Global Talent Trends Mercer

The challenge of the man-machine era: from the talent rebus to the 'augmented manager'

Companies struggle to find AI talent and develop appropriate leadership, while the urgency of reskilling to support digital transformation grows

by Gianni Rusconi

8 June 2026

5' min read

Translated by AI

Versione italiana

5' min read

Translated by AI

Versione italiana

The artificial intelligence has now firmly entered the strategic agenda of companies, but while technology is running, organisations and people are (often) struggling to keep up. This is, in a nutshell, the picture that emerges from the Global Talent Trends 2026 by Mercer, a business unit of the American multinational Marsh specialising in HR consulting. The survey, which involved almost 12,000 C-Suite executives and managers, HR managers, investors and workers globally, returned a very clear picture: the AI-driven transformation has already begun, but the human capital required to support it continues to represent the main bottleneck.

In fact, the numbers of the study tell of a reality made up of high expectations and still insufficient preparation, with 54% of top managers considering it a priority to integrate talents with AI-related skills into their workforces, while 59% of HR executives say they have difficulty finding suitable profiles. At the same time, 98% of executives expect significant changes in organisational design in the next two years and 63% indicate the redesign of work through algorithms, intelligent agents and automation as a priority. Yet, only 51% of leaders (compared to 65% in 2024) believe their organisation is truly ready for the era of human-machine collaboration.

Human capabilities and AI make the difference

The perception that emerges from Mercer's research confirms the assumption that the AI game is no longer played solely on the adoption of technological tools but through the ability to integrate skills, processes and organisational models into a coherent vision of transformation. It is no coincidence that investors also seem to be looking at this aspect with increasing attention: 77% say they are more inclined to invest in companies that are training their employees in AI skills, and 72% believe that organisations capable of effectively integrating human capabilities and artificial intelligence are destined to develop a more solid competitive advantage. As Marco Valerio Morelli, Managing Director of Mercer Italia, observes, "the scarcity of talent is indicated as the main driver of people plans by more than half of the C-suite and only 32% of top managers believe that their organisation is now really able to effectively combine people skills with technology". The real challenge, in short, lies in the ability of companies to translate the potential of innovative tools into productivity and sustainable growth.

The skills mismatch and the reskilling imperative

If there is a terrain on which the ability of companies to cope with the artificial intelligence revolution is concretely measured, it is undoubtedly that of skills. It is certainly not the first time that companies and HR managers have to deal with a talent 'shortage', but generative models and increasingly popular agent solutions are profoundly changing the nature and scale of this phenomenon. And this profound acceleration stems above all from the fact that organisations are not only looking for technology specialists but also need people capable of translating the potential of AI into business applications, governing its adoption and accompanying change within business processes. According to the study, 65 per cent of executives expect between 11 per cent and 30 per cent of their workforce to be reallocated or retrained over the next two years as a function of AI deployment programmes, while, in parallel, 63 per cent of executives believe it is necessary to adopt people management models based on competencies rather than traditional roles.

In Italia, the problem takes on special characteristics because the generalised difficulty in finding advanced technology skills is compounded by certain structural factors, such as the composition of our production fabric, made up mainly of SMEs and supply chains. "Compared to more mature markets such as Northern Europe, the United Kingdom or the United States,' Morelli observed in this regard, 'our country suffers from a certain fatigue in making the training supply grow at the same rate as business demand, and this translates into very concrete impacts: longer times to start up AI projects, difficulties in bringing them to scale, and greater bottlenecks in governance and implementation.

The skills mismatch consequently becomes a strategic issue, but also a very operational one, directly affecting productivity and the speed at which pilot projects are transformed into industrialised solutions. The issue, in other words, goes beyond the search for data scientists, machine learning engineers or cloud architects because the real goal of companies are hybrid figures, capable of moving between vertical and specialised skills and knowledge of industrial processes and of translating the potential of AI into concrete use cases in different sectors. In this scenario, upskilling and reskilling become not only a lever for people development but a necessary condition for the competitiveness of organisations. Human capital thus returns to be a central element of industrial strategy as an asset to be exploited and the real challenge, as Mercer's CEO effectively summarises, 'is not to choose between people and technology, but rather to transform AI into real value for business without impoverishing human capital. The companies that will do this best will be those capable of bridging the skills gap, redesigning roles and responsibilities and building a new alliance between business and workers based on skills upgrading, trust and clarity about change'.

The need for a new leadership model

If the availability (or rather the shortage) of skills is the first knot to unravel, the second concerns the issue of leadership. In this sense, the research highlights an apparent paradox, which stems from the contrast between the growth curve of investments in AI technologies and the decrease in confidence (complained of by top management) in their ability to effectively manage the transformation. Among the most significant data contained in the study is that only 51% of executives consider themselves ready to tackle the new organisational paradigm, compared to 65% two years earlier.

'There is a gap,' Morelli emphasises in this regard, 'that is above all cultural and leadership, rather than strictly technological, precisely because technology today is increasingly accessible. The focal point of the issue is therefore another: companies must rethink processes, roles, metrics and decision-making methods, and it is on this level that the gap between awareness and action often arises, what we call the awareness-action gap. One of the most frequent mistakes,' continues the CEO, 'is to consider AI as an issue to be entrusted to the IT area or to a small group of specialists, whereas in reality artificial intelligence changes the way people work, make decisions and measure results. A second mistake is to start with the tools instead of the business problems: many organisations experiment with interesting solutions, but without a clear strategic priority, without governance and without impact metrics, with the risk of accumulating proof of concept that never really reach production".

In this context, a different managerial figure emerges from the one that characterised the last season of digital transformation, one that wears the guise of a facilitator of new ways of collaboration between people and digital agents and no longer just that of a decision-maker and controller. In the AI era, leadership is needed that knows how to build trust, foster experimentation and create the conditions for technological innovation and human value to move in the same direction. Without forgetting that, as Morelli recalls, 'bias, explainability, responsibility in the use of AI and data security are issues that must be addressed from the outset. If clear policies are lacking, perceived risk increases and the organisation tends to slow down: leadership must therefore create the conditions for AI to be adopted with confidence, responsibility and real impact'. For Italian companies, the game is played on two fronts: on the one hand bridging the skills gap and on the other developing a new managerial culture capable of driving change. Because, as the Mercer report suggests, the competitive advantage in business marked by artificial intelligence will reward above all those companies that manage to integrate it better with the talent, skills and 'augmented' leadership of the managers who guide them.