packs.

4

Review

Monitor performance and model drift, calibrate assumptions, and update accounting policies as needed. Extend to additional standards and disclosures once governance is stable and audit feedback is incorporated.

Common Questions

What business owners ask us

Q.Is AI relevant for SMEs and growing businesses, or only large enterprises?

It is relevant for both. Start with focused use cases that are material to your business—often leases (AASB 16), revenue (AASB 15), or ECL (AASB 9). A phased approach allows you to build governance and confidence before broadening scope.

Q.Will AI replace accountants or auditors?

No. AI supports accounting judgments by improving data quality, consistency, and documentation. Management remains responsible for policy decisions, and auditors evaluate evidence and controls. Human review and approval are essential.

Q.How accurate are AI outputs and how are they validated?

Accuracy depends on data quality, configuration, and governance. Establish validation procedures, materiality thresholds, exception handling, and periodic recalibration. Keep a clear audit trail of inputs, assumptions, and approvals.

Q.What about data security and privacy?

Perform vendor due diligence on hosting location, encryption, access controls, and certifications. Apply data minimisation, role‑based access, and monitoring. Confirm how your data is used, stored, and deleted, and engage your auditors on the control environment.

Q.How does this integrate with our existing systems?

Most platforms connect via APIs or secure file exchanges to common ERPs and accounting systems. Plan your data model and mapping early, define a single source of truth, and test end‑to‑end with your close calendar and reporting timetables.

Conclusion

Turn compliance into a growth advantage

AI can help finance teams elevate AASB reporting, strengthen governance, and support better decisions about capital, growth, and risk. The right approach is pragmatic: start small, design for auditability, and scale with strong controls.

If you would like tailored guidance for your business, speak with an advisor who understands both AASB requirements and AI enablement. Contact our team to discuss your goals and the best path forward.

About the Author

Graham Chee

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:

Strategic Business Advisory
Taxation Planning & Compliance
Business Valuation
Succession Planning
Investment Management
Governance & Risk
Regulatory Compliance
Financial Reporting
Experience: 25+ years in accounting, taxation, investment management, governance, risk & compliance

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