Essays on meaning, work and AI

Founding essay

When Management Meets the Absurd

Camus, work and meaning in the age of AI

Most discussions about artificial intelligence and work begin with prediction. Which jobs will disappear? Which tasks will be automated? Which skills will remain valuable? Which organizations will become more efficient? Which workers will be left behind?

These questions matter. But they do not yet reach the deepest layer of the problem.

Work is not only a set of tasks. Management is not only coordination. Organizations are not only systems for producing outputs. For many people, work has become one of the main places where identity, dignity, usefulness, recognition and belonging are negotiated. To lose work, to be displaced in work, or to feel that one’s judgment is no longer needed is therefore not only an economic event. It can become an existential event.

This is why the age of AI requires more than technological literacy. It requires existential literacy. It requires us to ask what happens to the person who works when work changes its meaning.

The manager as an existential figure

Management often presents itself as a discipline of control. It promises planning, coordination, prediction, measurement and improvement. In this picture, the manager appears as someone who makes uncertainty manageable.

Yet the lived experience of management is often very different. Managers repeatedly encounter situations that cannot be fully controlled: crises, interpersonal conflicts, moral dilemmas, organizational failures, competing expectations, emotional exhaustion, uncertainty and the fragile dependence of human projects on other people.

This way of thinking has an older management genealogy. George S. Odiorne’s idea of the existential manager already described the manager as someone who must act within uncertainty, ambiguity and situational limits rather than from the safety of a complete theory. A related existential-systems approach to managing organizations later connected existential concerns with systems thinking and organizational life.

This is where existential self-development becomes important. It asks not only how managers improve performance, but how they understand the crises, anxieties and responsibilities that shape who they become at work.

In this sense, the manager is not only a decision-maker. The manager is an existential figure: someone who must act without complete certainty, take responsibility without full control and remain human within systems that often reward only performance.

Camus and the recurrence of crisis

Albert Camus helps us understand why managerial life often feels cyclical.

In the myth of Sisyphus, the human being pushes the stone uphill only to see it roll down again. The point is not simply that life is meaningless. That is the shallow reading. Camus is interested in the confrontation between the human desire for order and the world’s refusal to provide final guarantees.

My earlier work on Camus and management explored this link between absurdity, recurring crisis, revolt and the ethical value of human life in management.

Management knows this confrontation well. A team is stabilized, and then a new conflict appears. A process is improved, and then the context changes. A crisis is solved, and another arrives. A plan is completed, and the future refuses to behave as planned. The organization asks for certainty, but the world answers with ambiguity.

This is not an accidental feature of management. It is one of its existential conditions.

The temptation, in such a condition, is to seek a final system: a method, ideology, technology or managerial doctrine that will remove contradiction once and for all. Camus warns against this temptation. Revolt is not the fantasy of total control. Revolt is the refusal to surrender human value to abstraction. It is the decision to act without pretending that action can eliminate the absurd completely.

This matters in the age of AI. AI systems promise new forms of prediction, optimization and automation. They may help us see patterns, improve decisions and reduce burdens. But they can also strengthen the illusion that the human condition itself can be solved by better systems.

The existential question is not whether AI can support management. It can. The question is whether organizations will use AI to deepen human responsibility or to avoid it.

Work after work

Meaning After Work begins from a double meaning.

It does not mean only leisure after the workday. It asks what remains meaningful when work can no longer carry the identity, dignity and purpose we have asked it to carry.

Modern societies have placed an enormous burden on work. Work has been asked to provide income, status, community, self-realization, discipline and moral worth. We often ask people not simply what they do, but who they are through what they do.

AI intensifies the question because it enters not only manual labour, but also domains associated with knowledge, creativity, judgment and expertise. It does not merely threaten repetitive tasks. It unsettles the symbolic structure through which educated workers have understood their value.

If a machine can write, summarize, design, advise, calculate, code, translate and decide, then the question is not only: what tasks remain for humans?

The deeper question is: what forms of human presence still matter?

Labour, work and post-work emptiness

This question also connects with Joe Alan Jones’s expanded understanding of work in response to AI . Jones argues that debates on automation often reduce work to paid employment or economic necessity. But work is not only what we do to survive. It can also be a mode of meaningful human activity.

His distinction between labour and work is useful here. Labour names activities bound to necessity, survival and welfare. Work, in his account, names meaningful activity through which a person can articulate selfhood beyond mere necessity.

This matters because automation may remove burdens, but it may also remove the very practices through which people learn, struggle, create, relate and find meaning. A future beyond employment is therefore not automatically a future rich in meaning. It may become empty if the human practices that once carried meaning are also automated away.

Meaning After Work begins precisely at this threshold. It does not ask for a simple escape from work. It asks how human beings can preserve meaning when employment, usefulness and productivity can no longer serve as the main foundations of identity.

The crisis of usefulness

Many people fear AI because they fear becoming useless.

This fear is not irrational. Usefulness has become one of the dominant moral languages of modern work. To be useful is to justify one’s place. To be productive is to prove one’s value. To be employable is to remain socially legible.

But a human being is not reducible to usefulness.

