Automation and AI in Accounting: Comparative Impact of Chat-bots and Deep Learning Machine of Accounting Officer's Work Effectiveness in Business Organizations in Anambra State

This study investigated the comparative impact of chat-bots and deep learning of accounting officers' work effectiveness in Anambra State. A correlation research design was adopted, and a structured questionnaire was administered using Artificial Intelligence Questionnaire (AIQ) and Work Effectiveness Questionnaire (WEQ) to 221 accountants in business organizations. The study found a moderate positive relationship between automated chat-bots and work effectiveness (r = .465, N = 221) and a low positive relationship between deep learning machines and work effectiveness (r = .305, N = 221). The study also revealed significant relationships between both automated chat-bots and deep learning machines with work effectiveness. The findings have implications for business organizations, highlighting the need to adopt AI technologies to enhance financial management capabilities, productivity, and efficiency. The study recommends that business organizations adopt automated chat-bots and deep learning machines to improve accounting practices and provide training and development opportunities for accounting officers. This study contributes to knowledge theoretically, practically, and methodologically, providing insights into the relationship between AI technologies and work effectiveness in accounting.