Cristian Randieri is Professor at eCampus University. Kwaai EMEA Director, Intellisystem Technologies Founder, C3i official member.
We are witnessing a profound technological transformation involving the most sophisticated artificial intelligence techniques, which are silently altering our social and economic fabric. This phenomenon raises several doubts and questions, the most crucial of which concerns the ability to safeguard employment in a context where entire professional categories are being redefined or even eliminated.
Addressing this problem is not easy if we aim to staunchly defend existing jobs. We must find new strategies capable of preserving the intrinsic value of workers by enhancing typical human capabilities, including the adaptive resilience and transformative capacity they bring to the world of work.
Peiying Chua’s Key Principle
This perspective is also shared by Peiying Chua, LinkedIn’s Asia-Pacific Chief Economist, who stated at an international conference: “You protect the worker, you protect the talent; you don’t protect the job itself.” The statement reflects a fundamental principle: People’s skills and intelligence are dynamic resources, while tasks, by their nature, are contingent and subject to obsolescence.
Human-Machine Co-Evolution: A Strategic Opportunity
Current applications of generative artificial intelligence and machine learning models have transcended the confines of industrial automation to enter the typically human realms of creativity, language, logic and even diagnosis. We are witnessing a natural evolution whereby the professions affected are not limited to low-skilled workers, but are beginning to extend to highly specialized professional roles, including lawyers, doctors, journalists, designers and analysts.
However, it has been demonstrated that, although artificial intelligence is capable of replicating models and processes, it remains partially limited in its complete understanding of context, management of ambiguity and assumption of ethical responsibilities.
It is precisely in the space between computational power and human understanding that the possibility of virtuous integration unfolds. Protecting workers, from this perspective, means shifting the focus from function to individual evolution. The goal is not to prevent change—after all, no one in history has ever managed to halt technological progress—but to enable individuals to transform their skills, perhaps by assuming new roles to create value within complex technological ecosystems.
The Role Of AI Shadowing
An innovative approach that follows this direction is the so-called “shadowing” of artificial intelligence. Rather than suddenly replacing the worker with an automatic system, the person observes, interacts with and actively contributes to the implementation of AI in their professional context. During this phase, the worker analyzes the logic underneath the algorithm, identifies its limitations, highlights any inconsistencies with the real-world context and contributes to the definition of new operational practices. This process can reduce the negative impact of change while also encouraging the emergence of new hybrid roles, such as AI integrators, context curators or ethics supervisors.
From a scientific perspective, this approach is consistent with theories of transformative learning and distributed intelligence. Research in the fields of work psychology, sociology of innovation and complex systems theory shows that human-machine integration is more effective when change is co-designed and internalized through meaningful processes, rather than imposed vertically. In other words, a worker who actively participates in the transformation of their role develops not only new technical skills but also a new professional identity.
Organizational And Institutional Challenges
To make this change systemic, multilevel interventions are needed. Companies must rethink their human resources management strategies, investing in continuous training programs, metrics that enhance adaptability and flexible work environments where learning is an integral part of daily operations. Institutions must update labor regulations, including rights related to the digital transition, and redesign education systems to develop skills such as critical thinking, algorithmic literacy and innovation ethics.
In this context, welfare should provide support to people not only during periods of unemployment but also throughout the entire retraining process, ensuring they receive not only high-quality but also personalized training that is recognized by the market. In other words, we must transform the concept of one-off opportunity into a structural right, because the ability to learn continuously is a key factor for long-term employability.
The Risks Of Technological Inertia And The Benefits Of Inclusive Strategies
Failing to pay close attention to these developments—or ignoring them—can create technological inertia, where the adoption of AI translates not only into a mechanism of social exclusion, but also into a loss of tacit knowledge and polarization between the digitally literate and digitally illiterate. Empirical evidence shows that, where people are not involved in industrial transitions, there are significant increases in the level of uncertainty-related stress and organizational disengagement—all factors that lead to reduced productivity.
Companies that adopt inclusive technological transformation strategies that put people at the center experience higher levels of innovation, greater organizational resilience and a stronger reputation among investors and stakeholders. Human capital, when properly leveraged, proves to be the only truly irreplaceable asset in the medium to long term.
A New Future For Work
The AI revolution does not mark the end of work, but rather the end of repetition, linearity and meaningless automation. The work of the future will not be that which outlives the machine, but that which can question, supervise, integrate and guide it. What is needed is to respond to the challenge posed by AI not by protecting work as it has been until now, but by creating new conditions so that every worker feels like a protagonist of the latest change and no longer a victim.
The concept of value must no longer reside in the ability to perform the task itself, but in the ability to learn, adapt and give new meaning to the new, ever-evolving context we are experiencing today. Because in the age of artificial intelligence, the most difficult capital to replicate is not code, but consciousness.
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