August 21, 2026 • 5 Min Read

Teams now manage more initiatives, face tighter timelines, and feel greater pressure to deliver results. That’s why more of my work today involves helping teams understand where AI can ease workloads and improve project outcomes.

AI can fundamentally change how projects get done by reducing administrative work and using predictive insights to surface risks earlier. Organizations that use AI effectively have an advantage over those that don’t, but the key is knowing where it can make the biggest difference. Here’s my take on what it means for project management and where organizations should start.

AI Is Becoming Standard in Project Management

At RGP, we’re already seeing project teams put AI to work across planning, reporting, resource management, and governance. As we’ve written about before, AI is beginning to reshape the role of the PMO itself. 

• Automate routine work: AI can streamline status reporting and project documentation. 
• Spot issues earlier: Predictive insights spot issues before they show up. 
• Improve planning: AI can use project data to inform schedules, resources, and priorities.
• Give leaders greater visibility: Real-time insights give leaders a clearer view of project and portfolio performance. 

AI Can Make Project Management More Strategic

AI isn’t just helping people be more productive and get work done faster. It’s also transforming how the work gets done, impacting strategy, decision-making, and planning. 

• Plan and communicate faster: AI can generate project plans, summarize discussions, draft communications, and maintain documentation. 
• Allocate resources more effectively: AI can analyze skills, workloads, and priorities to recommend staffing across initiatives. 
• Manage projects more proactively: AI agents can monitor performance, flag issues, and recommend next steps. 
• Focus on higher-value work: AI can free project managers to spend less time on admin and more time solving problems. 

Why Organizations Shouldn’t Wait to Put AI to Work 

Over the course of my career, I’ve seen organizations take on increasingly complex projects with tighter timelines, often with the same resources. AI can help them keep pace. 

• Limited capacity: Manual work takes time away from other more important activities. 
• Problems surface later: Predictive insights catch delays and budget concerns sooner. 
• Scaling becomes harder: As organizations take on more transformation projects, existing teams can quickly become stretched thin. 
• The performance gap can grow: Teams that use AI effectively can work faster and have a clearer picture of how projects are going. 

Getting Started with AI Is Easier Than You Think

One thing I tell clients is that you don’t need to transform your entire PMO to begin putting AI to work. Successful AI adoption starts with a real problem. So find a problem, test what works, and build from there. 

• Find the right opportunity: Look for repetitive, time-consuming work, such as reporting, documentation, and status updates. 
• Start small: Pilot AI within a single project or process before expanding more broadly. 
• Put the right guardrails in place: Establish clear governance, data standards, and human oversight from the beginning. 
• Learn and expand: Use what works to identify the next AI opportunity across project management. 

If you’re thinking about where AI could make a difference in your project management approach, we’d love to work with you. Get in touch to start the conversation.