Gamified progress signals can make AI recommendations feel more authoritative than they are. Good design separates workflow momentum from evidence that the machine is actually correct.
Reward hacking occurs when an AI optimizes the score instead of the intended outcome. Gamified systems are especially exposed because they already depend on visible proxies, points, and goals.
Task completion and user growth are related but distinct. Motivational AI needs an optimization hierarchy that rewards immediate success without making users permanently dependent on assistance.