Bias as an Attack Vector: How AI Training Data and Model Behavior Create Hidden Risk

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Artificial intelligence now sits at the core of many IT and cybersecurity operations, influencing how organizations detect threats, prioritize risk, and make decisions. As AI output increasingly shapes these workflows, bias becomes an operational risk rather than an abstract concern. Measured model behavior shows consistent directional tendencies, including preference patterns, valuation uplift, and bias that can persist or regress across updates. This whitepaper examines how bias enters AI systems, how it affects security operations, and why managing AI behavior is necessary to maintain reliable and defensible cybersecurity programs.