Learning typical user behaviour and detecting anything that's anomalous to that
Understanding sensitive data access patterns and flagging any activities that are seemingly unusual
Setting up automated alerts for suspected security incidents and allowing security teams to take proactive action instead of resorting to post-mortem analysis
Detecting any insider threat activities by ensuring that anything that's beyond the normal work pattern of behaviour gets immediately noticed
Blocking the transfer of any sensitive information within and outside the company network
Distribute workloads according to a team's or individual's working proficiency. Teams can understand the working patterns and solicit suggestions from AI about redistributing work strategically.
Provide personalised feedback based on employee's productivity and engagement patterns. This can be as simple as providing a nudge to improve engagement on certain channels or recommending the whole series of courses for professional growth.
Gauge employee sentiments through their communication patterns across internal or social channels being monitored. Large language models (LLMs) that power generative AI solutions can certainly be a boon for companies wanting to go granular into comprehending what employees like and dislike. This can help alert managers to potential hiccups in productivity and take proactive actions to personally interact with employees or perhaps even tweak the working conditions for the greater good.
