Interview Of The Week

Interview Of The Week: Eric Hazan, AI & The Future Of Work Expert

Eric Hazan is a senior partner with McKinsey & Company, where he co-leads the global strategy practice. He is active in the growth, marketing, and sales practice as well as the digital practice in Western Europe. With a strong focus on digital transformation, Hazan specializes in helping companies with strategic challenges, particularly in the retail, consumer goods, and tech sectors. He is also a member of the McKinsey Global Institute Council, offering insights that shape MGI’s business, economic, and technology research. Hazan has contributed to numerous McKinsey research programs, including recent studies on artificial intelligence and Generative AI, and the use of technology for the common good. He has also co-authored several reports on the future of work and the influence of the Internet and ICT on the economy. Prior to joining McKinsey, Hazan was a Senior Partner at Arthur D. Little, where he led the global telecoms, Internet, media, and entertainment practice and the consumer practice. He started his career in marketing and sales in consumer goods at Kraft Jacobs Suchard and at Danone.  Hazan, a speaker at the VivaTech conference in Paris on May 22nd, holds a Master of Science degree in management from HEC Paris, where he is a professor of business strategy. He recently spoke to The Innovator about the findings of McKinsey’s report “A New Future For Work: The Race To Deploy AI and Raise Skills in Europe And Beyond” which was released at the conference.

Q: What are some of the key points raised in the report?

EH: We are at a tipping point. The report talks about how up to 30% of the work hours both in the U.S. and in Europe will be automated by 2030, and even more than 45% by 2035. This is beginning to be really, really significant. If we want to reap the benefits of this technology and see the kind of productivity growth we had in the 1970s then we need to both deploy AI rapidly and reskill massively the workforce. If we don’t then we won’t reap the benefits of AI and GenAI and there will be social impact. This is equally true for Europe and the U.S. Embracing the path of accelerated technology adoption with proactive worker redeployment could help Europe achieve an annual productivity growth rate of up to three percent through 2030. However, slow adoption and slow redeployment would limit that to 0.3 percent, closer to today’s level of productivity growth in Western Europe. What’s more slow worker redeployment would leave millions unable to participate productively in the future of work and would not permit to face the current issue of talent shortage in the U.S.. and in the EU.

Europe has experienced a long-term productivity slowdown, with productivity growth almost steadily decreasing since the 1960s In addition to its divergence in productivity growth relative to the United States, Europe’s competitiveness is also waning. Despite its inclusive and sustainable growth model, Europe is behind the U.S on multiple key metrics, such as return on invested capital, revenue growth, capital expenditure, and R&D. Initial delays in Europe in technology development and adoption help explain this gap, as Europe did not benefit from the information communications and technology–driven productivity advancements that have occurred in the U.S. since the 1990s. Our previous research indicates that Europe is behind in eight out of ten key cross-sector technologies where winner takes most effects are common, widening the gap between the two regions.

Automation technology has the potential to revive productivity, allowing not just the U.S. but Europe to solve most of today’s labor market challenges. However, there are fears in both regions that the adoption of these technologies could prove disruptive to labor markets and exacerbate the challenges of both finding requisite skills in the workforce and enabling workers to move from declining occupations into rising ones.

Q: Which occupations are in decline, and which will see rising demand?

EH: The report highlights how sectors, and jobs within sectors, will be impacted differently. For example, the adoption of GenAI in Europe’s finance sector could see a decrease in labor demand by 2030, with the largest reductions in office support and customer service roles. The shift from traditional banking to digital platforms, accelerated by the pandemic, could drive demand for STEM professionals, reflecting a strategic focus on using data to enhance customer engagement. This trend requires specialists including data scientists and software engineers, particularly as financial services companies invest in digital architecture and IT modernization. In line with these trends, approximately 600,000 individuals in banking might need to change occupations by 2030. However, the demand for professionals in STEM and management roles, which generally require higher education, would grow.

In Europe’s manufacturing sector approximately 2.1 million individuals might need to change occupations by 2030, the second-most-affected sector across all sectors. This transition would be particularly pronounced in production work because of its core role in the sector. Specialized roles in management, business, and legal professions would be less likely to undergo occupational transitions as these roles currently tend to be held by workers with postsecondary education. Demand for technological skills in the manufacturing sector is expected to increase, along with demand for social and emotional skills.

Europe’s healthcare sector is projected to experience the most significant growth in labor demand by 2030, with the potential to add approximately 3.7 million jobs. This surge would be driven primarily by rising demand for health aides and healthcare professionals, while demand for office support roles would decline because of automation and AI. Key growth drivers include an aging population and rising challenges from mental health issues and chronic diseases.

