La Dolce Vita Paradox

Executive Summary 

This study examines Italy's national AI talent market, revealing a striking paradox: while the country's cultural appeal attracts AI professionals, structural economic barriers simultaneously drive them away. Through analysis of nearly 25,000 AI talent profiles and interviews with sector professionals, we uncover how La Dolce Vita both makes and breaks Italy's AI workforce ambitions, revealing a number of remarkable features within the AI talent pool, such as: 

Italy's AI workforce remains 87.9% domestic. 
Unlike many other leading AI nations, Italy does not have a significant international AI workforce and instead relies largely on domestic talent. Our research suggests that Italy struggles to attract global talent due to low salaries, language barriers, and limited career progression for non-Italians. Similar factors may influence the emigration of skilled Italian AI professionals, with Switzerland emerging as the top destination for emigrating Italian AI professionals. 

Italy defies European trends with exceptional female AI participation, but this drops off at senior levels. 
Milan leads European cities with 30.7% women in its AI workforce, nearly double the regional average. Unlike many other industries in Italy that remain male-dominated, STEM fields offer women safer career paths with clearer advancement opportunities and stronger networks. Women consistently outperform men in AI advanced degrees, yet this promise collapses at senior levels: from 35.4% of entry roles, women drop to just 14.2% of senior positions due to unequal pay and inflexible work cultures. 

The country pioneered aggressive talent repatriation through tax innovation.  
Since 2010, Italy has implemented various income tax deduction schemes to attract talent back to the country. Most recently, the "Rientro dei cervelli" programme offered 70-90% income tax exemptions for highly educated workers, drawing 75,000 Italians back from abroad in 2021, with 40% choosing Lombardy. However, the Italian government limited the scope of the programme, citing €1.3 billion in lost revenue, and the new Lavoratori Impatriati programme’s more limited scope may threaten some of these gains.  

Geographic concentration creates a two-speed AI economy.  
Lombardy hosts over 7,000 AI professionals while southern regions like Sicily and Basilicata each have fewer than 1,000, exacerbating Italy's historic north-south divide despite national policies promising equitable development. Talent is also clustered in the regions around Milan, like Lombardy, reflecting the centrality of that AI hub for universities, research institutions, and headquarters for startups and tech companies. This difference raises questions about effectiveness of national policies aimed at ensuring an equitable diffusion for the benefits of AI technologies. 

Italy stands at a crossroads between its unique assets - exceptional female participation, cultural appeal, proven tax incentives - and structural challenges that risk transforming it into merely a training ground for talent before they emigrate to other nations. 

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Introduction 

As Europe lays out ambitious plans to develop and attract top AI talent, understanding how individual countries implement national strategies to build diverse and capable AI talent pools becomes increasingly critical. Without examining the nations shaping Europe's unique talent dynamics, policymakers can draw only limited insights from different national approaches to gender equality, technical expertise, and talent migration. This paper represents the first in a series of case studies examining European countries, beginning with Italy's paradoxical position in the global AI talent race. 

Previous interface research papers, including Where is Europe's AI workforce coming from?, AI's Missing Link: The Gender Gap in the Talent Pool, and Technical Tiers: A New Classification Framework for Global AI Workforce Analysis identified that Italy has a smaller gender gap in its AI workforce compared to EU averages, and Milan leads European AI hubs in gender equality with 30.7% female AI professionals. Additionally, Milan is considered Italy's most relevant startup hub, driving the majority of VC investment since 2019. However, Italy also is experiencing one of the largest brain drains in G7 countries, losing approximately one-third of each annual graduate cohort between 2011 and 2021. Driving the brain drain are limited professional opportunities in the country and comparatively low salaries, especially in STEM-related fields. 

Seeking to counteract this phenomenon, the Italian Strategy for Artificial Intelligence 2024-2026 seeks to “increasingly recognize the importance and centrality of our talents, aiming for the highest quality standards for their training and actions that can then retain them in Italy with concrete prospects for personal and professional growth.” Since 2010, the country has implemented some unique tax deduction policies, offering unique financial incentives for skilled workers to return to Italy, although those have recently been seriously limited. 

