PMBOK chair says project leaders should stop chasing AI tools and start reducing complexity
Jesse Fewell, Project Management Educator, says project leaders should use AI to simplify project work and reduce complexity, while keeping stakeholder relationships and leadership firmly human.
Jesse Fewell
Project Management and Educator
Tool Usability: AI tools vary in ease of use; integrated platforms often offer a more straightforward experience.
Simplicity Priority: Simplify tech stacks to manage complexity efficiently, enhancing productivity and reducing mental overload.
AI Impact: AI enhances project management by handling repetitive tasks, allowing professionals to focus on strategy.
Human Skills: Stakeholder engagement remains a human domain, as personal interaction builds essential trust and communication.
Role Rethink: Project managers must adapt to AI advancements, as organizations integrate AI into workforce dynamics.
Jesse Fewell is a project management educator who helps organizations navigate complex transformation initiatives. He's also the author of Untapped Agility, and he chaired the 8th edition of the PMBOK Guide®.
We caught up with Jesse to discuss how AI is changing project delivery, leadership, and the future role of project managers. Here's what he had to say.
Shaping the future of project management
Hi, I'm Jesse. I help leaders at all levels drive change that sticks. My consulting work ranges from boosting leadership skills at DC Public Schools to driving the digital transformation for Frontier Communications, a $4B firm that recently sold to Verizon.
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I also share my insights with the broader community via books and trade articles, and I chaired the 8th edition of the PMBOK Guide®, the global standard for project management.
I'm the author of Untapped Agility, and I've written a column, "The Agile Project Manager," in PM Network Magazine for over ten years.
How AI serves as a thinking partner
The single most compelling change AI has brought to my work is my ability to generate more momentum and confidence in my own thinking.
In the past, I would invest hours researching ideas and generating outlines for a presentation, a workshop, or a team meeting. Now, I start typing into a chat prompt — I use Copilot and Gemini most often — and the idea in my head gets pressure-tested with a good question or validated by a suggestion I had already discarded.
Like everyone else, I was amazed by the sheer output volume of GenAI when it first came onto the scene. However, in the few years since, I've been settling back into the centuries-old advice that less is more. Whether it's my talking points, my formatting, or my insights, AI helps me be more of me, and that's the one thing that I value the most.
In day-to-day project work, I delegate tedious PM administrivia like meeting minutes, executive summaries, and agenda drafts to AI. Unfortunately, I now spend all that free time I gained experimenting with new PPM tools that overpromise and underdeliver.
For example, I tried a new AI tool to improve Monte Carlo schedule analysis results, but it didn't work. Reliable AI saves me time, but I then waste that time on unreliable AI.
What AI should handle and what should stay explicitly human
The activities that I feel are best handled by AI are tactical tasks based on readily accessible data: generating a roadmap from a master schedule, filling out the risk register based on the project brief, and compressing the business case into one paragraph for a status template.
In contrast, stakeholder engagement remains wholly human. Despite all the innovation today, I find that listening with eye contact is still the most credible way to gather project and product input.
I see many new AI-powered discovery tools on the market promising to save me time by eliminating "wasteful" meetings. But as a project leader, my colleagues need to know that I hear and understand them.
One sponsor recently complained to me she'd had to repeat herself "three times too many." No way would I ask her to dictate the same things all over again for the benefit of my AI meeting tool. Instead, I listen to her concerns, in her words. After the meeting, I use a chat session to type up a project brief for future context engineering; I get much more goodwill from my sponsor, and still end up with the data needed for future tasks. In the end, projects are still people work, because they're driven by people.
Managing complex calendars with AI
One easy workflow that helps me is managing my calendar. Since I manage several client and volunteer projects simultaneously, I have multiple events and calendars that require validation and coordination.
In the past, I would hire a virtual assistant, but today I can leverage a few automations to ensure I don't have conflicts or missed commitments. Granted, it took a lot of trial and error to navigate the many policies and firewalls in place at the various organizations I work with. But using some simple prompts, I accelerated my learning cycle and fine-tuned a calendar solution that works for my unique situation.
The reality of AI tool usability
The variation in AI tool usability has been surprising to me. Recently, I tried using a company's internal proprietary LLM for project analysis; it simply could not perform date arithmetic, e.g., "How many calendar days are left in my schedule?"
