Protexure Accountants Blog

Is Your Firm Ready? Machine Learning for Accounting is Here to Stay

Written by Christie Brandenburg | Jul 29, 2025 2:00:00 PM

Few tools have sparked more conversation—or transformation—than artificial intelligence.  

Machine learning for accounting is more than just a buzzword; it is becoming a foundational tool for firms seeking to improve accuracy, efficiency, and value-added services. From tax prep to document review, this technology is already reshaping how accounting professionals work.

But like all revolutions, it comes with both promise and pitfalls. 

How firms are using machine learning for accounting tasks 

Whether it is a global Big Four firm or a regional practice, accounting professionals are integrating machine learning into their workflows in increasingly creative ways. AI tools automate data entry, analyze complex financial records, generate memos, and even scan physical mail. 

The Big Four—Deloitte, EY, KPMG, and PwC—have heavily invested in AI. For example, Deloitte built a document review tool that quickly extracts critical data from contract populations. EY uses AI to audit unstructured data, helping flag fraud risks. Meanwhile, KPMG offers a "Trusted AI" framework that assists clients with designing and deploying their own AI tools. PwC’s developers use generative AI to write and review code, citing productivity gains of up to 50%

Small and mid-sized firms are also turning to machine learning for accounting to stay competitive. Common use cases include: 

  • Bookkeeping automation: AI-powered platforms categorize expenses and reconcile accounts.
  • Tax research: Algorithms return accurate, sourced answers from vast tax databases.
  • Return preparation: Tools extract data and identify eligible deductions, reducing human error and time.
  • Document summarization: AI condenses contracts and invoices, identifying anomalies for review. 

These examples reflect a shift from number-crunching to strategic advising, giving accountants more time to focus on complex analysis and client relationships. 

Read more: Understanding the Corporate Transparency Act and its Impact on Accounting Firms 


Labor cost reductions and productivity gains 

 

Automation through machine learning has the potential to significantly reduce overhead and increase efficiency. One firm reported saving four hours a week simply by automating incoming physical mail. Others now use AI-assisted coding to automate Excel tasks and custom reports that once required outsourced developers. The result? Projects that previously cost thousands and took days are now completed in hours at little to no extra cost.

In short, machine learning for accounting is not just about doing things faster. It is also about doing them cheaper and with fewer resources.  

 

Risks and concerns: What firms need to know 

 

Despite the benefits, adopting machine learning is not without risk. Ethical, legal, and operational challenges must be addressed to maintain client trust and regulatory compliance. 

1. Data privacy and legal exposure: Firms must evaluate how client data is processed, stored, and used. Laws like the Gramm-Leach-Bliley Act and new state privacy laws may require disclosure if AI tools use sensitive information

2. Overreliance on automation: Generative AI tools can hallucinate or produce inaccurate outputs. If accountants fail to review AI-generated work, they risk errors that could lead to professional liability insurance claims.

3. Transparency: Failing to disclose AI use can damage client relationships. Some clients may appreciate AI-driven services, while others may have concerns over data use or quality control. Either way, disclosure builds trust. 

4. Workforce transition: While AI augments professionals, some roles may decline, particularly in data entry or clerical work. The World Economic Forum has identified accounting clerk roles as high-risk for obsolescence. 

Also read: What Accountants Need to Know About the Potential SCJA Sunset 

 

Building a responsible AI use policy 

 

To mitigate risk, firms should create formal policies that govern how AI is used internally and with clients. Key elements of an effective policy include: 

  • Disclosure and consent: Clearly communicate when and how AI is used. Avoid generic language in engagement letters; instead, describe the technology, intended use, and safeguards. 
  • Review protocols: Require human oversight for all AI-generated outputs, especially client deliverables.
  • Data governance: Establish how client data is stored, accessed, and shared, particularly with third-party AI providers.
  • Ongoing training: Offer staff training on how to use AI tools safely and effectively, encouraging experimentation in low-risk environments.

By treating AI governance as a component of risk management, firms can safely harness its benefits without exposing themselves to unnecessary liability. 

 

Protecting your firm in the age of AI 

 

Machine learning is here to stay. The accounting profession’s future will be shaped not just by who adopts it, but by who adopts it wisely. 

With that said, even the best AI systems—and professionals—make mistakes. If a misstep leads to a client lawsuit, your firm could face steep legal expenses. That is why Professional Liability Insurance from Protexure Accountants is a critical safeguard. 

This “Errors and Omissions” insurance protects your practice in the event of a covered claim, such as: 

  • Failure to meet a deadline or statute of limitations
  • Poor advice related to tax or accounting issues
  • Conflicts of interest or failure to follow client instructions

Protexure Accountants offers tailored policies for solo and mid-sized firms, with competitive pricing and excellent customer service. In an age of evolving technology—and evolving risks—this protection can be the safety net your firm needs. 

Contact us today.