HOW AI MAY IMPACT THE ACCOUNTING LANDSCAPE

The advent of AI-driven technologies has resulted in numerous tools such as ChatGPT, Claude, Gemini, Copilot and Perplexity, which threaten the existence of many professionals. Accountants are not immune to this threat as many of their tasks can be automated. As a result, accountants must understand how these tools can be used to make them more productive and efficient. This article provides insights into how this technology is disrupting the accounting profession and what can be done to become better accountants.

Background

A study conducted by researchers from the University of Pennsylvania and OpenAI found accountants are among the professionals most susceptible to being impacted by the capabilities of generative artificial intelligence as at least half of the accounting tasks can be completed much faster with this technology. The study highlights the need to be prepared for potential economic disruption (Elondou, Manning, Mishkin & Rock, 2023). Therefore, accountants must be prepared by assessing their options. On this regard, the World Economic Forum is a strong advocate of upskilling and reskilling (Zahidi, 2020). Upskilling refers to acquiring new skills to do the current job better. Reskilling involves learning new abilities to take on a different job role or function. The good news is that AI technologies can assist accountants to achieve either goal. This article will first examine how AI can be used to enhance accountant’s work. Next, consideration for ethical issues will be addressed. Then, action items will be shared as to what accountants can do to better leverage AI technologies in their work.

How AI will improve accountants’ work

AI will profoundly impact the accounting landscape by automating routine tasks, shifting the accountant’s role toward strategic advisory, and creating higher demands for data analytics and ethical oversight. While AI is unlikely to fully replace accountants, it will redefine the profession by increasing efficiency, enhancing data analysis, and strengthening fraud detection.

• Automated data entry, and real-time reporting can be accomplished as AI and related technologies, such as machine learning (ML) and robotic process automation (RPA), handle the repetitive, high-volume tasks traditionally handled by accountants. For instance, through the use of optical character recognition (OCR), AI can extract key information from invoices and automatically codes and tags transactions. Thus, manual data entry is eliminated, processing time is improved, and human error is minimized. In addition, transactions can be categorized automatically enabling more efficient bookkeeping and account reconciliation. Expense reporting can also be improved as receipt images are scanned and expense reports completed based on past patterns resulting in fewer manual tasks.
• AI allows the detection of anomalies by analyzing huge sets of data. As a result, auditors will no longer need to rely on sample auditing. More importantly, AI can continuously monitor client data and alert accountants of any unusual activity in real-time.
• AI systems can prepare, estimate and review tax returns; identify deductions; and flag compliance risks resulting in fewer errors and enabling accountants to focus on complex tax strategies and value-added services to their clients. AI tools can also conduct research by drawing from numerous tax sources and commentaries to provide concise summaries with proper citations.
• As AI tools allow us to examine huge volumes of data, risk factors can be assessed on real time while performing a variety of scenario analysis to determine the best courses of action enabling better decision making. AI tools can also project revenues, expenses and cash flows along with the respective KPIs based on past financial data and external variables in a more expedited manner. Sensitivity analysis can also be performed to identify most impactful factors allowing management to be better prepared.

Ethical considerations and challenges

As AI technologies are widely adopted, considerations for ethical risks and implementation challenges must be addressed, such as:

• Data security and privacy: Concerns about potential breaches and unauthorized access may be raised as AI handles sensitive client financial data. Therefore, strong cybersecurity and data protection protocols are essential.
• Bias in AI models: AI algorithms are trained on existing data, which can contain inherent biases. As a result, monitoring will be key to ensuring no biased outcomes in financial reporting or risk assessments.
• Transparency and accountability: Accountants and auditors will face problems attempting to understand how decisions are reached when using AI systems given their “black box” nature. Firms must establish clear accountability and ensure that AI-generated processes are explainable and auditable.
• Training and talent gaps: Firms will need to commit to invest in AI training programs to address skills gaps and ensure their employees are prepared for new challenges integrating these technologies.

Conclusion

It has always been said that a commitment to continuous learning is essential for our careers. As AI tools become mainstream, it will be critical not only to stay updated on these new technologies but also to embrace their use in our daily lives to ensure we can do more efficient work and stay relevant as professionals.