According to the Politecnico di Milano Observatory, 77% of Italians are concerned about artificial intelligence's potential impact on the labor market.
In the past two years, particularly since GenAI demonstrated its capabilities, the relationship between artificial intelligence and work has become a hot topic. Two perspectives have emerged: one more optimistic, which sees GenAI as the ultimate tool to eliminate routine, low-value tasks, enabling companies to refocus part of their workforce on more significant activities; and a more pessimistic view, emphasizing GenAI's ability to replace roles that employ thousands, if not millions, of people, with clear consequences for current and future employment.
Automation becomes smarter
The 77% of Italians who are wary of AI focus on its ties to automation, which has grown smarter and able to surpass predefined boundaries over the years.
Traditional automation has always targeted the most routine, repetitive, and rule-based tasks. Robotic Process Automation, the technological cornerstone of digital system automation, has consistently applied itself solely to predictable, repetitive areas of business processes. Today, however, we are witnessing a pivotal shift in the concept of hyperautomation, which not only expands automation’s scope but also enriches it with advanced components like Natural Language Processing (NLP) and machine learning. These advancements grant machines decision-making capabilities that seemed like pure science fiction just a few years ago. This transition from traditional to intelligent automation not only marks a new chapter in the relationship between humans, work, and technology but also creates apprehension among today's and tomorrow's workforce.
Artificial Intelligence and Work: The Disruptive Role of GenAI
As mentioned, GenAI has intensified discussions about the connection between artificial intelligence and work. Its ability to generate content, images, code, videos, documents, and other outputs that were once exclusively human tasks—using natural language instructions (prompts)—has had a rapid and significant impact on the labor market. Just months after the introduction of ChatGPT, there was a recorded 21% decline in job postings for automatable roles, with a particular focus on jobs related to writing and the IT sector, especially coding and software engineering.
How have organizations responded to this revolution? Observing the market, three main approaches can be identified:
- Some organizations have embraced Generative AI quickly and extensively to streamline processes and reduce costs. GenAI has been immediately identified as a powerful driver of productivity and efficiency, leading to its rapid integration wherever possible to boost competitiveness.
- Other organizations, particularly in specific sectors like education and media, have developed and implemented restrictive policies. This stems largely from fears of losing control over their data and fueling the use of unauthorized tools. Such an approach is clearly temporary, awaiting a new equilibrium in the relationship between humans and machines.
- Some organizations have begun exploring the concept of job augmentation, integrating AI to enhance the skills, productivity, and capabilities of their employees. This balanced and forward-looking approach appears destined to become the reference model for the future of work.
We Are Far from Human-Machine Substitution
The impact of AI on work is undoubtedly complex and requires a thorough evaluation, ideally supported by reliable data.
Fortunately, some key points remain clear: research suggests that the use of generative AI in specific contexts can increase individual productivity by up to 40%, creating unprecedented opportunities for businesses. Not surprisingly, those who have sought to limit the use of this technology have done so solely to buy time while developing tailored strategies.
The impact on the labor market is and will be significant. According to the Politecnico di Milano, artificial intelligence has the potential to automate 50% of equivalent full-time jobs (FTEs, meaning the total jobs derived from the hours allocated to automatable tasks). Even more striking is the estimate that, in the Italian context, "over the next 10 years, the new capabilities of machines could perform the work of 3.8 million people." While potentially alarming, these figures highlight the need for a balanced approach that can harness AI's opportunities while mitigating its risks, including social ones.
To better understand the phenomenon, it is essential to emphasize the term "potential." AI may potentially take over the work of nearly four million people in Italy, but it is equally true that:
- To date, the process has been minimally implemented (estimated at just over 5% of FTEs, primarily in large companies);
- The substitution effect can be, and likely will be, offset by demand for new roles requiring AI system management skills;
- The management costs of some AI systems may be comparable to or higher than those of a fully human-managed underlying process;
- AI still has clear limitations requiring human experience and cognitive abilities.
On a systemic level, the intelligent automation of processes and activities also represents a strategic response to increasingly significant demographic challenges. In Italy, the aging population requires innovative solutions to boost productivity and safeguard the pension system's sustainability. The productivity boost provided by GenAI (and similar intelligent solutions) could be decisive for shaping the societal balance of the near future.
Job Augmentation is the solution
While fears are legitimate, the hypothesis of complete human replacement by intelligent systems is unrealistic—at least for now and on a large scale.
The intrinsic limitations of AI systems, such as hallucinations in generative models, difficulties in contextual understanding, and the orchestration of different capabilities, highlight the need for a collaborative approach. Job augmentation thus becomes the true solution: AI serves as a tool that supports workers, enhancing their abilities and freeing them from low-value tasks.
There are already fascinating use cases:
- In industry, so-called cobots work closely with operators, improving precision and efficiency in production lines.
- In healthcare, AI supports doctors in interpreting radiological imaging (e.g., genomics), allowing them to dedicate more time to complex cases.
- In contact centers, AI-based virtual assistants provide a more efficient and personalized customer experience. These systems automate the handling of common requests, delivering quick and accurate responses. Additionally, by analyzing the emotional tone of conversations, they can route complex queries to the most suitable operators, improving customer satisfaction.
Job augmentation is not only a more ethical approach than replacement but also the most advantageous for companies, which simultaneously achieve increased productivity, improved product and service quality, and higher employee satisfaction—a key driver of productivity. It’s a classic virtuous cycle.
However, transitioning toward a collaborative relationship between AI and humans requires significant cultural and organizational change. Providing tools is not enough to ensure people adopt and use them daily. Processes must be rethought with collaborative automation in mind, and investments must be made in training and skills development, creating a workplace environment that fosters continuous support from machines for human-managed activities. Only in this way will it be possible to fully exploit the potential of artificial intelligence and build a more equitable and prosperous future of work.
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