From Taylorism to AI: The Great Shift in Business

Under the pressure of artificial intelligence, the business model inherited from the industrial era is faltering. By Xavier Comtesse & Pascal Eichenberger

An article available in AGEFI: https://agefi.com/actualites/opinions/du-taylorisme-a-lia-le-grand-basculement-de-lentreprise

The economic world is undergoing a transformation of unprecedented speed and depth. The business model that has long been the norm – the Taylorist company, with its division of labor, its integrated management (ERP) and its famous siloed processes – is collapsing in the face of the imperatives of artificial intelligence (AI).

This model, inherited from the industrial era, is now facing the emergence of its successor: the AI enterprise, a learning organization, fluid and driven in real time by flows of documents, data or other signals.

"The functions within the Taylorist company (here a GM factory in Biel in 1947) most often work in isolation from each other, each optimizing its own scope. Information circulates poorly, and coordination is often delayed."

The company of yesterday was characterized by an organization that can be summarized as: siloed, stock-driven, and slow. This model, while resilient, has become an obstacle to growth and survival in the age of AI.

Silo (organization)

Functions within the Taylorist company most often operate in isolation, each optimizing its own scope. Information flows poorly, and coordination is often delayed. Data itself becomes isolated silos, reinforcing a culture of control that stifles innovation and cross-functional collaboration.

Inventory (resource management)

In this paradigm, performance relies on accumulation: accumulation of finished products to anticipate market uncertainty, accumulation of untapped data, and accumulation of talent confined to rigid job descriptions. The company becomes a cumbersome structure where responsiveness is perceived not as a necessity, but as an unattainable luxury .

Slow (execution)

The speed of execution is the Achilles' heel of this model. Strategic and operational decisions are slowed down by endless procedures requiring validation, consensus, and compliance at all levels of the hierarchy. Innovation cycles stretch over months, even years, creating a growing gap between the defined strategy and its actual execution.

Faced with the acceleration of the market and the need to refocus on customer value, the company is forced to adopt a new model: the AI-driven model designed for continuous adaptability: flexible, flow, fast.

Flexible (organization)

The AI organization breaks down silos by adopting a structure of continuous transformation. Teams become autonomous, and talent is organized into networks rather than vertical hierarchies. Governance is distributed, fostering collective intelligence and the ability to pivot quickly in the face of change.

Flow (resource management)

The modern enterprise abandons the logic of accumulation (stock) in favor of the fluid circulation of resources (flow). Management is on-demand, and resources and capacities are allocated dynamically. Data, freed from its silos, circulates freely, transforming the enterprise into a living ecosystem. The results are immediate: optimized costs, real-time allocation of resources, and constant alignment with the value created for the customer.

Fast (execution)

Speed is no longer an obstacle, but a lever. Artificial intelligence, automation, and cloud computing are becoming the engines of operational performance. Validation processes are simplified or automated, and decisions are made closer to the field by autonomous teams. Innovation cycles are no longer measured in quarters, but in days. The company thus becomes a learning organization, augmented and self-adapting.

By Xavier Comtesse and Pascal Eichenberger