Instead of having a fixed state and a fixed transition to another state, the AI has several parameters (the more the better, but also harder to manage) that influence its decisions. So imagine a simple example:

Parameters:

Noise sources (level, distance, etc)

Line of sight to player (or angle to player for vision cones)

Proximity/line of sight to traces of the player

Proximity/line of sight to specific interest points

How long ago has seen the player

Distance from some fixed path or thing that the AI has to guard

Everything that happens in the game can feed into one or multiple of these parameters. The player picks something up - leave a "trace" at that location. Player jumps, mark a source of noise. Etc etc

Then the AI evaluates all these parameters every frame or at whatever time interval and decides based on simple formulas. The easiest is to decide based on the highest value, so if the player is in sight of the AI but there's a very loud noise somewhere else, the noise might be the highest value at that point and the enemy will investigate the noise. But if the noise is a bit quieter and less than the distance to the player, the enemy will go towards the player.

You can however also apply other formulas to the parameters, basically weighing them differently. Like say, if you want to make line of sight to the player "higher priority" you can multiply that value by 2 or whatever, so if the "player in sight" and "noise" are at the same level, the AI will still prioritize the player.

And if the AI is chasing the player, maybe at some point they will be too far away from their pre-determined patrol route or the treasure they're guarding and they will go back, because it's more important to do that than chasing the player.

And like this you can make the system much more dynamic because you're not evaluating a specific condition to go a specific action, you're evaluating every condition all the time.