AI, Accounting and Compliance in 2025: What Firms Need to Know

AI in Accounting Firms: Navigating Regulatory Guidance and Implementation

Artificial Intelligence (AI) is transforming the accounting landscape, offering opportunities for enhanced efficiency and compliance. However, with these advancements come responsibilities, especially concerning regulatory expectations and ethical considerations.

AI offers exciting opportunities for firms to increase productivity, automate decision-making, and better serve clients. But as tools become more powerful, Australian regulators are sounding a clear warning: governance, transparency, and data protection must evolve just as quickly.


Regulatory Perspectives on AI in Accounting

ASIC – “Beware the Governance Gap”

ASIC’s 2024 REP 798 report warned that AI adoption is often outpacing governance. Key issues:

  • 50% of licensees had no policies addressing fairness or bias.

  • Most did not inform customers about AI involvement in decision-making.

  • Many had no audit or monitoring mechanisms for AI outputs.

Implication: If your firm uses AI (even indirectly), your policies, disclosures, and controls must keep pace—or risk non-compliance.


AUSTRAC – Transparency & Human Oversight

AUSTRAC released an AI Transparency Statement in February 2025, committing to:

  • Responsible, ethical, and explainable AI use.

  • Mandatory internal AI training.

  • Human oversight of AI-generated decisions.

Implication: You’ll need to demonstrate the same transparency, especially when AI touches customer data, compliance, or financial crime systems.

AUSTRAC has developed internal AI capability to support its mission in detecting financial crime. It’s also encouraging firms to use AI to enhance their AML/CTF programs, with cautions about governance, auditability, and data integrity.

CPA Australia

CPA Australia has issued guidance on the use of generative AI in accounting practices, outlining key considerations:

Chartered Accountants ANZ (CA ANZ)

CA ANZ supports innovation while stressing professional and ethical standards. They provide:


2. Practical Actions for Accounting Firms

Here’s how to stay ahead of regulatory expectations—and build trust with clients and boards alike.

Understand the Types of AI You’re Using

Not all AI is equal in risk or complexity. Examples:

Type of AI Description Examples in Accounting & Financial Services
Predictive Analytics Uses historical data to forecast future outcomes Client churn prediction, lead scoring, tax liability forecasting, cash flow projections
Natural Language Processing (NLP) Interprets human language (text or speech) Chatbots for client FAQs, email classification, invoice data extraction, document summarisation
Machine Learning (ML) Learns from data patterns without explicit programming Fraud detection in accounts payable, automated expense categorisation, credit scoring models
Generative AI Produces new content based on training data Drafting financial reports, generating engagement letters, paraphrasing meeting notes, email responses
Computer Vision Interprets and understands images or visual data OCR for scanning receipts/invoices, validating physical IDs, reading scanned financial documents
Reinforcement Learning Learns via trial and error to optimise decision-making Adaptive investment portfolio strategies (in larger firms), audit strategy simulation (in R&D)
Expert Systems Encodes human expertise into decision rules Tax advisory decision trees, audit checklists, logic-driven eligibility or compliance assessments

What to do: Document all use cases, identify which types are in scope, and assess their level of risk—especially if they’re client-facing or decision-influencing.

Before You Implement AI: Key Considerations

AI implementation isn’t just plug-and-play. Before your firm introduces AI-powered tools, consider:

Data Location
Where will your client data be stored or processed? Public models may send data overseas—check residency and retention policies.

Bias in AI Models
Even the best AI can reflect data bias. Use AI as a co-pilot, not a sole decision-maker—especially in compliance or financial forecasting.

Types of AI Models

  • Public models (e.g. ChatGPT) offer ease of access but pose risks.

  • Private/fine-tuned models increase control and relevance.

  • On-premise AI can ensure compliance but may require IT investment.

Security and Confidentiality
Ensure tools meet ISO 27001 or similar standards. Don’t paste confidential data into unverified AI tools.

Executive Oversight
Boards and partners must understand the AI tools being used and ensure internal policies are updated accordingly.

AML/KYC Compliance
AUSTRAC expects high-risk areas like AML/KYC to maintain transparency and full auditability, even if AI tools are used.

Third-party Risk Management
CPS 230 (which applies to APRA-regulated entities) outlines vendor management responsibilities—these best practices also apply to accounting firms using external AI vendors.

Staff Training and Culture
Your team must know what AI is, what it isn’t, and how to use it safely. Embed AI education into your practice’s culture.


🔍 How Argo Logic Can Help

At Argo Logic, we specialise in helping accounting and financial services firms implement AI responsibly and strategically. We can support you with:

An AI Readiness Audit tailored for accounting firms
Risk and data mapping across your practice
AI tool selection and vendor due diligence
Security and compliance frameworks aligned with ISO 27001 and CPS 230 principles
Change management, staff training, and updated policies
AML/KYC process design, including automated checks, alerts, and reporting

We don’t just plug in tools—we help you build a tech roadmap that makes sense for your business.


📞 Let’s Talk

Interested in using AI safely, ethically, and efficiently?
👉 Contact Argo Logic for a free AI Readiness Consultation and discover how we can futureproof your firm—while staying compliant.

GET IN TOUCH With ARGO

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