Artificial Intelligence in Accounting: Opportunities, Risks, Future Direction
Artificial Intelligence (AI) is one of the most current and hottest topics in society. It is increasingly becoming a part of our daily lives—both at work and at home. Therefore, it is no surprise that in 2026, it will remain one of the main trends in accounting. Process automation, anomaly detection in data, as well as forecasting and analytics—these are just some of the benefits AI offers.
However, it is human nature to be cautious about unfamiliar things and often wait until there are enough practical examples before deciding whether to implement them in daily life. Therefore, it is not surprising that a study conducted by Norstat revealed that in 2024, only 8% of Latvian companies used AI in accounting. But this statistic cannot be viewed in isolation from the overall business environment and how it adapts to the new era.
Artificial Intelligence in Latvia: Current Situation and Development Direction
Although it may seem that artificial intelligence has been a part of our lives for years—and to some extent, that is true—the real revolution in this field only occurred in 2022, when Open AI's version of the now-famous ChatGPT became publicly available. As a result, changes in our lives have been rapid, and it is not surprising that we are adopting them gradually.
Nevertheless, we are moving towards a future where AI does more and more on our behalf. This is also evidenced by Eurostat data — in 2024, 13.5% of companies in the European Union used artificial intelligence in their operations, a significant increase compared to 2023, when only 8% of companies used AI. Latvia is not far behind the average—AI was used by 4.53% of companies in 2023, rising to 8.83% in 2024. This represents one of the fastest growth rates in the EU. It is important to note that these figures reflect the extent and depth of AI usage in various systems; merely using ChatGPT is not sufficient.
The process has been set in motion, as confirmed by the study "The Digital Portrait of a Leader 2025." Business leaders and employees were asked which tasks they would like to delegate to AI. Administrative tasks dominated—human resource management (19.76%), document management (18.29%), and accounting (13.57%). Interestingly, managers are more interested in using AI in accounting (15.47%) than employees (11.39%). To understand why, let us examine the benefits and potential risks of using artificial intelligence in accounting processes.
AI Advantages in Accounting
Modern accounting is unimaginable without technology, ranging from Excel to specialized accounting software. AI is becoming a reliable assistant, easing routine tasks and providing valuable support in decision-making.
- Automation and Simplification of Routine Tasks
AI can take over time-consuming, repetitive tasks such as data entry, invoice reconciliation, and account checks. This saves time and reduces the likelihood of errors. A study by Zenceipt found that AI reduced document entry time from ~15 minutes to less than 30 seconds, freeing up employees' time for other tasks.
- Data Analysis and Forecasting
Thanks to AI's ability to process vast amounts of data, it becomes easier to identify trends and model potential future scenarios. This enables accountants to create more accurate financial forecasts and allows company leaders to make data-driven decisions.
- Risk Management and Regulatory Compliance
AI monitors transactions in real-time, enabling quicker detection of suspicious situations, invoice discrepancies, or errors. It can also automatically prepare reports, simplifying tax declaration submissions. Particularly useful is the ability to set reminders for deadlines, which is crucial in accounting.
- Strategic Support and Competency Transformation
By processing large volumes of data, preparing reports, and identifying trends, AI provides accountants with a strategic support role. 57% of leaders who implemented AI in finance reported improved employee productivity and positive ROI.
AI Risks in Accounting
While artificial intelligence brings efficiency and precision to accounting, it also raises concerns about data security, management, and the reliability of the information it provides.
- Data Quality and Availability
AI operates based on the data it is given. If the data is not high-quality, structured, and consistent, it can lead to incorrect forecasts or flawed data analysis. Additionally, AI may not account for missing critical data, which could completely alter outcomes, leading to incorrect decisions. ( MDPI, 2024 )
- Privacy and Security
The most commonly mentioned risk associated with AI is that people increasingly input sensitive data, which should not be accessible to everyone. Therefore, when implementing AI in a company, it is crucial to establish data security mechanisms to prevent information leaks. Reliable AI tools have settings that prevent them from using information further, but these must be enabled. If a company fails to ensure data security, it could lead to significant breaches and even legal consequences.
- Insufficient Human Oversight
Although there were initially loud claims that AI would replace humans in many fields, this is not feasible—at least not yet. Like humans, AI can make mistakes, and the consequences can be severe. This is why AI will never fully replace specialists in accounting—regular manual checks are necessary to prevent situations where non-existent data or incorrect interpretations are used. ( Indonesia Auditing Research Journal, 2024 ) Often, AI cannot account for all possible factors that may influence the outcome—the final decision must always rest with a human.
- Changes in Employee Skills and Experience
As with any new technology, achieving the best results with AI requires knowing how to use it. Therefore, accountants need to acquire new skills to fully utilize its capabilities. This can lead to resistance, especially if an employee has been satisfied with their current way of working. If an accountant is not open to the idea of integrating AI into their work, its benefits will be limited.
The Future of Accounting Under AI Influence
It is clear that both employees and managers approach AI with caution, albeit for different reasons. While accountants are concerned about potential job loss and the need for new skills, managers focus on data security and quality to make informed decisions.
However, standing still hinders progress, and although slowly, attitudes towards AI are changing, with more people willing to learn how to use it effectively. This is also indicated by data from the "Digital Portrait of a Leader 2025" study—AI usage has become the most sought-after skill in workplaces, with 24.8% of all respondents already having acquired it. Additionally, 33.9% of respondents expressed a desire to learn or enhance these digital skills in the coming years. This is particularly important for managers—38.2% of respondents in this group expressed such a desire.
Numerous accounting software solutions already offer ways to automate routine tasks—data entry, invoice checks, expense processing, etc. This does not mean that AI will replace accountants. It is here to help reduce administrative burdens, catch errors or discrepancies, and allow humans to focus more on higher-value tasks. The ability to adapt to change is always appreciated and will become even more crucial in the coming years.
Frequently Asked Questions
How can artificial intelligence assist in accounting processes and daily tasks?
AI can automate routine tasks such as data entry, invoice checks, account reconciliation, and document processing, significantly saving time.
Can artificial intelligence replace accountants?
No, AI primarily automates routine tasks like data entry and document processing, but strategic decisions, interpretation, and accountability remain the responsibility of the accountant.
What are the main risks and challenges of implementing AI in accounting, and how can they be managed?
The main risks include data quality issues, privacy and security concerns, algorithm biases, and insufficient employee skills. These can be managed by ensuring high-quality and structured data, regular human oversight, clear security protocols, and employee training in using AI tools.