What the study found: Artificial intelligence (AI) can enhance enterprise risk management by improving risk detection, decision-making, and operational efficiency. The study also says AI introduces new risks, including algorithmic bias, data privacy concerns, and model transparency issues.
Why the authors say this matters: The authors conclude that AI significantly advances enterprise risk management, but they say organizations must use robust, proactive governance frameworks to address the new challenges and support responsible deployment of AI.
What the researchers tested: The paper reviews relevant theories, analyzes practical applications, and discusses risks and challenges related to AI in enterprise risk management. It also uses case studies from financial services, supply chain management, and cybersecurity.
What worked and what didn't: The abstract reports that AI improved risk detection, decision-making, and operational efficiency in the case studies. It also reports that wider AI adoption brings challenges tied to algorithmic bias, data privacy, and transparency.
What to keep in mind: The available summary does not describe detailed limitations beyond the noted risks and governance challenges. The abstract does not provide quantitative results or compare specific AI systems.
Key points
- AI was reported to improve risk detection in enterprise risk management.
- The study says AI improved decision-making and operational efficiency.
- Case studies were drawn from financial services, supply chain management, and cybersecurity.
- The abstract identifies new risks from AI, including bias, privacy, and transparency concerns.
- The authors say organizations need proactive governance frameworks for responsible AI use.
Disclosure
- Research title:
- AI changes enterprise risk management while adding new governance risks
- Authors:
- Qingyang Long
- Institutions:
- Hong Kong Polytechnic University
- Publication date:
- 2026-02-24
- OpenAlex record:
- View
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