Our analysis draws from a dataset of nearly 25000 individuals in the Italian AI labour pool and examines the unique factors that differentiate Italian talent from that of other European nations. Italy stands out among European countries with a largely domestic talent pool, with 87.9% of its AI workforce coming from Italy. Additionally, Italy has a strong history of working to reattract top talent back to the country, implementing a series of repatriation schemes to attract back talent that has left to work abroad, which many AI experts cited as a reason to return. Our paper also examines the factors that shape women’s participation across the country in the AI labour pool, and the obstacles that may be faced to retaining them throughout their careers.  

Examining Italy's AI talent ecosystem proves crucial not only for understanding current national industry dynamics, but for addressing the broader challenge of how European countries can develop effective strategies to attract and retain talent, even from neighbouring nations. Through comprehensive examination of Italy's current AI talent landscape and identification of strategies that distinguish Milan and other Italian hubs, this research aims to inform policymakers seeking competitive approaches in the global race for AI expertise. 

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Findings  

Regional AI talent divide in Italy 

These charts reveal Italy's stark regional AI talent divide, with northern regions dominating both in absolute numbers and per capita distribution. Lombardy leads with over 7,000 AI professionals, reinforcing Milan's position as Italy's premier tech hub, while southern regions like Sicily, Basilicata, and Molise each host fewer than 1,000 AI workers. Even when adjusted for population size, the northern advantage persists, with Lombardy's surrounding regions of Piemonte, Emilia-Romagna, and Trentino Alto Adige all showing significantly higher AI talent density than the national average. 

This geographic concentration reflects and reinforces Italy's historic north-south economic divide, an issue raised repeatedly by our interview subjects. Many of the people interviewed stated that there were simply much more opportunities to work or study AI in the north, mentioning cities like Milan, Bologna, or Turin, which boast urban centres with strong universities, research institutions and a higher density of tech industries.   

“Some structural issues such as limited private investment, weaker infrastructure, and fragmented support systems continue to hinder [Southern Italy’s] attractiveness for AI talent” (Monica Cerutti, 2025).  

“In the north we have many statistics that are better than the Eurozone: the case of Milan, the case of Trento, the case of North-East Italy closer to Padova, Venice, Bergamo and Turin” (Valerio Mancini, 2025). 

The concentration of jobs also reflects this geographic divide, with one interviewee stating that “most of the tech jobs, if they’re in person, they’re in Milan or worse, Rome” (Interviewee F, 2025), exacerbating historical economic divides and undermining national AI strategy goals of equitable distribution. 

“[The Agenzia per l’Italia Digitale] promotes widespread and inclusive adoption of artificial intelligence through the implementation of the Three-Year Plan for Informatics in PA, the Guidelines on the Adoption of AI and support to the Italian Strategy for [AI] 2024-2026. The Agency works to strengthen the digital capacities of all administrations, including local and peripheral ones, by facilitating the integration of AI solutions in key areas such as health, justice, mobility and education. Through shared tools such as and technical support activities, AgID contributes to reducing territorial and sectoral disparities, ensuring that the benefits of technological innovation are accessible in a fair way throughout the national territory” - AgID 

While national agencies like AgID (Agency for a Digital Italy) officially promote equitable AI adoption across all regions through digital skills programs and infrastructure support, global investment patterns continue strengthening northern advantages. Major tech companies like Microsoft channel massive cloud infrastructure investments exclusively into northern Italy, despite government promises of nationwide digital equity. 

Lombardy, the region in which Milan is located, leads Italy with the highest concentration of AI talent for a variety of regions. Startups in Milan have driven the majority of VC investment in Italy since 2019, and the number of employed ICT specialists is up 9.7% since 2022 and 24.3% since 2017, with ICT representing 4.7% of Lombardy’s workforce and processional, scientific, and technical activities representing another 9.5% (Assolombarda, 2024). It is also ranked as a moderate innovator according to the European Commission’s Regional Innovation Index 2023, indicating a strong presence of technical expertise in the country.  

