Accounting Tasks AI Should Not Automate: The CFO's Guide

AI usage in core business operations is at an all-time high. In fact, recent research from McKinsey found that 88% of respondents in a recent survey regularly use AI in at least one business function. This is a 10% increase from 2024. While AI can certainly lower costs, promote innovation, and support accounting operations, there are limitations and tasks it should not automate.

AI can’t use empathy, moral judgment, common sense, or creativity in outputs. It can’t solve complex problems that rely on both financial data and critical thinking skills. Human expertise still matters. This makes it no surprise that 65% of organizations seen as high AI performers use a human-in-the-loop strategy as a best practice.

In this blog, we’ll cover accounting tasks AI should not automate, helping you find the optimal balance through a hybrid AI outsourcing strategy.

The Rise of AI in Finance & Accounting

AI has become embedded in fundamental finance and accounting tasks. It’s highly unlikely that repetitive tasks, like data entry, are completed manually anymore. The initial roots of AI in the accounting realm date back to the late 1970s with the rise of the VisiCalc spreadsheet. This spreadsheet eventually transitioned into what’s known as Microsoft Excel today.

The 2010s saw another round of new AI technology, with accounting software beginning to create AI-powered programs. Automatic bank categorizations, expense management programs, and predictive analysis all went into effect. Today, nearly 98% of accountants and bookkeepers use some type of AI.

Curious about how this technological shift is changing the day-to-day responsibilities of your team? Explore our deep dive: From Data Entry to Decision Makers: How AI is Shaking Up Accounting Roles.

Why AI Can’t Replace Accountants

While artificial intelligence excels at processing massive datasets, the nuances of corporate finance require more than just computational power. The strategic complexities of financial leadership demand human attributes that algorithms simply cannot replicate. Here is why true advisory work and reliable financial planning will always require a human-in-the-loop approach:

Human Judgment Matters

Judgment matters in financial reporting and accounting decisions. Many tax code provisions and GAAP standards have room for interpretation. An AI model can’t make informed decisions based on specialized situations.

Client Relationships are Important

Relationships are at the core of accounting. Many accounting professionals often say that the profession is a relationship business. AI can’t give empathetic advice or provide an understanding of complex situations.

Accountability Improves Results

Accountants can provide accountability, not just in your data, but in your core processes. They can review your financial results, make judgment-based adjustments, and follow up on strategic goals. This level of advisory work isn’t something AI offers.

Compliance is Complex

Let’s say you have a problem with a tax filing. Can your AI agent call the IRS? No. The IRS does not even accept electronic signatures on certain forms. Human accountants are essential when dealing with the IRS and other regulatory agencies.

Data Privacy is a Concern

AI workflows are still in their infancy; however, they’ve already become a hot spot for cyber hacks and attacks. According to Stanford’s AI Index Report, there was a 56.4% rise in AI incidents in 2024. Working with accounting firms and outsourced professionals with the necessary safeguards and human oversight is crucial.

Despite the rapid advancement of these tools, human oversight remains non-negotiable. For a closer look at the future of the profession, read: The Automation Era: Will Accounting Teams Become Obsolete?

Accounting Tasks AI Should Not Automate: What CFOs Should Never Delegate

By now, it should be clear that AI can’t replace human expertise in finance and accounting. This can leave you wondering what tasks require human oversight. Here are the accounting tasks AI should not automate:

High-Level Decision-Making

High-level decision-making can be subjective and is often based on factors outside of financial data. Tasks, like interpreting financial statements, planning for growth, or creating budgets, should be left to humans. While AI and automation can be useful in the initial data entry and creating real-time reports, any decisions based on the information provided are up to the CFO.

Client Confidentiality

Managing clients’ confidential information shouldn’t be left to AI in your finance function. Public AI models create a higher risk of data leakages. Not to mention, using these models can break privacy regulations. For example, your finance team shouldn’t ask an AI model to summarize the results of your financial statements or ask for advice on how to make a contract more profitable. Anything involving sensitive information should be completed by a human.

Legal and Ethical Decisions

The right legal and ethical decisions can easily be missed by AI. Let’s say that you are expanding your client base domestically. You enlist the help of an AI program to track sales to different states. However, your AI program neglects to factor in fees paid directly out of revenue, creating understated revenue figures. As a result, you missed filing a state sales tax return. Artificial intelligence doesn’t always know what’s right and what’s wrong, which is when human expertise comes into play.

Technical and Data Integrity: Tasks AI Should Not Automate

While it can be easy to have AI handle your accounting and finance transactions, it can cause serious problems. For example, if AI incorrectly inflates revenue, how will the board and owners react? What happens if these mistakes make it into filed tax returns? CFOs and finance leaders have an obligation to promote transparency in the finance function, which is why technical and data entry validation should not be automated.

