AI in accounting: A virtual colleague, not competition

8 min read
AI in accounting represented by image of woman's hand using computer mouse

Artificial intelligence (AI) is a buzz-worthy topic regardless of your background, profession, or age, and while AI has existed since the 1950s, AI in accounting is more prominent now due to its accessibility and functionality in public and professional spaces. 

Today, many of us use AI in some form all the time. My fifth-grade son and I wrote a spooky short story using Chat-GPT as our co-author and creative muse. My friend sent me DALL-E generated art of a watercolor painting of cowboys wearing pajamas and eating spaghetti at the beach under a full moon. And who doesn't ask Siri for directions to their hotel in a new city or take a picture of a check and deposit it from their phone? 

You can also use AI as an accountant; many professionals are already embracing the new technology. While I first viewed it with skepticism, now I look at it with optimism for myself as a former practitioner turned professor and for my students entering the profession. Accounting AI is on track to become a tireless colleague who will help us do our jobs more efficiently and thoroughly, saving us from late nights we've all seen too often. 

But how? 


While some accountants see AI as a threat, it can actually be a valuable tool to help support and streamline your work. Through machine learning, natural language processing, and automation, accounting AI can take on the tedious tasks of data entry and report generation as well as support strategic decision-making, though its important to understand the need for human understanding and insights. 

What is Artificial Intelligence?  

AI is the capability of a machine to imitate intelligent human behavior and perform tasks that would typically require human intelligence. Intelligence in this context is the ability to learn, understand, and apply knowledge and skills.  

While artificial intelligence capabilities are incredibly advanced, your input is key to its success. Without critical thinking and professional judgment to create prompts, set up tests and run automation, using AI in accounting will result only in headaches and confusion.  Whether you're a leader, practitioner, or educator, you must understand AI's capabilities and when and how to implement them. 

Types of AI in accounting and how to use it  

With this in mind, let's look at different types of AI capabilities and how today's accountants can use them. 

Machine learning 

Machine learning creates algorithms and models that empower computers to acquire knowledge, make predictions and make decisions without requiring explicit instructions.     Accountants can use machine learning to:  

  • Perform risk analysis to understand relationships between variables better 
  • Review potential fraudulent scenarios based on hypothetical and real situations 
  • Forecast financial performance 
  • Determine optimal tax savings for a client through a review of deductions, credits, and tax laws

Natural language processing 

Natural language processing (NLP) is the ability of a computer to understand, interpret, and utilize written and spoken human language. Natural language generation (NLG) is a branch of NLP that focuses on producing language that simulates human speech and writing.     

Accountants can use NLP to:  

  • Extract pertinent language in lengthy documents for regulatory and compliance procedures
  • Verbally record inventory counts 
  • Reconcile workpapers to source documentation such as invoices or purchase orders

 Accountants can use NLG to:  

  • Generate documentation based on notes 
  • Record meeting minutes 
  • Double-check calculations 
  • Generate filled-out templates based on input 
  • Write first drafts of reports 
  • Summarize findings 
  • Review reports for established criteria.     

Computer vision 

Computer vision allows computers to "see" and comprehend visual data, enabling them to analyze images and videos. Machine vision is a branch of computer vision used to interpret and understand images focusing on industrial automation and inspection.    

Accountants may use computer vision (including optical character recognition or OCR) in the following ways:  

  • Extract information from supporting documentation 
  • Digitize documents to make them machine-readable and editable 
  • Detect and classify inventory in images or video for accurate counting and documentation Implement biometrics as internal controls 

Accountants can also use machine vision in managerial accounting for quality assurance and process management.          


Automation (including Robotic Process Automation) employs software bots to automatically manage repetitive, rule-based, and mundane tasks typically performed by humans. Intelligent automation enables automation to utilize other AI capabilities, such as machine learning, NLP, and computer vision.     

Accountants can use intelligent automation for:

  • Completing data entry 
  • Creating sample selections for testing 
  • Creating amortization schedules 
  • Performing audit confirmations 
  • Generating reports and e-mails 
  • Performing routine audit tests and reconciliations

For example, intelligent automation using OCR could match purchase orders, receiving documents and invoices (three-way match) before invoice payment, regardless of the origination channels or format.  

A comprehensive example of AI in accounting 

Let's look at how AI in accounting can streamline a common financial accounting scenario. 

You have a 42-page hard copy of a lease agreement for a warehouse your company is renting and have been asked to classify it and create an amortization schedule. You could pour yourself that fifth cup of coffee and begin reading or embrace AI to save time and improve accuracy with these steps:  

  1. Use OCR to digitize the lease agreement.  
  2. Allow NLP and machine learning techniques to interpret, understand, and categorize the document's details and identify payment schedules, lease durations, and other critical financial clauses.  
  3. Generative AI can reference FASB standards to summarize the agreement and note how the lease should be classified. 
  4. Generative AI can then use the extracted data to create a detailed amortization schedule automatically and map out the payment timeline and amounts based on the agreement's terms.  

Now, you can review the output rather than create it. 