“Milan is a leading European business and innovation hub, with a strong presence of global tech companies, startups, and a thriving entrepreneurial ecosystem. The city’s strategic position within Europe, its high quality of life, and its rich cultural heritage make[s] it an appealing location for professionals” (Monica Cerutti, 2025). 

Additionally, Milan offers services, like support opening a bank account, that attract and facilitate the migration of top international talent, with an increased focus on accessibility and diversifying existing industries based in the city. There are eight universities within the city, hosting over 232,000 students, of which 7.4% are international, which exceeds the national average of 6.8% international students in 2022/2023. The majority of international students coming from China, Iran and India, with 47.4% studying subjects related to STEM, reflecting Milan’s centrality in the Italian AI ecosystem. One member of academia states that in Milan, it is also easier for international talent to overcome language barriers in their daily life, mentioning that it is possible to speak English in the city centre.  

“We have two very good universities here from my major, at least they are very highly ranked in the world, so a lot of people come here for the names of this university” (Interviewee C, 2025). 

The national AI strategy lays out the importance of “promoting mobility, the return of Italian talents from abroad, and the attractiveness of Italian universities and research centres for foreign talents.” Some interviewees shared that not only were universities in Milan perceived well, but that the process of obtaining a visa to study in Italy was relatively easier when compared to other countries. One academic spoke of the travel ban that the US put in place in 2018 for many individuals, whereas the processing time between receiving an offer for a PhD position to arriving in Italy was only 45 days. The interviewee notes that this may be different because PhD positions are salaried, in comparison with master’s degrees which require a guarantee of available finance, but that ultimately the immigration process was simple and to their benefit.  

It is not just the city’s amenities that attract talent. Interviewees mentioned how culture and quality of life may also shape people’s decision to return to Italy. Milan benefits from a unique blend of a strong industry presence and a globally recognized high quality of life.  

“When we talk about living in Italy, it's always kind of a dream, like the Italian dream. So, I have friends that had to choose between Italy and the Netherlands, they choose Italy because of the culture, like the La Dolce Vita” (Interviewee D, 2025). 

All of these initiatives aim to ease the bureaucratic obstacles that would prevent international talent from moving to the city and seek to facilitate various processes for non-Italian speaking residents. They highlight the investments that cities like Milan are making to remain competitive for global AI talent.  

Milan’s intense concentration of talent doesn’t mean that the city is without challenges. One interviewee mentioned:  

“The quality of life is not so good because especially the housing in Milan is super expensive in comparison to the salary you get; I found that the salary and work-life balance also don’t quite match with each other” (Interviewee C, 2025).  

Another interviewee mentioned that even international talent from countries like the US, Germany and UK found that the cost of living in Milan was “crazy expensive” (Interviewee F, 2025). Like many other top tech hubs, Milan is grappling with challenges related to cost-of-living, which may influence the decision of talent to migrate there when weighing the purchasing power they could command with their salaries. 

Talent Migration Dynamics 

Although there is a growing concentration of international AI talent in northern Italian cities like Milan, Italy still has a largely domestic AI workforce. Previous interface research has found that Italy’s AI labour force has a strong majority composed of domestic talent, as opposed to the proportions of international talent seen in other European countries. Our research revealed that Italy’s AI labour market is only about 12% international, with 87.9% of the Italian AI labour force having received their undergraduate degrees in Italy, a factor we use in our analysis as a proxy for nationality. For more details on this, please refer to our methodology section.  

The countries representing the largest sources of international AI talent in Italy are Argentina, Iran, and the UK. 1.6% of foreign AI talent in Italy comes from Argentina, reflecting a historic diaspora community of Italians in Latin American countries starting in the 19th and 20th centuries. This may be influenced by laws that, before 2025, imposed no generational limits to claiming Italian citizenship by descent, which is passed ‘by blood’ as long as one could prove they had an ancestor who lived after 1861, when Italy was unified. This was considered one of the most generous citizenship laws in a European country. This also did not impose the extensive language proficiency requirements that naturalization in Italy as a foreigner would entail. Today, applicants for citizenship must have at least one parent or grandparent that was an Italian citizen at the time of their birth. This could mean that some portion of the domestic labour force also holds dual citizenship and moves to Italy for studies or work after growing up in other countries around the world. 