Specific Client Cases

Clients still want an interpersonal relationship with the people they work with. If AI is handling all interactions, clients have no obligation to stay loyal to your business. For example, if a client calls and requests a copy of their outstanding amount in accounts receivable, does an AI chatbot handle the conversation or are they communicating directly with a member of your finance team? Bolstering client relationships can improve recurring revenue and brand loyalty.

Vendor Communication

The same goes for vendors. Improving your vendor relationships can result in exclusive discounts and an overall better working relationship. AI-powered programs may be able to help match payments from your bank statement to invoices, but they shouldn’t be used in the front-facing role of your finance department.

Policy Changes

Policy changes are highly individualized and rely on human judgment. Let’s say that you are trying to find a cost-effective way to rework paid leave in your company. An AI program might say to cut leave by 20% across the board. However, AI doesn’t take into consideration the impact on your employees. Will turnover increase? Will your workplace culture decline? Any type of policy change should be left to finance and accounting professionals.

What AI Should Handle

By delegating high-volume transactional work to automation, finance leaders can free up their teams to focus on value-added analysis and strategic growth. Here are the most effective and secure applications for AI in your daily accounting workflows:

AR and AP Entry

Initial accounts receivable and accounts payable entry can be delegated to AI. For example, you might have a program that reads scanned invoices and inputs the information into your system. However, your finance team should still review AP and AR ledgers for accuracy.

Expense Management

Employee expense management can be facilitated using AI programs. For example, your employees can upload a copy of their receipt into a program. This program then sends the amount to the proper manager for approval. Any accounting tasks that involve data entry can utilize AI.

Repetitive Tasks

Any type of repetitive task that does not include sensitive information can be shifted to an AI program. For example, in your accounting workflows, you might have rules established for clearing bank transactions, such as Caribou Coffee always being reported in the meals account. AI can easily clear these transactions from your screen. However, any data entry done by AI should be reviewed by a human for accuracy.

The 30% Rule in AI

Knowing how much AI to use in your organization is dependent on a variety of factors, from team dynamics to strategic goals. However, a baseline framework on AI usage that many CFOs follow is the 30% Rule. The 30% Rule says that about one-third of tasks should require human input, while 70% can use AI and automation.

For example, AI might categorize all of your bank transactions, while a human completes the bank reconciliation. 70% of the work is already done, leaving an accounting or finance professional to verify the categorizations and make any adjustments.

A CFO’s Checklist: How to Evaluate What to Delegate to AI

Every organization is different. The accounting tasks one organization shouldn’t delegate to AI might not be the same as your company. As CFOs, it’s your job to evaluate which roles and tasks can be moved to AI, and which strategic work should be kept with a human.  Here’s a five-step process on how to evaluate what to delegate to AI:

1. Differentiate Tasks – First, differentiate between tasks that can be delegated to AI and tasks that need to be human-led. Use our previous sections as a starting point.

2. Assess Offerings – After you have a list of tasks that are safe for AI in accounting, look at your resource offerings. One of the disadvantages of AI in accounting is that software programs can become extremely expensive. Make a list of cost-effective alternatives. It’s okay if some tasks aren’t worth outsourcing to AI right now.

3. Determine Risk Appetite – Compile a list of all of the potential risks of using AI for certain tasks. Would AI potentially increase your risk of noncompliance or undetected errors? What would be the outcome if those risks happened? What boundaries would be in place to lower potential risks?

4. Look at the Big Picture – Before you outsource an accounting task to AI, look at the big picture. What would be the impact on your team of outsourcing the task? Would it help them or result in more work from multitasking with a new system and validating outputs?

5. Avoid Over-Automating – Equipped with all of the above information, make an informed decision. Remember, strategic work should never be delegated to AI. Over-automating can lead to excessive dependency on technology, reduce flexibility in operations, and create an impersonal feel to your business.

Need a more comprehensive framework for handing off these workflows? Check out our complete CFO's Guide to Delegating Accounting Tasks to ensure a smooth transition.

The Hybrid AI Outsourcing Model

The benefits of AI in accounting should not go unused in your organization. However, finding the optimal balance between AI usage and human oversight is essential. The most successful finance leaders are adopting a hybrid AI outsourcing model, combining the processing power of advanced automation with the strategic oversight of dedicated, highly trained accounting professionals.

AI won’t replace accountants in advisory work, financial reporting, and decision-making, but it can help improve efficiency and accuracy in your workflows. If you’re ready to learn about the Personiv advantage and how our team can help you blend AI and world-class human expertise in your organization, contact a team member today.