The piece cites research on employee disengagement and work intensity to argue that poorly defined goals create wasted effort or burnout. It positions goal-setting within broader workplace pressures: change fatigue, fragmented work, unclear priorities, and burnout. The article does not propose new frameworks but rather emphasizes that only people can judge whether a goal is realistic given current capacity, motivation, and competing demands.
Organizations are rapidly adopting AI tools for performance management and goal-setting while workers and managers struggle with workload and shifting priorities. The timing reflects a genuine tension: AI can automate the mechanics of goal-setting, but it cannot assess sustainability or fit. For in-house counsel and employment lawyers, this signals growing reliance on algorithmic performance management tools—and the corresponding risk that poorly designed systems create liability if they drive unrealistic expectations, discriminatory outcomes, or documented overwork. Practitioners should watch whether clients' AI-driven goal systems include meaningful human review or whether they operate as black-box assignment engines.