The Project Management Podcast

Artificial intelligence projects need more than a promising tool and an ambitious rollout plan. In episode 561, Cornelius Fichtner speaks with Erin Hill, Provost at Austin Christian University and a strategic consultant with experience implementing AI across higher education, legal, and financial organizations. Erin argues that AI leadership begins by asking whether an organization should use AI for a particular business outcome, not simply whether the technology can perform a task. She connects AI initiatives to organizational strategy, mission, governance, data privacy, security, and available resources. For project managers who inherit an AI initiative from senior leadership, she explains why a clear project charter, stakeholder conversations, and decisions about tool selection and employee training matter before implementation begins. The discussion also examines how needs assessments help teams find repetitive tasks and high-friction processes where AI may add value. She warns against introducing AI into disconnected or outdated systems without first addressing their underlying problems. Her examples show why organizations need trustworthy information, clear accountability, and people who understand how the tools fit into their daily work.

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Flexible leadership sounds straightforward until a project leader has to decide what to do differently when the situation changes. Kevin Eikenberry, author of Flexible Leadership: Navigate Uncertainty and Lead with Confidence, returns for a second conversation focused squarely on practical application. Kevin explains why project leaders often fall back on autopilot, how habits and even leadership identity can make flexibility difficult, and why the phrase "it depends" should serve as a trigger to stop and consider the context before acting. He also challenges the assumption that consistency and flexibility compete with each other. Effective leaders can remain consistent in their values, purpose, and project boundaries while adapting how they lead. That becomes particularly important when projects operate in uncertain or complex environments where leaders cannot know every variable, established practices may not produce the expected results, and new information can require a different response.

David Luria, author of Flatten the AI J Curve: Your Unfair Advantage in the Race to Enterprise Adoption, brings a practical conversation about what happens when an AI pilot moves into real operational use. Luria, a vice president and business manager at T. Rowe Price and a Six Sigma Black Belt, explains the AI J curve: productivity can fall before it improves, especially as teams learn new workflows, run old and new processes in parallel, and adjust to changing responsibilities. He argues that project managers should set expectations before implementation begins, keep early scope narrow, and use short stepping-stone projects to learn quickly. He also explains why culture matters. AI often removes tasks that people associate with their expertise, so adoption requires more than access to a chatbot. Leaders and project managers need to create room for experimentation, communicate what will change, and help people understand how their roles can shift toward higher-value work. Luria calls for business ownership close to the work, supported by leadership, IT, and risk teams, rather than treating AI transformation as a technology handoff.

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Sara Gallagher returns to examine a frustrating reality for project managers: organizations can employ smart, experienced, well-intentioned people and still produce the same bad outcomes again and again. Sara, president of The Persimmon Group and creator of the Big Dumb Questions newsletter, brings more than 15 years of consulting experience to a discussion that starts with artificial intelligence and quickly expands into how organizations make decisions, manage transitions, respond to change, and structure project leadership. She explains how she separates work into simple, complicated, and complex categories when deciding what to give AI, and why simple and selected complicated work offer the most practical opportunities today. From there, Sara and Cornelius examine decision latency and the danger of judging a decision only by its eventual outcome. Sara argues that leaders should focus on whether they made a defensible decision based on the information and criteria available at the time. They also examine project handoffs, where weak preparation can allow value to leak away and risk to increase just as the project reaches a critical transition point.

Artificial intelligence can now appear in PMP exam scenarios, but that does not mean candidates need to study AI technology. In Episode 557, Cornelius Fichtner starts with the PMP Exam Content Outline and separates what PMI actually says from what many candidates may assume. AI appears in the introduction as one of the trends PMI evaluates when researching changes in professional practice expectations, but it does not appear as a task or enabler in the People, Process, or Business Environment domains. That distinction matters because the PMP exam measures project management competencies, not technical mastery of the tools a project manager may use. AI can show up as a project risk, a deliverable, or a tool that a team wants to adopt, while the underlying exam question still asks whether you can manage risk, evaluate a tool, address a stakeholder concern, handle change, or make an accountable project decision. Cornelius also shows the kinds of questions candidates should not expect, including technical questions about generative versus predictive AI, prompt-writing techniques, and AI model selection.

Sara Gallagher, President of The Persimmon Group and author of the LinkedIn newsletter Big Dumb Questions, joins Cornelius Fichtner to answer the uncomfortable questions most PMO leaders avoid. The conversation follows four threads: PMO identity, design, accountability, and the future. It opens with the biggest question of all: are PMOs dying? Sara takes an optimistic view, with caveats. She explains that traditional PMOs are built on standardization, which raises weaker projects to a certain ceiling but also flattens excellent, tailored work down to the law of averages. She then paints a concrete picture of what comes next: project managers with robust knowledge bases and AI agents that draft synthesized status reports, simulate steering committee members such as a CFO, and hand results to a PMO agent that standardizes everything for portfolio roll-up. The result combines hyper-customized stakeholder communication with standardization only where it is truly needed, and it frees the PMO to coach project managers in sophisticated stakeholder management and risk practices.

A brief personal update from your host. My wife recently had a serious fall that required hip surgery and rehabilitation, so my time is fully devoted to her recovery right now. One recorded interview is on its way to your feed shortly, but the schedule will stay quiet for the next few weeks while I reschedule cancelled interviews and we get through this together.

The seven performance domains from the PMBOK Guide 8th edition form the backbone of how project work actually happens, and they are woven into nearly every situational question on the PMP exam. The catch is that the exam never labels them. Cornelius Fichtner, PMP, takes you through all seven domains: Governance, Scope, Schedule, Finance, Stakeholders, Resources, and Risk. For each domain, he presents a sample question from The PM Exam Simulator, works through the answer choices, and then hands you a structured takeaway built around three skills: how to recognize the domain in a scenario, how to evaluate your answer options, and how to eliminate the traps. Along the way you work through fourteen exam-style questions, including drag and drop matching, choose-multiple formats, and classic four-option scenarios covering everything from negative float and crashing to contingency reserves and psychological safety.

Preparing for the PMP exam means developing the ability to make sound decisions under pressure, not simply recalling definitions from a textbook. In this lesson, drawn directly from the PM PrepCast PMP exam prep course and PrepCast PMP Exam Simulator, Cornelius Fichtner walks through all six project management principles from the PMBOK Guide 8th Edition and shows exactly how to recognize and apply them when facing the kind of ambiguous, scenario-based questions that appear on the actual exam. Each principle gets its own sample question from the PrepCast PMP Exam Simulator, a step-by-step walkthrough of why the wrong answers are wrong, and a second practice question so listeners can immediately test what they have learned. The episode covers all six principles in sequence: Adopt a Holistic View, Focus on Value, Embed Quality into Processes and Deliverables, Be an Accountable Leader, Integrate Sustainability Within All Project Areas, and Build an Empowered Culture. Each principle is taught not as a concept to memorize but as a mindset to recognize and apply, because the exam consistently rewards situational judgment over terminology.