Real Consequences
Enterprises cannot deploy generative AI agents in production today because they cannot trust LLMs to behave reliably in the real world. LLMs are prone to errors, easy to attack, and slow to recover. Even if they were originally aligned to be honest and helpful, they can be easily compromised. Broken free from guardrails, they can diverge from developer goals, degrade user experience, and damage enterprise reputation and revenue.
Winter is Coming
The transformative potential of generative AI will remain unrealized if enterprises cannot trust foundation models:
If investment banks cannot trust search engines to extract facts from earnings reports without memorizing personal identifiable information
Incidents of Harm
Visit the AI Incident Database to see real world examples of harms caused by the deployment of flawed AI systems.