Implications of AI in Information Management - Shakeel, Zarafshan (2025)
This thesis is an inquiry into the ethical dilemmas of artificial intelligence (AI) in information management, where AI adoption in systems is occurring amid increasingly complex ethical, technological, and regulatory issues. A mixed-methods research design was used, combining 20 professionals' qualitative interviews with a large-scale survey to provide a clearer view of AI acceptance than the interviews alone. A research paper indicated that it is necessary to understand the extent to which ethical principles such as transparency, fairness, accountability, explainability, and data privacy can be upheld in an automated, algorithmic decision-making world that is gradually taking over. The thematic analysis of interview data produced six main themes: (1) AI-assisted efficiency and decision making support; this theme was represented by processing workflow and data-driven insights; (2) the need of human supervision where it was pointed out that AI cannot take the place of the professional's judgment; (3) XAI as the fundamental criterion for establishing trust and accountability; (4) data privacy and governance risks, especially concerning the GDPR compliance, consent, data leakage, and unauthorized access; (5) trustworthiness and risk reduction with the following dangers considered: biased datasets, hallucinations, opaque model behavior and system vulnerabilities; and (6) organizational preparedness including skill deficits, training requirements and structural readiness for the responsible AI deployment. The quantitative results confirmed these themes and showed that the areas of concern overlapped with issues of transparency, data security, model fairness, and the absence of transparent internal AI governance, all of which were deemed the most serious.