AI as a Catalyst for Better Project Leadership

Reducing the Friction of Complexity

What initially interested me in AI was seeing how much time talented people spend managing information rather than actually making decisions.

In almost every complex project, you have people gathering updates, checking information, coordinating between teams, identifying problems and trying to understand what changed. The more complex the project becomes, the more time people spend keeping up with the project instead of moving it forward.

That was the problem I became interested in solving. I didn’t look at AI simply as a way to automate tasks. I saw it as a way to reduce that operational friction and give people better information, faster.

For me, the real opportunity is using AI to handle the repetitive and analytical work at scale while allowing people to spend more of their time on judgment, strategy and execution. If you can do that without sacrificing accountability, you fundamentally change how efficiently a project can operate.

Designing AI around People

I think organizations sometimes become too focused on what AI can do and not enough on how people actually work.

You can build an incredibly sophisticated system, but if using it creates more steps, requires people to completely change their workflow or produces results they don’t understand or trust, adoption is going to be difficult.

The technology has to solve a real problem for the person using it. Ideally, it should remove friction rather than introduce another platform that people have to manage.

Trust is equally important. People need to understand what the system is doing, where the information is coming from and when they should question the output. I don’t think successful AI implementation means asking people to trust technology blindly. It means building systems where the technology consistently demonstrates its value while keeping people informed and in control.

The organizations that do this well will be the ones that start with the workflow and the problem, then determine where AI actually belongs.

Balancing Automation and Judgment

The principle I come back to is that automation should increase human capability, not remove human accountability.

AI is extremely good at processing large amounts of information, identifying patterns and performing repetitive analysis at a speed that humans simply can’t match. But there are decisions that require context, experience and an understanding of consequences that goes beyond what the data alone can tell you.

I think the amount of human oversight should increase with the consequence of the decision. If you’re automating a low-risk administrative task, you can give the system significantly more autonomy. If the decision affects safety, finances, compliance or a major strategic outcome, human judgment becomes much more important.

  ​AI’s real value in project management isn’t replacing people. It's helping them make better decisions, faster. By turning complex project data into actionable insight, AI allows leaders to focus less on managing information and more on driving outcomes.   

The best systems aren’t designed around choosing between AI and people. They’re designed around understanding what each does best. Let AI create speed and visibility, and let people provide judgment, context and accountability.

From Reporting to Anticipating

I think project management is going to become significantly more predictive and less reactive.

Today, project managers spend a tremendous amount of time figuring out what happened: what changed, what’s delayed, what’s over budget and what needs attention. Over the next five years, AI will increasingly be able to continuously analyze project information and identify those issues before they become obvious.

The shift will be from reporting problems to anticipating them.

I also think the way people interact with project information will change. Instead of manually searching through reports, schedules, emails and dashboards, professionals will increasingly be able to ask questions directly: What’s putting this deadline at risk? What changed this week? Where are we likely to have a problem next month? The system will be able to bring together information from multiple sources and provide context almost immediately.

That doesn’t eliminate the project manager. I think it actually elevates the role. When less time is spent gathering and organizing information, more time can be spent making decisions, managing relationships and solving the problems that actually require human judgment.

The Skills AI Can’t Replace

I think judgment becomes one of the most valuable skills.

As AI makes information and analysis increasingly accessible, simply having information becomes less of a differentiator. The advantage comes from knowing what information matters, recognizing when something doesn’t make sense and deciding what to do with it.

Domain expertise will also become more important. The better you understand your industry, your customers and the problems you’re solving, the better you’ll be able to evaluate what AI gives you.

I also think people need to become very good at asking questions. Working effectively with AI isn’t just about knowing how to use a particular tool. It’s about knowing how to frame a problem, provide the right context, challenge an answer and recognize what’s missing.

And finally, adaptability is going to matter. The technology will continue changing very quickly. You don’t need to chase every new tool, but you do need to be comfortable learning and adjusting how you work.

AI will make people faster. But being faster isn’t necessarily the same as being better. Judgment, communication, accountability, curiosity and the ability to make good decisions will ultimately determine who gets the most value from it.