Twenty years of complex programs have led to a simple conviction: effectiveness depends on the quality of interactions, not the power of tools. AI has not invalidated this conviction. It has made it more visible. As tools take over the mechanics of steering and control, what remains irreducibly human stands out with new clarity: the ability to bring people along, to energize and motivate the collective, to decide. AI can calculate theoretical risk, but only a human can choose which risk is acceptable, and when the unexpected happens, leadership cannot be delegated to an algorithm. Between these two poles lies everything that makes up these professions: context, pressure, relationships, timing, the unspoken, and intuition forged over years of experience.<\/p>\n
In these environments, steering never follows a purely mathematical logic. It plays out in a fog of uncertainty, conflicting interests, hidden agendas, critical dependencies, and, to be honest, a few well-established egos.<\/p>\n
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Empathy cannot be calculated<\/p>\n
Any HR leader familiar with group dynamics knows this experience well: an announcement about a relocation, made to a hundred people, does not produce a hundred identical reactions. Some will need the intent behind the decision to make sense, while others will focus first on the schedule and logistics. A portion of that group will only get on board if their opinion has been heard. No tool can automatically and systematically map out all these sensitivities, or give a leader the ability to adapt their message not to an average, but to each representative slice of a team. Empathy is neither intuition nor a natural gift: it is a skill. According to the PMI Pulse of the Profession 2023, 47% of projects fail to meet their original goals, and human factors consistently rank among the top causes cited. In these fields, empathy has nothing to do with softness or niceness. It functions as a high-precision relational technology.<\/p>\n
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An accelerator whose limits remain to be defined<\/p>\n
If empathy determines the value of what gets asked of AI, can its development be accelerated through AI itself? Immersive environments already rely on emotional AI to build training grounds that move beyond traditional role-play. Exposing an employee to avatars configured with distinct behavioral profiles helps them anticipate reactions and build more influence: one avatar challenges everything, another listens without responding, a third pushes back relentlessly. The approach is supportive by design and offers analysis of exchanges along with recommendations tailored to different personality styles.<\/p>\n
Human value begins where data runs out: in trust, negotiation, and crisis management. This human command of complexity gives rise to a particular kind of leadership, one built on influence, where managers earn authority through relevance rather than rank or hierarchical level. AI does not strip professionals of their importance, but it forces them to become excellent again in the areas where they cannot be replaced.<\/p>\n
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Decisions have no model<\/p>\n
Ethan Mollick, professor at Wharton and author of Co-Intelligence, sets a simple bar: being the human in the loop is not enough if that human lacks the skills to evaluate what the machine puts in front of them. One thing AI will never take on is the decision itself. Not creativity, which AI already fuels. Not necessarily empathy either, though the line between empathy and simulation still needs to be drawn. But judgment calls remain with the leader for a reason the law has always recognized: someone has to answer for the consequences of what they chose. What insurer would cover a decision made by an artificial intelligence forced to choose between two lives? Judgment requires an accountable subject.<\/p>\n
To see this clearly, look at what happens in the 70th minute of a World Cup match, right after conceding a goal. A team of analysts may have produced the best tactical projections in the world, but if no one can remobilize the locker room, the data stays dead on the page, however polished the dashboard looks. What makes the difference is the decision made under pressure, shaped by a human context that no model captures.<\/p>\n
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A few years ago, plenty of program and project managers swore they would never end up talking to a conversational agent. Convictions have shifted, and so have the tools. What has not shifted is what these tools demand from the people who use them. AI does not replace a PMO. It replaces a PMO reduced to a set of tasks. Tomorrow’s professionals will not be model operators but facilitators, able to pick up on weak signals that AI cannot read, to rally people where AI cannot build alliances, and to make judgment calls where AI cannot decide. This is the work HR leadership now needs to accelerate, because AI does not change the fundamental question of management. It exposes it. What separates a successful project from one that drifts off course has never been the power of the tools involved, but the quality of the leader holding them together.<\/p>\n","protected":false},"excerpt":{"rendered":"
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