Intesa Sanpaolo’s Early Retirement Program and the Fear of AI Replacement

Intesa Sanpaolo, one of Italy's largest banking groups, has announced its generational change strategy by planning 9,000 staff exits by 2027, with 7,000 in Italy and 2,000 in international subsidiaries. As per the bank this will be effectuated “at no social cost”. This initiative aligns with the Group's focus on technological transformation and future sustainability. In Italy, an agreement with trade union delegations outlines a path for voluntary exits and upskilling initiatives aimed at enhancing digital capabilities and adapting to new professional roles. The plan includes 4,000 voluntary exits through retirement or the Solidarity Fund, and hiring 3,500 young employees by June 2028, with a focus on bolstering Wealth Management and customer services.

“Upskilling is integral to redefining the purpose and structure of work. By investing in substantial training programs, institutions like Intesa Sanpaolo can set a precedent that turns AI into a partner in the process of economic and social evolution. ”

The strategy anticipates significant cost savings of approximately €500 million annually from 2028, despite an initial charge of €350 million in 2024. The new hires, which will be in addition to the 4,600 planned under the 2022-2025 Business Plan, are intended to sustain growth and adapt the business model to a digital and AI-focused environment. The exits in international subsidiaries will mainly affect central functions without impacting commercial roles. This approach maintains the Group's commitment to innovation and supports its projected net income of over €8.5 billion for 2024.

The challenge here is not solely about facilitating smooth transitions but about ensuring that progress remains human-centric, addressing the capabilities and freedoms people need to participate meaningfully in a rapidly transforming economy.

AI and Human Development

Intesa Sanpaolo’s strategic program for generational change underscores a significant societal tension between economic efficiency and human agency. The planned 9,000 exits—though voluntary and occurring at no social cost—illustrate the shifting contours of labor markets where AI and digital processes increasingly take precedence over human labor. This trend reflects an age-old question about the purpose of economic progress: if it is merely to replace humans with automated systems, society risks eroding the intrinsic value of work as a source of self-worth and identity.

If we shift our perspective to view AI not as an adversary but as an ally, Intesa Sanpaolo’s program can be seen as a pivotal moment to harness technological growth as a means of enhancing human freedom and economic well-being. By integrating AI into the workforce thoughtfully, the framework shifts from one of replacement to one of augmentation. In such a framework, upskilling becomes essential—not as a defensive strategy but as a proactive approach to equip individuals with the tools to thrive alongside technology, expanding both their professional opportunities and personal capabilities.

Upskilling is integral to redefining the purpose and structure of work. By investing in substantial training programs, institutions like Intesa Sanpaolo can set a precedent that turns AI into a partner in the process of economic and social evolution.

Such an approach fosters an environment where AI complements human efforts, allowing the labor force to adapt and grow without succumbing to the fears of obsolescence. This can reshape the discourse from one of labor displacement to one of collaborative enhancement, ensuring that technological innovation becomes a channel for empowerment rather than exclusion.

A notable example of a multinational firm successfully integrating AI as an ally rather than a replacement for human labor is Siemens. The German engineering giant has embraced AI and digitalization not as tools for cutting jobs but as means to enhance the skills and productivity of their workforce. Through their comprehensive “Siemens Learning Campus” initiative, the company has invested in continuous employee education focused on digital skills, AI literacy, and advanced technical knowledge. This approach has enabled Siemens to foster a workforce that is better equipped to manage and collaborate with AI systems, resulting in higher efficiency, innovation, and job satisfaction.

“By integrating AI into the workforce thoughtfully, the framework shifts from one of replacement to one of augmentation. In such a framework, upskilling becomes essential—not as a defensive strategy but as a proactive approach to equip individuals with the tools to thrive alongside technology, expanding both their professional opportunities and personal capabilities.”

By viewing AI as a complement to human capabilities, Siemens has shown that investment in upskilling leads to sustainable growth and resilience. Employees have transitioned from routine, automatable tasks to more complex roles that emphasize critical thinking and creative problem-solving. This model of collaboration between AI and human labor has strengthened Siemens' competitive edge while maintaining job security and promoting a culture of lifelong learning. The company’s strategy illustrates how an inclusive approach to technological integration can enrich both business performance and human development, reinforcing the idea that AI, when harnessed properly, can serve as a catalyst for enhancing human potential.

The Heckscher-Ohlin (H-O) Model: A Framework for Reallocation

One of the most unforgettable lessons I’ve carried from my time studying international economics under Professor Jaime de Melo at the University of Geneva is the Heckscher-Ohlin (H-O) model. This model, etched into my memory due to the grueling 864-page textbook and one of the toughest exams I have ever taken, provides a framework for understanding how resources—labor and capital—are allocated based on comparative advantage.

Extrapolating the H-O model to today’s AI-driven world, we can see AI as a form of capital that fundamentally shifts how resources are deployed. Economies need to adapt by reallocating labor to sectors where human skills still hold a comparative advantage. This reallocation does not signal the end of employment or economic decay; rather, it presents an opportunity for growth and stability when approached strategically.

AI as a Capital-Intensive Force

AI functions as a form of capital, automating routine, repetitive tasks that once required human labor. Industries such as manufacturing, logistics, and data processing are increasingly AI-dominated. This shift can initially displace workers, but as the H-O model suggests, labor does not simply vanish—it moves to sectors where it remains essential.

When AI displaces jobs, it propels a natural shift in labor toward industries that thrive on uniquely human qualities. Creativity, empathy, and complex problem-solving become critical assets in sectors such as healthcare, education, and creative industries. These areas will absorb displaced workers, aligning perfectly with the H-O model’s principle that labor reallocates to maintain productivity.

Upskilling and Specialization

The key to harnessing this shift lies in upskilling. Workers displaced by AI must be equipped with new skills that enable them to operate within or adjacent to their current industries. For example, in the finance sector, while AI may automate routine data analysis, it allows human employees to focus on strategic initiatives and complex decision-making. As workers enhance their skill sets, their productivity—and consequently their income—increases.

In this framework, salaries not only remain intact but have the potential to expand. As workers become more skilled and productive, their earnings grow. The H-O model’s emphasis on comparative advantage reinforces the idea that economies can thrive when labor is channeled into sectors that maximize its unique capabilities.

However, this positive outcome hinges on one essential factor: upskilling. Workers displaced by AI must be equipped with the skills necessary to transition into roles that leverage human strengths, such as strategic thinking and advanced problem-solving. In finance, for instance, AI may handle data analysis, but human employees can focus on interpretation and strategic planning. Enhanced skill sets translate into greater productivity and potential income growth, strengthening economic resilience.

Governments, educational institutions, and private enterprises must therefore prioritize investments in training programs that foster adaptability and continuous learning. Without such commitments, the workforce risks stagnation and decline. The H-O model emphasizes that economies flourish when labor is channeled into sectors that maximize its unique capabilities—a goal achievable only through robust upskilling efforts.

The fear surrounding AI’s impact on the workforce is valid, but it need not result in fatalistic conclusions. With strategic upskilling, the labor force can pivot to collaborate with AI, ensuring that economies remain dynamic and human-centric. Upskilling is not merely a response; it is the linchpin of an economically vibrant future.