EURO 2025 Leeds
Abstract Submission

1916. Revolutionizing Accounting Systems with AI-Driven Automation and Analytics Tools in Developing Countries

Invited abstract in session WA-23: Data Analytics for Business Resilience and Sustainability - Measuring SME Performance , stream OR for Societal Development.

Wednesday, 8:30-10:00
Room: Esther Simpson 3.01

Authors (first author is the speaker)

1. Amos C. Mpofu
Accounting Sciences, National University of Science and Technology
2. Helper Zhou
School of Accounting, Economics and Finance, University of KwaZulu Natal
3. Gordon Dash
Finance and Decision Sciences, University of Rhode Island
4. Nina Kajiji
Computer Science and Statistics, University of Rhode Island, and The NKD Group, Inc.

Abstract

This study explores the integration of AI tools into Accounting Information Systems (AIS) for both small and medium enterprises (SMEs) and corporate entities across the Southern African region. Over a three-month period, ten companies were analyzed to assess the impact of generative AI-driven automation in financial transaction processing and analytics. The study employed Llama and Gemini models, with a comparative focus on Llama, deployed in Python. The system, termed "Smart Quantilytix" or "Smart Qx Ledger," was connected to a WhatsApp interface to facilitate real-time interaction, transaction tracking and data visualization using both audio and text prompts. Results revealed that all transactions conducted in English were accurately captured, while those in indigenous languages—Shona, Zulu, Sotho, and Ndebele—had an error rate of up to 20%. Despite language-based discrepancies, companies utilizing Smart Qx Ledger, the AI-powered analytical tool, exhibited significantly faster transaction processing and analysis compared to the control group. These findings highlight the transformative potential of generative AI in enhancing data processing efficiency and analytical capabilities, contributing to resilient business performance in both SME and corporate environments.

Keywords

Status: accepted


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