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All Journal Aptisi Transactions on Management International Transactions on Education Technology (ITEE)
Williams, Jack
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Social Sciences

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Journal : Aptisi Transactions on Management

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Leveraging AI-Powered Automation for Enhanced Operational Efficiency in Small and Medium Enterprises (SMEs) Andayani, Dwi; Indiyati, Dian; Mayang Sari, Meri; Williams, Jack; Yao, Goh
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2363

Abstract

This study explores the potential of AI-powered automation in enhancing opera- tional efficiency within Small and Medium Enterprises (SMEs). The primary objective is to identify how automation tools driven by artificial intelligence (AI) can streamline business processes, reduce operational costs, and improve productivity. The methodology includes a quantitative analysis of SMEs that have implemented AI-based solutions, supported by qualitative interviews with key stakeholders. The Results indicate significant improvements in operational workflows, particularly in areas such as supply chain management, customer service, and financial operations. The findings demonstrate that SMEs adopting AI technologies experience reduced human error, faster decision-making pro- cesses, and improved customer satisfaction. However, challenges such as initial investment costs and technical expertise remain. The study concludes that with proper implementation and strategic planning, AI-powered automation can be a key driver of success for SMEs in competitive markets.
Evaluating Risk Management Strategies in Fintech and Blockchain An Empirical Approach Hartono, Tri; Putri Oganda, Fitra; Williams, Jack
APTISI Transactions on Management (ATM) Vol 9 No 2 (2025): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i2.2473

Abstract

The rapid growth of fintech and blockchain technologies has revolution- ized the financial sector, introducing innovative solutions but also posing unique risks. Managing these risks effectively is crucial for ensuring the stability and sustainability of these technologies. This study aims to evaluate the effective- ness of risk management strategies in fintech and blockchain sectors, focusing on identifying the most adopted strategies and assessing their impact on mitigating various risks. A quantitative research design was employed, using surveys to collect data from industry experts in fintech and blockchain companies. The data were analyzed using Structural Equation Modeling (SEM) with SmartPLS software to assess the relationships between risk management strategies and or- ganizational outcomes. The findings revealed that cybersecurity protocols, reg- ulatory compliance programs, and smart contract audits are the most commonly adopted risk management strategies. The study found that blockchain companies prioritize smart contract audits, while fintech companies focus more on cyber- security and regulatory compliance. Effective risk management strategies are crucial for the growth and stability of fintech and blockchain sectors. The study recommends that companies integrate advanced technologies and prioritize reg- ulatory compliance to mitigate risks and enhance trust.
Co-Authors Anggy Giri Prawiyogi Dian Indiyati Dwi Andayani Hartono, Tri Ismail, Farid Bin Kovac, Ivan Mayang Sari, Meri Putri Oganda, Fitra Rodriguez, Miguel Sutarman, Asep Wilson, Daniel Yao, Goh