While not as large of an Iranian diaspora in Italy as in other global minority countries like the US, there is some evidence of a historically strong relationship between Iran and Italy. Additionally, there was an increase of 19.3% from 2023 to 2024 in Iranian population in Lombardy, representing 26.6% of the total Iranian population in Italy. 

Not only is Italy an interesting landscape with regards to attracting international talent, but also reveals strong patterns of concurrent emigration of AI talent out of Italy. Switzerland was found to be a top destination for Italian AI talent, probably due to a shared language, high wages, and geographic proximity. Similarly, many Italians may choose to go to other EU nations, like Germany, the UK, and France due to relatively low wage premiums to education in Italy, especially for STEM-related education: “high skill workers that do their training in Italy are also prone to migrate in large numbers to other EU countries where they can find better jobs and mostly higher wages.”

“Within the AI technical engineering workforce, there's a lot of emigration from Italy into countries like Switzerland or to the UK where they can command higher salaries for the work that they're doing” (Valerio Mancini, 2025).    

“If I want to stay in academia here, it’s super competitive for non-Italian people, so they have a very, very hard process of how you switch from your postdoc to be assistant professors, which I think makes it almost impossible for us as young researchers and non-Europeans to stay in the country” (Interviewee C, 2025). 

Not only are financial reasons limiting Italy’s ability to attract international talent but also limited career progression opportunities. Outside of academia, multiple individuals mentioned that industry jobs show a high bias towards hiring Italians and often prioritize speaking Italian over international working languages like English. The recent limitation of tax incentives, persistently low salaries relative to other European hubs, and preferential hiring of Italians create structural barriers to attracting and retaining international talent, making Italy overly dependent on domestic graduates who statistically are more likely to emigrate for better opportunities. 

Key Policies for Talent Reattraction 

Migration to Italy and retention or re-attracting top talent is increasingly important for Italy, which is faced with an aging population and weak demographic growth across the country, which is especially apparent in southern regions. Italy’s AI labour market is particularly interesting because there have been incentives for key talent to move to, or return to, Italy after working or completing their studies abroad. While salaries in the country may be lower, tax deduction schemes can offer appealing financial incentives to work in Italy, even at a lower salary in absolute numbers. Building on evidence that tax incentives for skilled workers are an effective way to attract them to a country, Italy has offered four different forms of tax incentives since 2010 to attract top skilled workers to the country. 

Multiple interviewees cited these financial incentives as key factors in their decision to return. These financial incentives for highly skilled workers reflect what many of the interviewees mentioned as a large hindrance to their return to Italy: every professor, post-doctoral researcher, and PhD candidate mentioned the financial limitations of careers in Italy.  

“[It’s a] huge discount in taxation and I know some people that actually went abroad for 2 years just to come back later[...] your salary potentially can be doubled with this incentive.” (Interviewee E, 2025)  

“Simplifying entry pathways for non-EU professionals is also crucial. Italy’s introduction of a start-up visa programme and tax incentives for returning professionals (such as the “Impatriate Tax Regime”) has helped reduce barriers and made the country more competitive in the global talent market.” (Monica Cerutti, 2025) 

While many people interviewed stated that they knew the salaries they commanded in Italy were lower than those in other countries, offering tax incentive structures might reduce the financial barriers to joining the Italian labour pool. 

According to la Repubblica, 75,000 Italians returned from abroad in 2021, which should reflect a success in attracting talent back to the country. 40% of the Italians who returned went to Lombardy, the region around Milan. However, it is imperative that the Italian government considers the plethora of reasons that AI talent may or may not choose to settle in the country. Previous research has also found that poor career progression prospects and working conditions have also pushed top STEM talent to go abroad, despite only 2% of PhD candidates wanting to go abroad permanently. Removing financial incentives without addressing the other obstacles that may lead to the migration of top AI talent challenges Italy’s attempt to counteract the brain drain of top AI talent. 

