Insider Threats in AI refer to?

• A. Malicious Or Negligent Insiders Stealing Proprietary Data, Model Theft, Or Sabotaging Models
• B. External Attackers Breaching Networks
• C. Cloud Service Outages
• D. Data Labeling Errors By Crowd Workers

Answer: (A)

Insider threats in AI come from people who already have legitimate access to an organization's AI assets—data, models, code, or the infrastructure that runs them. These insiders can act with malicious intent (stealing proprietary data or model weights, sabotaging models) or through negligence (carelessness, weak controls) that exposes or damages AI systems. This focuses on internal risks, not external attackers, outages, or labeling mistakes, which is why it’s about insiders who might misuse access to steal, steal/intentionally break, or sabotage AI assets. To reduce this risk, organizations implement strong access controls, least-privilege principles, continuous monitoring, and solid model governance.