AI behavioral risks

When sensitive internal info, IP, or system prompts are unintentionally exposed, revealing operational details and algorithms, it creates legal/security risks and allows competitors to copy proprietary tech.

When AI spreads false information, it erodes user trust, leads to poor decisions, and harms brand credibility–risking damaged reputations, regulatory scrutiny, and lost loyalty.

Overwhelming the AI with excessive inputs can cause service outages (DoS/DoW) by exhausting resources, leading to downtime, higher costs, and poor user experience.

Tricking the AI to bypass its safety controls, enabling the creation of harmful or unethical content risks AI misuse, regulatory issues, and brand damage.

Malicious data injected into RAG systems corrupts AI outputs, causing misinformation or biased responses compromises system integrity, trust, and security.

Accidental exposure of the model’s details enables IP theft, competitor replication, and targeted attacks–posing significant competitive, legal, and security risks.

Exploiting the AI conversation to subtly extract confidential documents, IP, or personal data leading to serious security breaches and compliance risks.

Using deceptive prompts to make the AI trick users into revealing sensitive data or performing unsafe actions, facilitating phishing or social engineering attacks.

Users deliberately prompting the AI for harmful outputs, causing service issues, increasing operational costs, and risking reputational harm from inappropriate content.

AI responses steer users toward competitors, causing direct revenue loss, reduced customer loyalty, and weakened market standing.

AI makes controversial comparisons (e.g., between groups or entities) that offend users, sparks backlash, damages reputations, and erodes trust.

An AI that’s overly assertive or aggressive in its response can alienate users, reduce engagement, and negatively impact brand perception.

The AI generates harmful, abusive, or offensive content, damaging user trust, brand reputation, and potentially leading to legal issues.

AI produces biased or discriminatory content, undermining fairness, violating ethical standards, harming public perception, and risking legal penalties.

The AI uses vulgar language, degrading user experience and damaging brand reputation.

AI provides off-topic or unhelpful answers, frustrating users, eroding trust, and hindering adoption.

AI gives inaccurate information in critical fields (think healthcare, law, or finance), potentially causing real-world harm, legal liabilities, and loss of credibility.

AI invents facts or provides nonsensical information–misleading users, spreading misinformation, damaging credibility, and potentially causing real harm.

AI fabricates or provides inaccurate citations/references–misleading users, damaging credibility, and potentially creating legal liability.

AI incorrectly uses external data in RAG systems, leading to factual errors and misleading outputs that undermine trust and spread misinformation.

AI is overly cautious, wrongly flagging safe user input and triggering protections unnecessarily which harms user experience and engagement.