IIRC if you take out the human element of poker (bluffing), it becomes a statistics / numbers game - at least, I see 'win chance' numbers on the off occasion I see poker on TV. Knowing your chances and being able to guess at other players' gives you an advantage.
But you don't need a computer for that... knowing the odds for a hand is a pretty basic skill. And on the other hand if you did place bets based on your hand odds you'd be leaking a lot of information to your opponent.
Not really related to AI but it gives quite an advantage if you can connect multiple "players" to same table. It is not worth to do it without some kind of automation and service providers try to prevent it from happening.
> In AI, two-player zero-sum games (such as heads-up hold'em) are usually won by approximating a Nash equilibrium strategy; however, this approach does not work for games with three or more players. Pluribus instead uses an approach which lacks strong theoretical guarantees, but nevertheless appears to work well empirically at defeating human players. Across the competitions, Pluribus won an average of over 30 milli big blinds per game. Pluribus' self-learned play style eschews "limping" (calling the big blind), and engages in "donk betting" (ending a round with a call and starting the next round by betting) more often than human experts do.