Maintenance planners are the backbone of industrial asset management; they ensure equipment uptime, optimise resource allocation and balance reactive and preventive tasks. Traditionally, maintenance planning has been a manual, experience-driven process heavily reliant on historical data and human intuition. Undoubtedly, artificial intelligence (AI) is slowly remodelling positively or negatively how planners work. By leveraging machine learning, predictive analytics, and intelligent scheduling systems, AI is shifting maintenance planning from static, time-based schedules to dynamic, real-time, thus influencing decision-making.