THE INFLUENCE OF GENERATIVE AI ON THE ACCOUNTING PROFESSION

Our previous article, “Impact of AI on the Accounting Profession,” aimed to introduce readers to AI and its various specialized branches. Each branch is designed to emulate specific elements of human intelligence in machines. In our AI universe diagram (see below), we highlighted subsets such as machine learning (ML), deep learning (DL), natural language processing (NLP), and generative AI (GenAI). These particular branches are, in my view, the most relevant to the accounting profession. Since ML acts as a fundamental support for the other branches, the article focused on explaining what ML is and how it enables accountants to work more efficiently and effectively.

After discussing AI and ML's effects on accounting, let's examine how Generative AI (GenAI) is shaping the field.

What is GenAI?

IBM defines GenAI as an “artificial intelligence (AI) that can create original content such as text, images, video, audio, or software code in response to a user’s prompt or request.”

How does it work?

GenAI models work by training on large amounts of data, building on ML. With some GenAI tools, businesses can feed and “ring-fence” their own datasets, documents, and other information into the system, so the technology can cater to their specific needs and internal data. “Unlike traditional AI, which focuses on predictions and classifications, GenAI mimics human-like creativity.” (Techresearchs)

Note: “Ring-fenced” data refers to protecting sensitive information by creating virtual, secure barriers (ring-fences) around it, isolating it from other applications, networks, and unauthorized users.

Key Characteristics

The following are some of the defining features that separate GenAI from other AI tools: (Techresearchs)

• Content Generation: Text, images, audio, video, and code.

• Language Understanding: Natural language processing (NLP).

• Creativity: Ability to simulate human-like design and storytelling.

• Context Awareness: Maintains coherence across large inputs.

• Personalization: Generates user-specific output.

The Use of GenAI for Accounting Professionals

Given what we know about GenAI, the question becomes how it can be used by accounting professionals during the course of their work. Currently, the main areas of accounting that GenAI is making a difference include:

• Audit and Assurance: Accounting firms, such as Deloitte and PwC currently use GenAI to automate the review of massive volumes of documentation, such as revenue agreements and board minutes, highlighting key areas of audit significance.

• Tax research and Standards Reporting Compliance: GenAI can provide instant summaries of complex tax codes and FASB codifications (see illustration below).

  It can assist in identifying potential deductions, credits, and tax-saving opportunities tailored to specific client scenarios

• Bookkeeping and Financial Reporting: AI-powered tools such as Dext, Docyt, Ramp and others can automate data extraction from invoices and receipts, reconciling transactions in real-time.

  Tools such as Datarails can gather data, create automated reports, generate insights, and also draft the initial narratives and footnotes for financial statements.

• Client Advisory Services (CAS): The concept of CAS lets accounting professionals move from routine tasks to higher-value strategic work, such as:

  -- Analyzing financial data to guide decisions, manage risks, and support growth.

  -- Creating forecasts, exploring scenarios, and helping clients set and reach goals.

  -- Partnering in long-term planning, budgeting, cash flow management, and identifying growth opportunities.

Illustration of GenAI at work

You’re a senior partner of an accounting firm and one of your clients is an Oil & Gas exploration and production (E&P) company. Your client has been purchasing smaller E&Ps and your responsibility is to review the acquired firms’ lease agreements, including land easements, drilling contracts, and equipment rentals.

Complying with ASC 842 standard requires identifying every contract that contains a lease, extracting critical data points (lease term, payments, renewal options, implicit interest rates, etc.), and calculating the “Right-of-Use” (ROU) assets and corresponding liabilities for the balance sheet. Manually reviewing these dense, often unstructured, documents is a massive, time-consuming effort that is prone to human error.

Note: Under ASC 842, the Right-of-Use (ROU) asset represents a lessee's contractual right to control and use a tangible asset (such as real estate, vehicles, or equipment) for the duration of a lease term.

Solution: You implement a GenAI-powered lease abstraction and analysis platform. This solution uses Large Language Models (LLMs) and Optical Character Recognition (OCR) to read, interpret, and extract relevant data from thousands of lease documents.

GenAI streamlines this process through five phased implementation steps, described below.  Step 1: Data Ingestion

Thousands of lease documents (PDFs, scanned images, Word files) are uploaded to the platform. The OCR technology converts scanned images into machine-readable text.

Step 2: GenAI Abstraction

LLMs are trained on accounting principles and legal terminology to "read" the contracts and identify all quantitative and qualitative data points required by ASC 842 (e.g., lease start/end dates, monthly payments, clauses about control of the asset, renewal options, etc.).

Step 3: Data Validation and Calculation

The extracted data is automatically validated for consistency and accuracy. The system then performs the necessary present value calculations to determine the ROU assets and lease liability figures.