Women’s “leaky pipeline” in the Italian AI workforce 

This figure shows the gender distribution by seniority in the Italian AI labour market, reflecting the challenges as women spend years within the labour force. In some ways, it leads parts of the European AI ecosystem, with previous interface research finding that Milan leads European cities with 30.7% women in their AI labour force. This echos other research, which reflects that women represent a larger percentage of universities, outperforming male counterparts in rates of on-time graduation and their average grade at the time of graduation. Italy also produces the highest percentage of AI papers published by at least one female author among OECD countries. However, achievements in early stages do not translate into a professional environment in which women continue to thrive. Instead, women face higher rates of attrition as they advance in their careers, slowly leaving in between every career level. 

Italy demonstrates exceptional gender equality in AI education and early career stages. According to one interviewee, the country is increasingly focusing on gender inclusion within tech and research sectors, promoting different initiatives to encourage women to pursue STEM careers, including different scholarships, mentorships and partnerships with tech companies to offer internships to young women in AI and engineering fields, perhaps explaining the higher rates of women in early stages of their careers. Additionally, some interviewees note the perceived career stability of the STEM field, which may also attract women with career prospects and competitive salaries. 

“Another key element is the role of influential female figures in the Italian AI ecosystem, which has inspired more women to enter the field” (Monica Cerutti, 2025).  

A member of academia interviewed stated that while men might represent most computer science students at the bachelor's degree level, they tend to join industry directly after they graduate. By contrast, women progress up to more advanced degrees in AI, representing more of the cohorts of students and receiving better grades than their male counterparts. 

“Women in Italy are increasingly taking on entrepreneurial roles, launching AI-based startups or leading innovation within established tech companies. This broadening of roles illustrates the growing presence and influence of women in Italy’s AI ecosystem” (Monica Cerutti, 2025). 

Another reason for the strong female participation in the AI labour pool could be the strong cultural emphasis on family life in Italy. One interviewee mentioned that companies that support this and provide flexible working conditions tend to see higher retention rates among female employees. These multiple factors may create workforce dynamics that allow women to pursue their studies and careers in AI, creating flexibility and incentives to participate and shape Italy’s growing AI field. 

Despite strong female participation at entry levels (35.4%), women represent only 14.2% of senior-level AI roles. The high participation rates of women in the AI workforce does not reflect meaningful gains at higher positions. In the years that follow graduation, permanent employment contracts are less common for women than they are for men, at 49.9% vs 56.1%, respectively. A member of academia studying the Italian labour market echoed this, stating that in Italy, women represent almost “50% of part-time jobs, and men only 27%” (Valerio Mancini, 2025). The interviewee also said that only 18% of women receive a salary that is commiserate with their qualifications, including level of study, and that they receive lower salaries than men. This may push women out of the AI labour force as they move up the career ladders, failing to achieve the contractual stability or salaries that their male counterparts achieve.  

Despite Milan’s leadership in gender equality in the AI labour market, the "leaky pipeline" phenomenon continues, driven by unequal pay, limited contractual stability, and uncompromising work-life balance challenges that particularly affect women with caregiving responsibilities. 

“Some of my friends really said, ‘who's staying there until 9:00 PM in the office?’ Single male people living in Milan. If you have family, it's really hard to live this life; or in general, if you don't want to be exploited” (Interviewee E, 2025). 

Milan received certification for gender equality, making it the first large local authority to receive this award. In turn, Milan similarly rewards companies that also possess this certification, introducing recognition into the tender phase for organizations with definitive proof of commitment to gender equality. This certification may explain its strong performance regarding gender equality, as well as high rates of female participation in the labour market in Milan. Moreover, it may also be that women may be less willing or able to move abroad to pursue other opportunities due to caretaking opportunities in Italy, leading to a higher concentration of women in the country while Italian men pursue opportunities abroad. 

