The Project Economy has changed where value is created. More of today’s enterprise value now comes through change: transformation, AI adoption, digital modernization, portfolio decisions, new operating models, customer experience redesign, regulatory initiatives, and strategic projects that cut across functions. This is the capability shift. Organizations have moved from primarily running the present to continuously building the future, but leadership development has not kept pace. Leaders are still often developed for operational excellence, then asked to sponsor, govern, prioritize, adopt, and sustain project-shaped work. That is why the gap facing many organizations is not simply a talent gap, and it is not only a project management gap. It is a leadership capability gap.
What happens when the work shifts, but the leadership system does not?
Sometimes a name change is not a branding exercise; it is evidence that the work has changed. I understood this more clearly during my time at Amazon, when the language around the people function was shifting toward People eXperience and Technology. I was also part of the team supporting the launch of Amazon’s Ottawa facility, and that experience gave me a practical education in something I did not yet have the language to describe. A facility launch is not only an operations event, an HR event, or a technology event. It is project-shaped work: hiring, onboarding, learning, safety, leadership readiness, scheduling, communication, escalation, technology adoption, and employee experience all moving together under pressure. The facility may open as a building, but what really launches is a human operating system.
That lesson stayed with me because it showed that people capability, employee experience, operational readiness, and technology adoption are not separate agendas. In project-shaped work, they become one system. That is why the phrase People eXperience and Technology has always seemed more important to me than a function name. People, because capability, trust, learning, and leadership determine whether an organization can absorb change. Experience, because employees do not live transformation through strategy decks; they live it through workflows, tools, managers, policies, systems, friction, support, and the daily moments that either build confidence or create resistance. Technology, because work is now mediated, accelerated, redesigned, measured, and increasingly reshaped by digital systems and artificial intelligence.
The future of HR is not only people process. It is enterprise capability.
This is why Beth Galetti’s recent LinkedIn post about Amazon covering one AWS AI or Machine Learning certification exam per year for every employee caught my attention. I appreciated the post because it made the point in practical terms. Read narrowly, it is an upskilling announcement. Read strategically, it is a signal that AI literacy is no longer being treated only as a specialist technical skill. It is becoming part of the operating vocabulary of the workforce.
But that distinction matters. A certification exam can create access to knowledge, confidence, and a shared language, but a credential alone does not prove capability. Capability is what happens when learning changes decisions: when a leader can ask whether an AI use case is solving the right business problem, whether the data is ready, whether the workflow has been redesigned, whether adoption has been planned, whether risk has been governed, whether ownership is clear, and whether the promised value is measured after launch rather than assumed at go-live. Training opens the door; capability is what walks through it.
This connects directly to the broader shift I have been writing about in this series. Uncertainty has become the operating environment rather than an occasional entry on the risk register. Organizations have become project-driven while leadership development has remained operation-driven. More people are building the future than simply running the present. The initiatives that carry that future have grown too interconnected for leadership models designed around stable functions. And as AI absorbs more transactional and administrative work, human leadership capability, rather than administrative throughput, becomes the scarce advantage.
The question is no longer whether organizations can manage projects. The question is whether leaders can carry change all the way to value.
The scale of the shift is not in dispute. Writing in Harvard Business Review, Antonio Nieto-Rodriguez reported the Project Management Institute’s estimate that the value of project-oriented economic activity worldwide would rise from $12 trillion in 2017 to $20 trillion by 2027, drawing some 88 million people into project-oriented roles. He also documented a quieter inversion inside organizations: a generation ago, roughly 80 percent of organizational resources supported operations and 20 percent supported projects; today that ratio has effectively reversed. Value is now created primarily through change. Yet the results have not kept pace with the investment. The same article cites Standish Group research indicating that only about 35 percent of projects undertaken worldwide succeed. The reflexive reading is that organizations have a project management problem, solvable through better tools, methods, and certifications. That reading is not wrong, but it is incomplete, and its incompleteness is where the real gap hides.
The real gap sits above the level of the project manager. In most organizations, leaders are selected and promoted for operational excellence: running a function well, meeting recurring targets, managing stable teams, controlling cost, and delivering predictable performance. They are then asked to sponsor transformations, govern portfolios, arbitrate competing initiatives, lead AI adoption, protect investment value, and convert strategy into realized benefits. These are different activities. They call for different judgment. They require different forms of accountability. Yet few leaders have been deliberately developed for them. This is the leadership capability gap: the distance between the leadership that project-driven, AI-enabled work now demands and the leadership capability that organizations have intentionally assessed, developed, embedded, and rewarded.
