"Leadership is the art of getting someone else to do something you want done because they want to do it." said Dwight D. Eisenhower. In my experience teaching AI in urban planning, I emphasize focus and clear goals to avoid scope creep. One mistake students make is trying to over-deliver, losing sight of core objectives. Innovative solutions like Agile methodology or breaking projects into phases are critical. I always remind students, "Clear boundaries inspire creativity." How do you ensure alignment in complex AI projects?

A pledge for a new perspective: is scope creep really that much of an issue or can there be some goodness in it? After all, it is an indicator that the project is hitting the needs of its target audience. When additional features or aspects are being requested, these may even significantly enhance the value add that is being delivered. So, rather than very strictly managing to the original scope, the best AI projects are managed with an agile and somewhat flexible mindset. Particularly AI projects are often exploring very new grounds. Therefore, the seizing of new arising opportunities, should be a constant practice. New requirements need careful evaluation and intake or rejection should be balanced. Ideally it’s not a one-way street.

One time at work, we faced significant scope creep in an AI project. To address this, we implemented a rigorous change management process, requiring all new features to be evaluated against our core objectives and resource constraints. In my experience, maintaining clear communication with stakeholders is crucial. We held regular check-ins to review progress, discuss potential changes, and realign on priorities, which helped prevent unexpected additions to the project scope. A strategy I recommend is adopting an agile methodology. By breaking the project into smaller sprints and continuously reassessing priorities, we were able to accommodate necessary changes without derailing the overall timeline or compromising core deliverables.

Is your AI project growing beyond its original scope? Staying on track with deadlines and scope is the real challenge. It’s all about clear communication, setting realistic milestones, and constant reassessment. How do you keep your AI projects from spiraling out of control? Let’s share strategies that work!