This demonstrates that achievements in one area of ensuring gender equality does not necessarily translate to roles up the career ladder, and that although the higher rates of participation by women may attract other women to the field of AI, it does not keep them. This emphasises the need for targeted and comprehensive interventions aimed at retaining women at every stage of their careers.  

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Recommendations 

Based on the findings of this case study, three key recommendations emerge for strengthening Italy’s AI talent ecosystem. They build on the elements of the Italian case study that work well, while addressing the factors that limit the country’s attractiveness for top AI talent. 

1. Redesign Tax Incentives with Targeted Regional Focus 
   Restore and restructure talent attraction tax schemes to address both international competitiveness and regional inequality. Create tiered incentives that offer the highest benefits (80-90% tax exemptions) for AI professionals relocating to southern regions, while maintaining moderate incentives (50-60%) for northern hubs. This approach could simultaneously counter brain drain and redistribute AI talent to underserved regions, supporting national goals for equitable digital development. 

2. Implement Comprehensive Women's Career Progression Programs 
   Develop targeted interventions to address the "leaky pipeline" phenomenon affecting female AI talent. This should be through the establishment of mandatory pay equity audits, creation and assurance of flexible work arrangements that support work-life balance, and introduction of career advancement programs specifically for women transitioning from junior to senior roles, ensuring contractual stability parity between men and women. 

3. Diversify Talent Sources While Strengthening Domestic Retention 
   Launch a dual-track strategy that combines aggressive international talent attraction with domestic retention programs. This can be done through simplified visa processes for AI professionals from key talent origin countries, while simultaneously addressing the root causes of domestic brain drain through competitive salary frameworks and improved career progression opportunities. This could be facilitated through "AI talent corridors" that facilitate movement between Italian cities and European hubs, positioning Italy as a strategic base rather than a temporary destination. 

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Conclusion 

Italy's AI talent story reveals a country caught between impressive achievements and persistent challenges. The La Dolce Vita cultural appeal and strong academic institutions could lead to the development of a competitive AI ecosystem, but structural realities often undermine what the country does well. 

Italy has genuine successes worth recognizing: Milan leads European cities with 30.7% female AI participation, far ahead of most tech hubs. The country's tax repatriation programs proved that eligible individuals were 27% more likely to return than they were before the policies were implemented, bringing 75,000 Italians back home in 2021 alone. Italy also produces the highest percentage of AI research papers with female authors among OECD countries, showing real strength in developing female talent. 

But these achievements exist alongside contradictions that limit their impact. Milan, despite its gender equality leadership, still demands Silicon Valley hours. Professionals work until 9 PM in a country built on work-life balance, with the city becoming what many try to escape when choosing Italy. Additionally, the representation of women drops sharply from 35.4% at entry level to 14.2% in senior roles, suggesting that early promise doesn't translate to long-term advancement 

International talent also faces mixed signals. Italy's cultural appeal and strong universities may draw people in, but professional integration remains difficult. Companies often prioritize Italian language skills over technical expertise, and networks can be hard to penetrate. Italy's 87.9% domestic workforce composition suggest that retaining domestic talent is sensible, given its large share of the labour market, although this limits the diversity in attracting international talent. 

Geographic concentration presents another challenge. While Lombardy's 7,000+ AI professionals demonstrate the success of regional hubs, southern regions offer fewer opportunities and thus miss out on the benefits of having a more robust AI talent pool. Italy's innovation policies work well where they're implemented but haven't overcome historical north-south disparities. The recent limitation of successful tax incentives also illustrates tensions between policy goals. After proving these programmes worked, the government scaled them back citing €1.3 billion in costs. This shows both fiscal responsibility and the difficulty of sustaining innovative approaches. 

