Human capacities, critical thinking, skills of tomorrow, natural resources consumed by AI: these questions matter. But before deciding what to protect, we still need to understand what the adoption of AI changes.
Imagine a management that wants to reduce its costs through AI. Customer service deploys an AI chatbot: more requests are processed, faster and at lower cost. So the company is expanding its use. The chatbot takes over part of the work of the agents.
What’s next? HR reviews its workforce assumptions. Operations is rethinking processes around this capability. IT no longer manages a simple tool; it maintains a system on which the business depends. A supplier who provided a solution gradually becomes difficult to replace. Managers raise productivity targets.
Taken separately, these decisions are rational. But put end to end, they tell another story. The company didn’t just automate its customer service. It began to reorganize itself around what the chatbot makes possible.
From now on, it is no longer quite the same people who do the work, nor the same people who participate in the decision-making. Certain human expertise is less requested. New dependencies arise. And each subsequent decision is made in an organization that the previous ones have already changed.
Over time, these changes take hold. Fewer people have mastered the old process. The objectives include the pace allowed by the AI. Changing course may then require rebuilding skills, processes or alternatives. And yet, nothing necessarily failed. The organization has simply changed.
It is then that the questions arise: What human capacities should we develop? Where to preserve critical judgment? Which dependencies to accept? Are the resources consumed by AI justified by the value created? What options do we want to keep open? The answers depend on two things: what we call “value” and our understanding of the real consequences of our choices.
If a chatbot saves thirty minutes per employee per day, that doesn’t create thirty minutes of value. This frees up thirty minutes of capacity. Value depends on what the organization does with it.
And if the efficiency gained today is paid for tomorrow by less expertise, resilience or freedom to change course, then part of this value will have been created at the cost of capabilities that the organization will need later.
Creating value, capturing it and preserving the capacity to create it tomorrow: this is where sustainability takes on its full meaning. Sustainability therefore does not begin because AI consumes or replaces. It begins with our ability to understand what our decisions really set in motion.
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