Understanding the current limitations of AI in accounting 

While AI is changing the way accountants can and will do their jobs, there are still many limitations to what AI can achieve. 

Limited by its training 

Accounting AI is poised to significantly augment human creativity and analytical capacity, but it’s not there yet. AI lacks sentience and self-awareness, which restricts its ability to think creatively, and it is highly dependent on the quality and breadth of its training data. Instead of AI driving any innovation, humans must understand and evaluate the new challenges and concepts first. 

Not all accounting AI is created equal 

Not all AI is created equally, nor are the companies that employ it. When you think about artificial intelligence processes, you probably think of advanced systems and software programs that integrate effortlessly with huge quantities of high-quality data, creating crisp reports through intuitive, well-designed dashboards. 

But the reality is that the integration of AI in accounting processes often reflects the scale of the firm. Large organizations can adopt advanced, high-cost AI technologies more readily than mid-sized or small firms. This disparity could widen the technological divide, with smaller firms using inferior AI solutions that become outdated, rely on low-quality data, or don’t fully integrate with existing hardware. 

Reliance on inaccurate data 

Accountants have always had to deal with poor data quality; however, poor AI may make a challenging situation worse. The effectiveness of accounting AI largely depends on the quality of the training data. Poor-quality data can lead to significant inaccuracies and errors, which are particularly problematic in accounting. If the data is outdated, irrelevant or unreliable, this can undermine the integrity of the outcome. 

Generative AI models that have these data issues become less effective at solving more complex or judgment-based problems. For example, some AI models have had “hallucinations” where information is created without a source. Accountants must be proficient in data wrangling to mitigate these risks and ensure data relevancy, accuracy, and integrity.  

Lack of human touch 

AI can simulate human interactions but cannot replace the human touch required in sensitive situations, such as negotiating with clients or managing employee relations. 

Using AI in accounting also raises significant concerns regarding consumer privacy, transparency, and the traceability of decision-making processes, necessitating a thorough understanding and scrutiny of AI tools by accountants.   As technology utilized in AI grows and changes, employees and management must be flexible and adaptable to overcome challenges in the inevitable learning curve.

AI in accounting brings fears of obsolescence

An additional challenge about AI in accounting comes from potential resistance from accountants, especially if they perceive that AI developments may threaten job security. Fortunately, fears of obsolescence are largely unfounded. Like past technological advances, AI is unlikely to displace the accounting profession. Instead, the shift offers improved efficiency, more time to devote to critical and strategic decision making and enhanced opportunities to provide value-added services in AI implementation, evaluation, and compliance with evolving regulations.  

Considering accounting AI as a colleague

In embracing AI, accountants are not handing their roles over to machines but are instead stepping into the future of accounting. One where their expertise is augmented by technology, not replaced. The future belongs to those who embrace AI, not as a replacement, but as an indispensable ally.  

Accounting AI software 

Now that we’ve discussed what it is, the types of AI in accounting you’re likely to encounter, and some of the challenges and value it offers, let’s look at the most common software options to support AI in accounting. 

Excel is a comfortable place for most accountants because it is both familiar and powerful, but you may be seeing changes in its functionality through AI capabilities. While it isn’t going anywhere anytime soon, the exponential growth in AI capabilities from new startups in software has driven existing programs, including Excel, to add AI components to remain competitive. 

As it pertains to the accounting profession, users benefit from AI software that can do the following: 

  • Automate processes
  • Prescribe decisions 
  • Predict outcomes 
  • Detect anomalies 
  • Document activities 
  • Transcribe calls 
  • Digitize, extract, and understand documents 
  • Populate templates 
  • Understand and apply accounting-based rules and concepts, among other possibilities. 

Based on the variety of needs, it is likely that most firms will or already do employ various software including proprietary tools. To remain relevant and efficient, accountants must familiarize themselves with a variety of AI tools that automate processes and enhance decision-making capabilities. 

Key AI software includes (but is definitely not limited to):  

  • Microsoft Copilot: Integrates with Microsoft suite products to generate data insights through natural language queries.  
  • Alteryx AiDIN: Enhances the Alteryx analytics platform with AI capabilities to automate and optimize data workflows.  
  • ChatGPT by OpenAI: Offers extensive text analysis and summarization capabilities, making it an effective tool for interactive and interpretative tasks.  
  • IBM Watson: Provides robust data analysis and natural language processing solutions to support complex decision making.  
  • UI Path with AI: Combines RPA with AI to improve process efficiencies and discover new operational opportunities.  

The integration of AI in accounting not only challenges accountants to adapt and innovate but also equips them with the tools to perform at higher levels of efficiency and strategic insight. By embracing AI, accountants can transcend traditional roles and drive the profession toward a tech-savant future. The journey will require perseverance, adaptability, and a commitment to continuous learning and ethical standards.    

Take the next step: CPE to support learning about AI in accounting 

If you would like to learn more about AI in accounting and implement it into your work, Becker offers a wide variety of CPE courses to support taking these next steps. Check out these options: 

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