The risks of artificial intelligence in
insurance include technological issues, transparency, and usage challenges like inaccuracies and dependency. These could potentially lead to various adverse outcomes, including privacy breaches and biased decisions. Also, the quality of the data used for training significantly influences an AI system's performance. If the training data is inaccurate, biased, or copied, the system won't deliver satisfying results regardless of its technical design.
Our intelligent automation solutions emphasize adopting comprehensive governance and fairness criteria to mitigate bias and ensure privacy and security. We also train AI Agents on your specific data and for your unique workflow, bringing the chances of inaccuracies to a minimum.