So here is the uncomfortable question: are we promoting leaders for how well they ran the present, then asking them to build the future without developing the capabilities that future-building requires?
This is not a talent problem. The leaders in question are usually intelligent, committed, experienced, and capable. The deficit is developmental. Operational mastery does not automatically transfer into the ability to lead change, because the two draw on different disciplines. Kaplan and Norton located the persistent failure of sound strategies not in their design but in the execution system meant to deliver them. Rumelt argued that strategy is fundamentally an act of choice, including the discipline of deciding what not to do. Teece, Pisano, and Shuen described dynamic capability as the capacity to sense change and reconfigure the organization in response. Kotter’s work on transformation failure reached a similar conclusion from another direction: the recurring causes were not merely technical shortcomings in execution, but failures of leadership, including weak urgency, weak coalitions, unclear vision, and premature declarations of victory. None of these capabilities is automatically acquired by managing operations well. Each has to be built.
Artificial intelligence is now widening the gap rather than closing it. As automation takes over more transactional, administrative, and analytical work, the distinctive human contribution moves upward toward judgment, prioritization, governance, stakeholder alignment, responsible adoption, and the translation of strategy into outcomes. These are leadership capabilities. An organization that has not developed them cannot simply purchase them, assume them from tenure, infer them from confidence, or outsource them entirely to project professionals, data scientists, consultants, vendors, or tools.
This is where Beth Galetti’s post landed for me. Not because one certification benefit solves the leadership capability gap. It does not. But because it shows the conversation moving in the right direction: people, learning, technology, and future readiness are no longer separate leadership conversations. They are the same conversation. If AI learning is treated only as a training benefit, the organization may increase knowledge without changing capability. If it is treated as part of a broader capability system, the question changes from “How many people completed the course?” to “What can the organization now do that it could not do before?”
That is the capability test.
Can employees identify better AI opportunities? Can leaders govern risk more intelligently? Can teams redesign workflows around new tools? Can sponsors distinguish technical success from business value? Can operational leaders build adoption rather than simply announce deployment? Can the enterprise sustain benefits after the initiative closes? These are not questions of training activity. They are questions of applied leadership capability. They determine whether AI becomes a source of sustained value or another wave of impressive pilots, disconnected tools, and unrealized benefits.
So the label matters. The Project Economy did not create only a project management gap, addressable with more practitioners and better tooling. It created a leadership capability gap, and the two require different responses. The first is a matter of delivery mechanics. The second is a matter of how organizations develop the people who sponsor, govern, prioritize, adopt, and sustain change, whatever the title on the door. Much of what closes this gap is already defined across established project, program, portfolio, risk, governance, business analysis, agile, change, PMO, and AI delivery disciplines. The difficulty is not that the capabilities are missing. It is that they are seldom developed as an integrated leadership capability, and seldom recognized as leadership at all.
Thank you, Beth Galetti , for putting a timely and practical example into the public conversation. Your post brought back a lesson I first learned inside Amazon: the future of people leadership is not only about HR process. It is about building the capability system through which people, experience, technology, learning, and value come together.
In your own organization, is AI capability being treated as a training problem to be solved with more courses and certifications, or as a leadership problem to be solved by developing the people who sponsor, govern, adopt, and sustain the work? And more broadly, has your leadership system caught up with the Project Economy, or is it still preparing leaders for a world where value was created mainly by running stable operations?
The answer tends to reveal how wide the gap has quietly become.
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References
Galetti, B. LinkedIn post on Amazon supporting AWS AI and Machine Learning certification access for employees: https://www.linkedin.com/posts/beth-galetti-60b1106_our-leadership-principle-learn-and-be-curious-share-7472722357149802497-y-pW/?utm_source=share&utm_medium=member_desktop&rcm=ACoAADXpgzcBK07EX7Q0QuWb6ThnpGrcKJnAOOw Kaplan, R. S. and Norton, D. P. (2008) The Execution Premium: Linking Strategy to Operations for Competitive Advantage. Boston: Harvard Business Press. Kotter, J. P. (1995) ‘Leading Change: Why Transformation Efforts Fail’, Harvard Business Review, 73(2), pp. 59–67. Nieto-Rodriguez, A. (2021) ‘The Project Economy Has Arrived’, Harvard Business Review, 99(6), pp. 38–45. Rumelt, R. P. (2011) Good Strategy / Bad Strategy: The Difference and Why It Matters. New York: Crown Business. Teece, D. J., Pisano, G. and Shuen, A. (1997) ‘Dynamic Capabilities and Strategic Management’, Strategic Management Journal, 18(7), pp. 509–533.