The agent is what can make the AI reliable
ChatGPT, Claude, Grok and Gemini are not deterministic, and this creates risks that must be managed
Hallucinations
Plausible but fictitious answers. The AI responds to a query with the most likely output given the data it has. This is done through probabilistic data-filling in a process that is still not well understood
Black box
Large language models grant no access to reliable records explaining why they answered as they did, or which sources they based their answer on. As a result, these systems cannot be audited
Inconsistency and unpredictability
The same question can produce different answers on different days, and it can produce answers unsuitable for a corporate setting
The AI reasons. The agent evaluates, logs and controls
We recommend four layers to control which data the AI processes and which replies reach the user:
Evaluation
Each answer is validated against set reliability thresholds before it reaches the user
Logging and audit
Queries, sources and answers are logged in line with your internal policy and current law
Guardrails
Explicit rules on what is allowed, what is forbidden and when the AI requires human confirmation
Operational control
Process guides are set with predefined workflows and preset data sources