What history reveals about AI and the Project Manager profession
| Every major technological revolution has triggered the same anxiety. Steam engines would destroy artisanal work. Tractors would eliminate farm labor. Computers would make offices obsolete. Each time, the warning sounded familiar: “This time is different.” Today, artificial intelligence has taken that role. For months, if not years, the impact of AI on the Project Manager profession has been debated. Will AI replace Project Managers? Will project management as a discipline disappear? Or will it be fundamentally transformed? I want to elevate this debate by stepping away from prediction and alarmism and instead looking backward. History, as economist Xavier Sala‑i‑Martín argues in De la sabana a Mart (literally From the Savannah to Mars), is not a forecast but a powerful teacher. In his book (unfortunately still untranslated into English), Sala‑i‑Martín traces how Homo sapiens evolved from its emergence roughly 200,000 years ago in the Serengeti savannah to a species capable of landing spacecraft on Mars. In spirit, it sits close to the work of authors like Yuval Noah Harari: a long‑arc view of human progress, and adaptation. One of its most relevant messages for today’s AI debate is simple but profound: while technology repeatedly destroys specific jobs and tasks, it has never eliminated human work as a whole. What changes is where humans add value. Below, I map five historical lessons from technological revolutions to concrete project management competencies; not to argue that Project Managers are “safe,” but to explain why the role is likely to become more human, not less. 1. We are bad at imagining future jobs and future project workOne of Sala-i-Martín’s central arguments is that humans systematically fail to imagine the jobs that will be created by innovation. In 1895, no expert could have predicted digital marketers, YouTubers, or UX designers. MIT economist David Autor estimates that roughly 60% of today’s occupations did not exist in 1940. The problem is not that experts were careless. Future work often emerges indirectly, as a second or third order effect of technology. What this means for Project Managers Much of today’s AI anxiety focuses on current PM tasks: scheduling, reporting, risk tracking, documentation... Yes, many of these will be automated or heavily augmented. But history suggests the more important question is: what new coordination problems will AI create? Early signals are already visible:
PM competencies amplified: systems thinking, strategic framing, ambiguity navigation. 2. Automation replaces tasks, not professionsWhen calculators entered offices, many believed accounting roles would vanish. When computers arrived, clerical work was expected to disappear. Neither happened. Instead, productivity rose and roles evolved. Technology consistently eliminates tasks, not entire professions. What this means for Project Managers AI will outperform us at:
PM competencies amplified: judgment, prioritization, decision‑making under uncertainty. 3. Technological transitions are painful and increase the need for PMsSala-i-Martín is explicit: the fact that innovation ultimately creates work does not mean transitions are easy. Workers displaced by mechanization did not automatically reskill. Societies had to invest in education, coordination, and institutional change. What this means for Project Managers AI adoption is not a technical rollout. It is a transformation. And transformations fail most often because of:
PM competencies amplified: change leadership, stakeholder management, organizational navigation. 4. Innovation creates new needs and new project portfoliosThe automobile didn’t just replace horses. It created tourism, hotels, road infrastructure, logistics networks and entirely new urban designs. Innovation doesn’t merely solve problems, it also creates new needs that later become essential. What this means for Project Managers AI is already creating new categories of work:
PM competencies amplified: portfolio management, value realization, cross‑functional integration. 5. “This time Is different” has always been wrong, including nowFrom tractors to computers to AI, the recurring claim has been: this time, humans will not adapt. History shows the opposite. Not because progress is guaranteed, but because societies reorganize around new constraints. What this means for Project Managers As automation increases, complexity does not disappear, it rather intensifies. And complexity elevates the value of deeply human capabilities:
PM competencies amplified: human leadership in complex systems. Conclusion: from controllers of work to designers of progressHistory does not tell us that Project Managers are immune to technological change. It tells us something more useful. Roles that sit at the intersection of technology, people, and decision making do not disappear. They evolve. AI will not end project management. But it will act as a filter. It will steadily automate coordination and execution mechanics, and leave behind the parts of the role that require judgment, ethical reasoning and leadership across uncertainty. For Project Managers, the real question is not whether AI will change our profession. It already is. The real question is whether we choose to remain controllers of tasks or step fully into our role as designers of progress, stewards of change, and leaders of complex human systems. For those willing to adapt, that shift is not a threat. It is an invitation. |
Artificial Intelligence & Machine Learning: Data is King
| I am far from being an expert in artificial intelligence (AI) and machine learning (ML). Actually, I spent some time googling these two concepts which - the truth to be said - are commonly used interchangeably. The ultimate goal of AI is to create intelligent machines that simulate the human thinking capability and behavior. Deep Blue, the famous supercomputer that defeated chess world champion Garry Kasparov falls into this category. On the other hand, ML is the art of these machines to learn in real time from all gathered data without being programmed explicitly. Most subject matter experts state that Deep Blue cannot be considered an example of ML because it was programmed to beat humans but learned little along the way. ML has evolved tremendously since the Deep Blue times in late 1990s. Its skyrocketing advancement poses novel challenges in our lives, especially when it comes to trust. An example of this - perhaps not the most relevant, yet illustrative - can be observed in Nascar races. In them, AI and ML play a vital helping hand in understanding a massive data set, such as identifying anomalies and contributing causes in real-time. The algorithms analyze the real time data and yield the best course of action to win the race: optimum timings to tank or change tires, best time to overtake a rival, etc. In one of the races, the machine advised to do A, yet the team went with their gut feeling (they knew better!) and picked B. They lost and realized that option A, indeed, would have been a far better choice.
At the end of the day, AI and ML require above all just one thing, data. And a project generates a massive amount of it. Having in mind the DIKW pyramid, data is treated to obtain information, which is then further processed into knowledge and finally wisdom. How this translates to project management? One can think of a situation that project managers often come across during a project: making scenarios. The PM is responsible for gathering and process all relevant inputs from SMEs or any other suitable sources and present the various options with their cons and pros to the sponsor, steering committee... It is easy to envision a machine (or software) that is able to not only analyze the data and define possible scenarios but also to provide timely alerts to avoid certain less favorable scenarios, thereby increasing the odds of delivering a successful project. This specific case example wants to reflect on the adapting role that the PM must face as the AI/ML technology becomes more mature. Cab drivers will become obsolete when self-driving cars become available at mass scale level. The threats that AI/ML will exert in project management is yet to be seen. Can they live in perfect harmony? Have your saying in the comments section below. |