The engineer told me my prompt was weak, but as a user, I expected it to infer my intent as a PM. Also, Copilot and Gemini offer very narrow use cases in my productivity suite. It shouldn't be surprising, but every tool has its own user experience.
The variation in AI tool usability has been surprising to me. It shouldn’t be surprising, but every tool has its own user experience.
How a tech stack evolves with AI-driven tools
Integrated platforms are more helpful these days. With many different apps and tools at the office and on my phone, I simplify wherever possible. For example, I recently dropped my beloved Trello boards in favor of the embedded task managers in Microsoft Outlook that my client uses and the Google Workspace my consulting firm uses. I've tried Zapier on and off over the years to integrate best-of-breed PM tools using automated workflows, but going to one place for everything is more compelling in an increasingly complex tech world.
ChatGPT Plus is my first stop for most things. I like how Gemini can access all my Google Docs. I've tried literally dozens of pure-play AI-powered PPM tools, but I keep coming back to these two.
Why simplicity is key in tech stack selection
Research shows humanity faces exponential growth in change and complexity. First, a dozen streaming services replaced my single cable TV subscription, and now, composing an email has three AI plugins.
Science shows the human brain handles only so much complexity at a time, so we must master the skill of zooming in and zooming out, rather than bouncing our attention across a dozen different things at once.
The old argument for tech platforms focused on cost efficiency, both in licensing fees and adoption overhead. However, simplicity will be its own reward as we head into an increasingly fragmented tech world in the 2030s.
How AI helps simplify project management
In my work with DC Public Schools, I observed two important trends.
- Every manager needed PM skills because budget and staffing shortfalls prevented hiring professional project managers. This means professional PMs add more value when they not only perform PM tasks but also teach and distribute PM responsibilities to their colleagues.
- An operations department or agency benefits from simple project management policies. Ninety percent of the team's work involves facility maintenance, family registration, and food distribution. Consequently, the team lacks the bandwidth for a formal PM framework like Scrum. Instead, we issued one-pagers on PM policies (e.g., every project uses the one-page charter worksheet) and PM skills (e.g., how to diplomatically follow up on late tasks).
To create those one-pagers, I first examined the principles behind the PM process. I asked GenAI about the goals and dynamics of a project charter, then compared its response with my own experience and training. Second, I prompted it to generate a draft for a one-page policy. For the charter, this included a worksheet teams could use to explore a project's 5Ws (e.g., Why should parents care about this public school project? Who are the key stakeholders?). Third, I shared the draft worksheet with team members and managers, collecting their feedback. Fourth, I input that feedback and my own analysis into GenAI to refine the worksheet. I find that both AI plugins and GenAI chatbots work best with simple tasks. Often, the first step involves having the tool decompose complex PM concepts into actionable tasks.
When AI tools don't belong in the workplace
Often, tech leaders feel pressure to roll out tools from vendors that simply do not yet offer the safety controls needed to prevent real harm. I work with a lot of risk-averse organizations, such as infrastructure, education, and defense. I encourage those leaders to shamelessly brag about the capability already in place that can often outperform the shiny new AI that everyone wants.
For example, one organization I work with currently bans all agentic platforms, and from where I sit, it's for all the right reasons. Instead, the same organization has embarked on a governance overhaul that will reduce project bureaucracy, allowing it to use existing workflow automations.
Early indications are that project approvals will accelerate from months to days, without adopting the copycat technology purchasing we see in the headlines.
Rethinking project management in an AI-powered workforce
We're already seeing the most sobering prediction coming true: hiring managers increasingly use AI-powered staff instead of hiring new employees. This is especially true in the tech industry.
Three years ago, we were in the age of the millionaire mid-level software engineer. Today, that's only true for AI engineers, and the rest of the tech workforce faces increased competition. Granted, we are still in the AI hype cycle, and a bubble correction will eventually occur. But every PM should immediately rethink their place in an AI-powered workforce.
We’re already seeing the most sobering prediction coming true: hiring managers increasingly use AI-powered staff instead of hiring new employees. Every PM should immediately rethink their place in an AI-powered workforce.
Follow along
You can follow along with Jesse Fewell on LinkedIn and his website. Or check out his book, Untapped Agility.
More expert interviews to come from The Digital Project Manager!