Around 500,000 healthcare workers in Europe could have to change occupations by 2030, with office support roles constituting the bulk of these transitions.

For Europe we are talking about doubling the pace of occupational transition compared with the pre-Covid period. We know in Europe that we have chosen to have an economic system closer to the needs of the citizen in terms of protection of jobs. The U.S. approach is tougher, but it enables them to adapt more easily. This is why the transition has the potential to cause more disruption in Europe. Europe can either stay where it is in terms of structure and growth or it can preempt the change, enabling people to get better paid jobs with reskilling.

Q: Will Europe also have to step up the pace of scaling AI and GenAI?

EH: Numerous factors might hinder the estimated growth of AI and GenAI in both Europe and the U.S. The integration of automation, AI, and GenAI into existing systems could take longer than expected if companies struggle to pinpoint effective applications or lack relevant workforce expertise. The costs associated with developing and deploying these technologies may escalate if there are shortages in computing power or energy resources. Another potential challenge is the sustainability of wage increases due to labor augmentation, which could impede further technological uptake. Finally, customer acceptance and other factors including social, political, or regulatory developments that we have not explicitly modeled, may need to be considered, as AI-fueled automation may require behavioral changes in some cases—for example, customers may need to accept that they will not speak to human agents during customer support calls. A perception of lacking risk management by AI suppliers could also hinder customer acceptance.

Q: What advice do you have for companies?

EH: The adoption of automation technologies will be decisive in protecting businesses’ competitive advantage in an automation and AI era. Companies must engage in proactive management to ensure rapid AI adoption and worker redeployment, including setting up training structures, supporting transitions, attracting the right talent, as well as prioritizing the development of worker augmentation technologies. To ensure successful deployment at a company level, business leaders need to establish four key priorities:

Understand the potential impact of automation technologies, notably how AI and GenAI can augment and automate work. This includes estimating both the total capacity that these technologies could free up and their impact on role composition and skills requirements. For example, one leading financial institution analyzed the current activities of its workforce and concluded that AI and GenAI have the potential to save about half of working-hours c at the company, highlighting the very significant potential workforce implications of these technologies.

Plan a strategic workforce shift: This requires sizing the workforce and skill needs, based on strategically identified use cases, to assess the potential future talent gap. From this analysis will flow details about the extent of recruitment of new talent, upskilling, or reskilling of the current workforce that is needed, as well as where to redeploy freed capacity to more value-added tasks. These kinds of strategies offer a prime opportunity to enhance operational efficiency and output growth, build trust with the workforce, and overcome some of the hurdles posed by labor shortages.

Prioritize people development. Leaders need to ensure that the right talent is on hand to sustain the company strategy during all transformation phases. This includes identifying, attracting, and recruiting future AI and GenAI leaders in a tight market, accelerating the building of AI and GenAI capabilities in the workforce; training nontechnical talent to adapt to the changing skills environment; and designing an HR strategy and operating model to fit the post–GenAI workforce. To that end, companies are increasingly setting up AI and  GenAI departments specifically to spearhead GenAI transformation efforts. These include roles focusing on strategy along with technical roles essential for executing strategies and developing future gen AI expertise across the organization.

The C-Suite Needs to Become Tech Savvy Too: Leaders need to undertake their own education journey to maximize their contributions to their companies during the coming transformation. A fundamental objective of this journey is for the C-Suite to not only reskill but also achieve a deep understanding the value of GenAI and the challenges it poses.

Q: What do you want The Innovator’s readers to take away from this interview?

EH: Europe doesn’t have a choice. If it wants to reap the productivity growth benefits of AI and GenAI, it needs to deploy the technology as fast as the U.S. while investing and improving human capital and raising the skills of its workforce. If it doesn’t do that it will experience much less growth and social turmoil. Training is the best social protection.

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About the author

Jennifer L. Schenker

Jennifer L. Schenker, an award-winning journalist, has been covering the global tech industry from Europe since 1985, working full-time, at various points in her career for the Wall Street Journal Europe, Time Magazine, International Herald Tribune, Red Herring and BusinessWeek. She is currently the editor-in-chief of The Innovator, an English-language global publication about the digital transformation of business. Jennifer was voted one of the 50 most inspiring women in technology in Europe in 2015 and 2016 and was named by Forbes Magazine in 2018 as one of the 30 women leaders disrupting tech in France. She has been a World Economic Forum Tech Pioneers judge for 20 years. She lives in Paris and has dual U.S. and French citizenship.