Welcome to our Master Talk series, where we cut through buzzwords and hype to have conversations with experts about what’s truly reshaping project management. This month, we talk with Billal Ben-Redouane, senior project manager and AI strategist who’s deployed AI driven solutions for startups to Fortune 500 companies. Billal is here to challenge the hype, unpack what AI really means for project managers today, and share a no-nonsense, forward-looking perspective.
Q: Billal, now that everyone talks about “project management powered by AI”, what does that phrase actually mean to you?
Billal: The truth is, the phrase “AI-powered project management” gets thrown around so much that it risks becoming meaningless. I’m quite upset by how much hype surrounds AI, with many people expecting it to be some miracle fix that will instantly solve all project challenges. That’s simply not true.
In my experience, AI is not a magic pill. It’s not just another tool to automate routine tasks or dashboards. AI is, above all, a mindset. It’s about how you approach problem-solving with an eye toward combining different disciplines. You need design thinking to frame problems properly, deep skills from the humanities, like understanding human behavior, psychology, and social dynamics and an ability to creatively connect ideas to data in ways that make sense.
So, when we say “AI-powered project management,” we should mean that AI technologies are embedded into the workflow in a way that augments human decision-making. For example, AI can forecast project delays by analyzing historical data, or automatically generate natural language summaries of progress. But the real value comes from how project managers integrate those insights into their expertise.
AI is a partner in the process, not a replacement or a standalone solution. Unfortunately, many still view it like a gadget or shortcut, which is dangerous. To succeed today, project managers need this AI mindset combined with strong specialization and human skills. The era when generalist PMs managed everything well is ending. The complexity of today’s challenges demands focused expertise – in sustainability, enterprise operations, financials, or digital transformation – paired with a foundation rooted in psychology and sociology.
Q: Why do you think this shift toward specialization and mindset is especially urgent right now?
Billal: Right now, we’re facing enormous economic and organizational pressures. Companies are cutting costs, restructuring, and laying off people. It’s a tough environment, and AI is both a factor in these changes and a tool companies lean on to survive. According to the 2024 PMI Pulse of the Profession report, organizations that incorporate AI into their project management workflows make decisions 30% faster and experience 25% fewer budget overruns. Those numbers tell us AI can bring real efficiency and risk reduction.
But here’s the catch, those benefits aren’t automatic. Many organizations have rushed into AI adoption without fixing foundational problems. If your processes are disorganized, data is messy, and your teams don’t understand what AI is doing, you won’t get those gains. You’ll just speed up chaos.
That’s why project managers must become more conscious about how they integrate AI. This means deepening their domain knowledge, specializing in complex areas, and not just leaning on generic PM skills. For example, a PM working on enterprise resource planning (ERP) projects must understand finance, compliance, and IT integration deeply because AI tools rely on good domain data and informed interpretation.
Simultaneously, PMs must strengthen their human skills, things like emotional intelligence, psychology, and communication. AI can analyze data, but it can’t replace the subtlety of human judgment needed to motivate teams, manage conflicts, and navigate political landscapes.
In this context, the “generalist PM” is no longer enough. Companies need PMs who combine a strong grounding in people skills with highly specialized knowledge. Without that combination, you’ll be outpaced or irrelevant.
Q: Can you share a real world example where AI made a concrete difference in a project?
Billal: Absolutely. I worked with a healthcare startup that was struggling with sprint delays impacting their time to market. We implemented an AI module that analyzed two years of detailed sprint data. The AI found a pattern: when two particular features were scheduled in the same sprint, delivery consistently slipped by three days on average.
This insight was eye opening. The data alone wouldn’t have been obvious without AI’s pattern detection. But importantly, it was how the team used this information that drove results. We restructured the backlog to separate those features into different sprints, which reduced sprint delays by about 40%.
We also implemented automated budget burn alerts. The system flagged any cost overruns as soon as they hit 80% of forecast, giving the finance team timely visibility to intervene early. This real time insight helped avoid surprises during financial reviews.
But I want to emphasize, AI didn’t solve the problems alone. It provided valuable, actionable insights, but the project team’s deep domain knowledge, critical thinking, and collaboration were essential to turn those insights into better planning and execution. AI is an enabler, not a stand in for human expertise.
Q: For project managers just beginning to experiment with AI, what practical advice do you have?
Billal: Start small, and be laser focused. AI is tempting because it promises big changes, but jumping in without a clear goal is a recipe for wasted effort.
Pick one well-defined challenge, risk management is often a good example. Gather your historical risk data from the past couple of years things like descriptions, likelihoods, impacts, and actual outcomes. Use a no code AI tool like Microsoft Power BI’s AI insights or your existing AI enabled PM platform.
Run an AI model on this data for example, a risk prediction model and then critically compare the AI’s outputs to your own judgment. You want to see where the AI agrees with you, where it surprises you, and where it might be wrong.
Don’t blindly trust the AI. It’s a partner for challenging your assumptions. Over a few sprints, track how well it predicts risks and refine the model based on false positives or missed risks.
Most importantly, involve your team early. AI adoption fails if the people on the ground don’t understand it or trust it. Get their feedback, train them, and iterate.
Q: What are the most common pitfalls PMs fall into when trying to adopt AI?
Billal: The number one mistake is expecting AI to be a silver bullet that it will fix messy processes or solve organizational dysfunction. If your workflows are chaotic, your data unreliable, or your teams untrained, AI will only accelerate the chaos and spread confusion faster.
Before bringing AI into your project, invest time in cleaning your data, clarifying workflows, and improving communication channels.
Another pitfall is ignoring user adoption. You can have the smartest AI tool, but if your team isn’t on board, it will fail. Involve people early and make sure they understand how AI works, and continuously gather their feedback.
Lastly, PMs sometimes treat AI as an end rather than a means. It’s easy to get caught up in tools and algorithms and forget that AI is meant to augment human skills, not replace them.
Q: To wrap up, what final words do you have for PMs who want to harness AI in their work?
Billal: Stop worshipping AI like it’s some miracle cure. Instead, invest in mastering it as a powerful augmentation to your expertise. It’s your deep domain knowledge, stakeholder relationships, emotional intelligence, and ability to navigate complexity that matter most. Those human skills remain irreplaceable.
We’re not heading into a utopia where AI solves all problems. We’re entering an era of greater complexity and rapid change. To survive and succeed, project managers must become mindful specialists, grounded in strong human skills and backed by highly specialized knowledge in areas like sustainability, enterprise systems, or financial operations.
AI is a critical element of this new mindset, but it’s only one piece of the puzzle. The future belongs to PMs who understand that AI’s power comes from partnership with human expertise.