Step 4: Audit Trail and Reporting

The platform creates a clear, searchable audit trail, linking the extracted data points directly back to the source clauses in the original documents. This ensures auditors can easily verify the calculations.

Step 5: Deployment and Monitoring (Human Oversight)

The final, validated data and calculations are seamlessly uploaded into the company's Enterprise Resource Planning (ERP) or dedicated lease accounting software.

You, along with the firm’s accounting staff review the E&P complex acquisitions to ensure accuracy and compliance.

Benefits of Using GenAI for ASC 842 compliance

The use of GenAI for ASC 842 compliance can yield significant benefits, including:

• Massive Time Savings: The process of data extraction, which might take hours per lease manually, is reduced to seconds per lease, dramatically accelerating compliance efforts.

• Increased Accuracy: Automated data extraction and calculation significantly reduce human errors that could lead to financial misstatements and regulatory penalties.

• Cost Efficiency: One case study outside the oil and gas sector showed an estimated 15-20% savings in overall project hours and a 42% saving over the cost of entirely manual review.

• Audit Readiness: The complete and transparent audit trail simplifies the external auditing process.

• Strategic Focus: Accounting teams are relieved of manual data entry and can focus on higher-value tasks like technical lease analysis, complex judgments, and strategic financial planning.

Final Word

Even though there are many benefits for accounting professionals to use GenAI, surprisingly, the "2025 Generative AI in Professional Services Report" by the Thomson Reuters Institute reports that during 2025 only 21% of tax, audit, and accounting firms were using GenAI at an enterprise level. The good news is that there was a nearly threefold increase from the 8% reported in their 2024 report.

Expected Global Growth

GenAI came into existence only in 2022, so it’s no surprise that the coming years are expected to experience explosive growth in its adoption, with various sources projecting Compound Annual Growth Rates (CAGR) of over 30% to 40% through the end of the decade and beyond.

According to Grand View Research, the global generative AI market is projected to grow at a CAGR of around 40.8% from 2026 to 2033, reaching an estimated market size of over $324 billion by 2033.

Key Challenges

The key challenges facing businesses when relying more and more on AI technology, like GenAI includes:

• Accuracy and Quality Control: GenAI models may generate outputs that appear credible but contain factual inaccuracies referred to as "hallucinations.” These hallucinations can potentially result in misinformation, damage to reputation, and legal exposure. Maintaining high standards of reliability and quality in AI-generated content necessitates rigorous human oversight and effective validation procedures.

• Data Privacy and Security: Handling vast amounts of sensitive client financial data with third-party GenAI tools raises significant security and privacy concerns. Businesses and accounting firms must invest in robust cybersecurity measures and secure storage to prevent data breaches and maintain client confidentiality.

• Ethics and Bias: GenAI models trained on public datasets containing historical biases can reinforce or magnify existing societal prejudices, leading to discriminatory effects in contexts such as recruitment or financial services. It is essential to establish robust ethical guidelines and promote transparency throughout AI decision-making processes to ensure responsible deployment.

• Legal and Regulatory Compliance: The rapidly evolving nature of AI technology makes it difficult to ensure compliance with stringent and evolving data protection laws like EU’s General Data Protection Regulation (GDPR) or California Consumer Protection Act (CCPA) and industry-specific accounting standards, such as U.S. GAAP and International Financial Reporting Standards (IFRS). A major concern is that a majority of surveyed firms still lack clear governance policies for AI usage and, more importantly, the operational implementation of those policies for AI usage.(IBM survey).

• Organizational Resistance to Change: Change can be scary, so it’s not surprising that the adoption of GenAI may encounter internal resistance stemming from concerns about job displacement or hesitation to alter established workflows. The absence of a clear strategic plan and insufficient leadership engagement can further intensify cultural barriers to successful implementation.

• Staff Training and Skill Gaps: A significant challenge is ensuring that accounting teams have the necessary skills to work effectively with AI tools. Many professionals report receiving no formal training on how to use GenAI for industry work, highlighting a gap between anticipated use and current preparation.

• Client Trust: For accounting firms, this challenge relates back to privacy and security issues. It can be difficult to manage client expectations and maintain their trust, as they may be concerned about how their sensitive information is used and the level of human involvement in their work.

In conclusion, the need for human judgment and oversight is more critical than ever. GenAI assists but cannot substitute human expertise. It lacks human intuition, ethical reasoning, and the ability to make complex, contextual judgments, requiring continuous human review and validation of its outputs, especially for critical tasks.

About Carl Burch

Carl Burch holds an MBA, CMA, CIA, FCCA, as well as a QuickBooks ProAdvisor. He is also founder of BURCH Business Services (BBS) located in Boston, MA. For more information on BBS, visit www.burchbusinesservices.com.