Building on what works, Italy could strengthen its position through targeted improvements. Redesign tax incentives with regional focus, offering higher benefits (80-90% exemptions) for southern regions while maintaining moderate incentives (50-60%) for northern hubs. Address women's career progression through pay equity audits, flexible work arrangements, and targeted advancement programs. Diversify talent sources by simplifying visa processes while improving domestic retention through competitive frameworks and career development. 

Italy has built a foundation of genuine strengths: policy innovation, gender inclusion in education, cultural appeal, and successful regional hubs. The challenge isn't starting from scratch but rather extending these successes more broadly and addressing the gaps that prevent them from reaching full potential. 

The La Dolce Vita Paradox reflects Italy's current position: a country with real assets that don't always deliver on their promise. With focused attention to structural barriers, Italy could transform from a nation of unrealized potential into a leading destination for global AI talent. 
 

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Acknowledgements

This research was generously supported by the Carl Zeiss Stiftung as part of the project 'Strength and weaknesses of the German and European AI ecosystem - talent in the focus.'

We extend our sincerest thanks to the many individuals who contributed to this research by sitting for interviews or sending us information related to our research questions, including but not limited to Monica Cerutti, Women in AI Italy Ambassador, Donya Rooein, and Valerio Mancini, Professor and Director of the Divulgative Research Center at Rome Business School. Your contributions have been invaluable to the creation and deepening of this research. We are grateful to Ruggero Marino Lazzaroni, whose support with data science was essential for creating the graphs and parsing the data. We also sincerely thank Sabrina Santos Peres and Teja Adarsh Dodda for their essential support and contributions to this research.  

We would also like to express our appreciation to the numerous scholars, practitioners, and policy experts who engaged with our previous research and whose thoughtful questions and feedback encouraged us to develop this more comprehensive study. Your intellectual curiosity and support have been instrumental in shaping this work. 

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Appendix 

Methodology & Data Sources 

This study utilizes comprehensive workforce data provided by Revelio Labs, a workforce intelligence company that aggregates publicly available professional profiles, job postings, and related sources. The dataset from 2024 encompasses 659 million individuals in the global workforce. From this extensive population, we identified approximately 1.6 million individuals constituting the global technical AI workforce based on our classification framework. For the Italian case study, this dataset encompassed 135,553,049 individuals, representing approximately 52.81% of Italy's 2024 labour force. 

Semi-Structured Interview Methodology 

This study utilized seven semi-structured interviews for qualitative primary data collection, primarily with members of academia, government officials, leaders in industry, and students pursuing advanced degrees like masters or PhDs. Sets of questions were developed for three groupings of interviewee identities: academia, industry, and HR professionals. Interview question sets were selected depending on which group best matched the role of the interviewee. 

All interviews have been anonymized for the protection of participants who shared critical thoughts about institutions, policies, and cultural elements in Italy. Select individuals who allowed their names or institutions to be included are acknowledged in the acknowledgements section. 

The transcripts and recordings from these interviews were analysed using inductive thematic analysis, manually coded along the following themes: academia, collaborations, finance, gender, geopolitics, leadership, talent, and quality of life. An additional set of codes related to integration, Milan, and the North-South divide were added after initial analysis to capture repeated themes. 

Data Validation and Limitations 

We tested the Revelio gender classifying algorithm for precision by randomly selecting 100 people to check whether the gender identified by Revelio matched online career platform profiles. In this test, we could not confirm 12% of the sample, noting the classifying algorithm was trained using American assumptions around names and perceived gender, not always applicable in other countries (e.g., Andrea generally being a man's name in Italy but a woman's name in the US). 

Our data may miss individuals due to outdated online profiles or profile deletion. The seniority metric combines information about current job (including title, company, and industry), job history (duration of previous employment and seniority of past positions), and age to generate individual scores averaged into a continuous seniority metric, then converted to seven ordinal levels from Entry Level to Senior Executive Levels. 

We also used the country of an individual’s undergraduate degree serves as a proxy for their origin, based on the assumption that most people pursue their early education in their country of origin. This method is generally reliable, as seen in these OECD data cases, especially with Italy having a lower percentage of international undergraduates (4%).