Navigating the challenges in advanced digital skills
At the Digital Skills EU Days 2025, the panel “Navigating the challenges in advanced digital skills | Insights & impact” moderated by our Founder & CEO Tanya Suárez with Michele Tuccio from OECD and David Timis from Generation, offered a counter-intuitive, human-centered roadmap for navigating these changes.
Why technology alone can’t build tomorrow’s leaders
One of the most striking messages came when the panel confronted a question that haunts many business leaders: why invest in training employees when AI can boost productivity immediately? While the short-term logic of deploying AI seems unassailable, the experts argued that focusing solely on technology is strategically shortsighted. AI can solve immediate problems, but it cannot build the next generation of leaders.
As David Timis (Generation) puts it, “Yes, you might be fine the next three to five years by just deploying AI, but who will be your next directors and leaders?” Michele Tuccio (OECD) echoed this concern, highlighting that without investment in human capital, companies cannot create the internal pipelines necessary for future managers. Firms that combine AI adoption with staff training, he noted, see twice the productivity gains compared to those that focus on technology alone. He also pointed to a cautionary example: an Australian consulting firm’s AI-generated government report contained numerous “hallucinations” and fake citations, illustrating that human oversight remains critical.
Taking your career into your own hands
The discussion also sent a clear message to employees: don’t wait for your employer or government to provide training. David emphasised the importance of proactive learning, in an era where digital tools are widely accessible and often free, taking control of your own learning journey is not just an option, it’s essential. Those who act early position themselves to benefit most from the productivity gains AI can deliver.
Europe advantage in the global AI landscape
Europe’s role in the global AI landscape emerged as another central theme. While the continent lags behind the US and China in producing foundational AI models (3 compared to 20 in China) panellists argued that Europe’s path to leadership lies elsewhere. Its real strengths are in applying AI responsibly, establishing robust governance, and leveraging strong social safety nets.
As David explained, the AI race “will not be won by the country developing the frontier models, it will be by the country which applies AI and disseminates or distributes the benefits widely.” This perspective reframes the competition: Europe may not create the most models, but it can set the standard for ethical, practical, and socially beneficial AI deployment.
Teaching Ai ethically and responsibly
The panel also addressed the evolving role of universities. Some institutions have resisted generative AI, with proposals to ban its use entirely. David argued that this is the wrong approach, rather than shielding students from AI, universities should teach them to use it ethically and responsibly. Michele offered practical steps, including micro-credentials, dual education programs, and multi-stakeholder partnerships between academia, tech companies, and NGOs. By combining academic rigor with real-world application, universities can prepare students for the challenges of a rapidly changing job market.
Strategic adoption over technical supremacy
The panel concluded on an optimistic, yet purposeful note. The future of work, they argued, is not about competing for technical supremacy but about strategic, human-centred adaptation. Leaders must adopt a long-term vision for talent development, individuals must take ownership of their learning, and Europe can lead by pioneering responsible application of AI within robust ethical and social frameworks. As the discussions emphasised, the ultimate goal is to build a fair, inclusive, and prosperous society. The question for all of us is clear: given that the future is as much about leadership, ethics, and societal impact as it is about coding or AI, where will you focus your learning journey?