Muhammad Fauzi Rais Lutfi
Universitas Sultan Ageng Tirtayasa, Banten, Indonesia

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Legal Perspectives on the Use of AI in Business Decision-Making in the Digital Age Raine Graciea Firdaus; Muhamad Miftahulloh; Muhamad Ridho; Hana Nailah Abiliah; Frilla Erita Foessy; Najma El Ulya Rahmania; Muhammad Fauzi Rais Lutfi
Synergy: Journal of Collaborative Sciences Vol. 2 No. 1 (2026): Synergy
Publisher : Yayasan Penelitian dan Pengabdian Masyarakat Sisi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69836/synergy.v2i1.223

Abstract

The integration of artificial intelligence (AI) into business decision-making processes has significantly transformed corporate operations while simultaneously raising complex legal issues, particularly concerning liability for decisions generated autonomously by algorithmic systems. This study analyzes the legal position of artificial intelligence within Indonesia’s regulatory framework and evaluates the extent to which the Electronic Information and Transactions Law (ITE Law) can serve as a legal basis for accountability when AI-generated decisions result in losses. Employing a normative juridical method with statutory and conceptual approaches, this research examines the classification of AI as an electronic agent and its implications for determining business liability. The analysis demonstrates that, under Indonesian positive law, AI has not yet been recognized as an independent legal subject, resulting in legal responsibility remaining with developers, operators, or business entities that deploy AI systems. Nevertheless, the absence of specific and comprehensive AI regulations creates legal uncertainty, particularly in light of AI’s autonomous operation and opaque decision-making mechanisms. This study concludes that although the ITE Law provides an initial normative foundation for regulating AI-related accountability, it remains insufficient to address the legal complexity, ethical concerns, and risks inherent in AI-driven business decision-making.