Comparative Analysis of Artificial Intelligence Applications in Chemical Industry Accounting: Opportunities, Challenges, and Implementation

The chemical and petrochemical industries represent one of the most economically sensitive sectors in terms of the need for advanced financial information systems, owing to inherent complexities in production processes, a high diversity of products, stringent environmental requirements, joint production, and intense volatility in raw material prices. This study adopts a descriptive-analytical approach based on a Systematic Literature Review to examine the applications of artificial intelligence (AI) in chemical industry accounting across multiple dimensions. The research population comprises 109 credible domestic and international scientific sources spanning the period 2010–2024. Findings indicate that AI technologies—including machine learning, deep neural networks, natural language processing, expert systems, and robotic process automation—can play a pivotal role in cost accounting, dynamic budgeting, continuous auditing, cash flow forecasting, financial risk management, regulatory compliance, and sustainability reporting. Nevertheless, challenges such as a shortage of qualified personnel, organizational resistance, high implementation costs, weak data infrastructure, and information-security concerns constitute substantial barriers to this transformation. The article ultimately proposes the "AI-CCA" operational model as a localized framework for the step-by-step implementation of artificial intelligence in the accounting systems of Iranian chemical companies.