Strengthening Internal Control Practices in AI-Driven Multinational Companies: A Strategic Approach to Sustainable Business Operations

Abstract

The rapid integration of Artificial Intelligence (AI) into multinational corporations has transformed decision-making, optimized operational processes, and enhanced productivity. However, AI also introduces emerging risks such as algorithmic bias, data privacy concerns, and operational vulnerabilities that may undermine corporate objectives if not properly managed.

This study aims to address the challenges namely the risks of algorithmic bias, data privacy issues, and operational vulnerabilities, by proposing the RAISE Strategic Control Framework, a structured approach that aligns internal control practices with the dynamic realities of AI-driven business environments. Specifically, it evaluates the framework’s effectiveness, relevance, and applicability in multinational contexts.

This study employed an Explanatory Sequential Mixed Methods Design to evaluate the effectiveness, relevance, and applicability of the RAISE Strategic Control Framework in AI-driven multinational corporations. The respondents included 368 employees from Internal Audit, Compliance and Risk Management, Digital Infrastructure and IT, Finance and Accounting, and Operations and Business Process departments of multinational IT corporations operating in the Philippines. Senior leaders and decision-makers were also interviewed to provide strategic perspectives. Purposive sampling was used to ensure inclusion of participants with direct expertise in internal controls and AI integration. Data were collected through a validated survey questionnaire. Quantitative data were analyzed using descriptive and inferential statistics, while qualitative data underwent thematic analysis to explore challenges, best practices, and implications for corporate governance.

Findings reveal that implementing the RAISE framework strengthens organizational governance, enhances risk identification and mitigation, and fosters a culture of ethical AI use. Results also highlight its potential to serve as a strategic tool for sustainable business operations by bridging the gap between AI innovation and robust internal control systems.

The study concludes that integrating RAISE into corporate governance policies can enhance regulatory compliance, support organizational adaptation to AI transformation, and promote ethical AI practices. Future research directions include longitudinal assessments of RAISE implementation, cross-cultural evaluations of AI governance perceptions, and refinement of human–AI collaboration models. The implications extend to policy formulation through harmonized AI governance standards and program development, including corporate training, certification initiatives, and cross-sector pilot projects to expand adaptability.