What the study found
The study finds that artificial intelligence (AI) can strengthen enterprise risk management (ERM), which is the way organizations identify, assess, and respond to risks. It also finds that AI brings new concerns, including algorithmic bias, data privacy, and model transparency issues.
Why the authors say this matters
The authors conclude that AI significantly advances ERM. They say organizations need robust, proactive governance frameworks to manage the new risks and support responsible use of AI.
What the researchers tested
The paper reviews relevant theories, analyzes practical applications, and discusses related risks and challenges. It also uses case studies from financial services, supply chain management, and cybersecurity.
What worked and what didn't
According to the abstract, AI enhances risk detection, improves decision-making, and increases operational efficiency. The abstract also says widespread AI adoption introduces algorithmic bias, data privacy concerns, and model transparency issues.
What to keep in mind
The available summary does not describe detailed limitations. The abstract does not provide specific measurements, comparison groups, or the full scope of the case studies.
Key points
- AI improved risk detection in enterprise risk management.
- AI improved decision-making and operational efficiency.
- The paper discusses case studies in financial services, supply chain management, and cybersecurity.
- The abstract says AI adoption can create algorithmic bias, privacy, and transparency concerns.
- The authors call for proactive governance frameworks for responsible AI deployment.
Disclosure
- Research title:
- AI is linked to better enterprise risk management
- Authors:
- Qingyang Long
- Institutions:
- Hong Kong Polytechnic University
- Publication date:
- 2026-02-24
- OpenAlex record:
- View
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