Degree

Master of Business Administration Executive

Faculty / School

School of Business Studies (SBS)

Year of Award

2026

Advisor/Supervisor

Dr. Rameez Khalid, Associate Professor, Department of Management

Project Type

MBA Executive Research Project

Access Type

Restricted Access

Keywords

Artificial Intelligence Governance, Responsible AI, AI Risk Management, Human-in-the-Loop, AI Ethics, Fintech Governance, Sustainability Governance

Executive Summary

Artificial Intelligence (AI) technologies are transforming organizational operations, decisionmaking systems, financial analysis, customer engagement, and software development processes across industries. While AI offers significant operational efficiencies and innovation opportunities, it also introduces substantial risks associated with data privacy, cybersecurity, governance ambiguity, explainability, ethical accountability, intellectual property exposure, and environmental sustainability.

This project aims to develop a Responsible AI Governance Framework (RAIGF) tailored to Enduring Planet, a climate-focused fintech organization operating in the financial services and sustainability domain. The framework addresses strategic, operational, ethical, and governance-related challenges in AI adoption by establishing policies, procedures, controls, and oversight mechanisms for responsible AI implementation.

The proposed framework builds upon multiple internationally recognized governance approaches, including the Hourglass Model (Mäntymäki et al., 2022), the NIST AI Risk Management Framework, Wirtz et al.’s Risk Tiering approach, the ARGO adaptive governance model, and AuroraAI’s principles of human-centricity and legitimacy.

A qualitative exploratory research design was adopted for this project. Data collection was conducted using semi-structured interviews with organizational stakeholders, technical leaders, finance professionals, governance practitioners, and external AI experts. Thematic analysis and line-by-line coding were employed to identify recurring governance patterns, operational risks, organizational tensions, and emerging governance needs.

Key findings from the study indicate that organizations face increasing tensions between innovation speed and governance control, trust and automation, performance and sustainability, and operational efficiency and ethical accountability. Human-in-the-loop oversight, multi-layer quality assurance, vendor trust assessment, AI transparency, and data governance emerged as critical operational governance requirements.

The framework is designed to be practical, scalable, adaptive, and operationally implementable within Enduring Planet’s organizational context.

Pages

xi, 140

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