This is easy to say and difficult to live. Organizations are built around usefulness. Careers are built around usefulness. Even self-development often becomes another form of usefulness: improve yourself, optimize yourself, become more resilient, become more productive, become more adaptable.

Existential management asks whether this language is sufficient.

The problem is not that usefulness is bad. The problem is that usefulness becomes dangerous when it becomes the only language through which we understand human worth. A person who is not currently useful is still a person. A person who fails is still a person. A person who cannot adapt quickly enough is still a person. A person whose work is transformed by AI is still not a remainder of automation.

Co-being after optimization

One of the deepest losses in organizational life is the loss of real relationship.

Managers and workers can become functions to one another. The leader becomes a role. The employee becomes a resource. The customer becomes a data point. The colleague becomes an obstacle. The self becomes a performance project.

My research on managerial crisis and co-existence examined how critical situations in managerial life are often linked to disrupted interpersonal relationships and to the need to rediscover more relational ways of being at work.

This is why co-being matters. Co-being is the practice of remaining present with oneself and another person without reducing them to performance, usefulness, diagnosis or failure. It is not sentimental. It is not a rejection of organization. It is a condition of any organization that still wants to remain human.

In AI-mediated work, co-being becomes more important, not less.

As more communication is filtered through platforms, metrics, dashboards and intelligent systems, organizations risk mistaking information about people for contact with people. A system may know that someone is underperforming. It does not know what it means to sit with them in their exhaustion. A model may identify risk. It does not take responsibility for how a human being is addressed.

The future of human-centred AI cannot therefore be only interface design, fairness metrics or compliance frameworks. These are necessary, but insufficient. Human-centred AI must also ask how human beings remain capable of attention, dialogue, responsibility and care around intelligent systems.

Existential contradictions

The AI age will not remove contradiction. It will multiply it.

We will be pulled between efficiency and dependency. Between creativity and skill erosion. Between personalization and surveillance. Between assistance and displacement. Between adaptation and self-betrayal. Between responsibility and automation. Between the desire to remain relevant and the desire to remain whole.

These contradictions cannot always be solved by choosing one side.

Sometimes responsible action means learning to inhabit contradiction without collapsing into resignation or escaping into shortcuts. Resignation says: nothing can be done. The shortcut says: only survival matters. Revolt says: I cannot control everything, but I will still act in a way that preserves human value.

This is not heroic in the dramatic sense. Often it is quiet. It may look like refusing to use AI to deceive. It may look like protecting time for real conversation. It may look like admitting uncertainty instead of performing mastery. It may look like redesigning a workflow so that human judgment is not merely decorative.

Existential contradiction is not a failure of management. It is one of the places where management becomes human.

Social enterprise and the value of human life

Social entrepreneurship offers an important lesson here.

Social enterprises live with contradiction from the beginning. They must combine economic survival with social mission. They must remain financially viable without betraying the people or communities they exist to serve. They must work with scarcity, uncertainty and competing expectations.

This is why research on social entrepreneurship and philosophical management is relevant for the AI age. It shows that management can be understood not only as technical coordination, but also as a value-driven practice shaped by interpersonal relationships, uncertainty and paradoxical situations.

The lesson from social enterprise is not that mission language solves everything. It does not. Mission can drift. Values can become branding. Ethical language can hide exploitation. But social enterprise shows that management can begin from a different question: not only what produces value, but what kind of value is worth producing.

In the AI age, this question becomes urgent. A technically successful system can still produce human loss. An efficient organization can still become existentially empty. A productive worker can still feel that their life is being drained of meaning.

Beyond responsible AI

Many initiatives in AI ethics ask how we can make AI responsible. This is important. But it is not enough.

We must also ask how humans and organizations can remain responsible around AI. Responsibility cannot be delegated entirely to systems, policies or tools. It must be carried by people who are willing to remain answerable for what they build, adopt, automate and normalize.

This is the starting point of existential human-centred AI.

The question is not only whether an AI system is aligned with human values. The question is whether the human world around the system still cultivates people capable of valuing.

Are workers still able to question? Are managers still able to listen? Are organizations still able to protect spaces where human judgment matters? Are people still recognized beyond performance? Are relationships still possible in systems optimized for speed?

AI may become more intelligent. That does not guarantee that organizations will become wiser.

Meaning after work is not the end of work

Meaning After Work is not an anti-work project.

Work will continue. People will still build, care, teach, organize, repair, design, decide, trade, create and serve. The question is not whether work disappears completely. The question is whether work can be reimagined without making human worth depend entirely on productivity.

The future may require a different relationship between work and life.

Not work as the sole source of identity. Not leisure as mere recovery from exhaustion. Not AI as a replacement mythology. Not management as control over uncertainty. Not ethics as compliance after the fact.

Rather, a more difficult possibility:

• work as one place where meaning may appear, but not the only one,
• technology as assistance, but not destiny,
• management as responsibility, not only efficiency,
• organizations as relational worlds, not only systems,
• human beings as more than their usefulness.

This is not a solution. It is a direction.

Camus did not offer escape from the absurd. He offered revolt within it. Existential management does not offer escape from crisis, contradiction or uncertainty. It asks how we might remain human inside them.

That may be the central task of the AI age: not only to ask what work remains for human beings, but to ask what kind of human beings we become when work no longer explains us.