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The Role of AI in Modern Accounting Automation

Tanvir Ahmed1*

+ Author Affiliations

Paradise 1 (1) 1-9 https://doi.org/10.25163/paradise.1110341

Submitted: 03 December 2024 Revised: 10 February 2025  Published: 12 February 2025 


Abstract

The rise of Artificial Intelligence (AI) is changing the accounting profession in remarkable ways. By automating routine tasks, AI not only improves the accuracy of data but also enhances the decision-making process. Many industries have adopted AI technologies to streamline their financial processes, leading to a significant reduction in errors and inefficiencies. As we have transitioned from traditional manual accounting methods to automated systems, accountants can now devote more time to strategic roles, providing valuable advice to clients. Tools like machine learning, natural language processing, and robotic process automation are playing vital roles in this transformation, making accounting work smoother and more effective. However, the journey towards AI integration is not without its challenges. Issues such as ethical considerations, data security threats, and gaps in required skills have emerged as obstacles to the full adoption of AI. To tackle these, there is a pressing need for comprehensive training and solid governance frameworks. This ensures that technology is used responsibly and maintains the trust of clients. Real-world examples from various sectors, including finance, retail, public service, real estate, and manufacturing, demonstrate the tangible benefits and strategic advantages that come with embracing AI. As this innovation unfolds, the accounting profession is set for ongoing evolution, driven by new technologies and the increasingly complex financial landscape. Throughout this transformation, it remains crucial to priorities transparency, ethical considerations, and human judgment to maintain the integrity and credibility of accounting practices in the era of AI.

Keywords: Artificial Intelligence, Accounting Automation, Machine Learning, Ethical Considerations, Predictive Analytics.

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