Europe is currently facing significant skills gaps across various sectors of the economy, as highlighted in the recent EU report on the Future of European Competitiveness. This isn’t entirely unexpected, especially as the rapid advancement of technology, particularly in AI, places increasing pressure on organizations to modernize. For those in leadership roles like Chief Data & AI Officers (CDAO) or Data & AI Literacy Leads, addressing this challenge is to stay competitive on a global scale, especially as organizations in the US and China continue to push forward.
This issue is compounded by demographic shifts, such as a declining labor force, and a growing demand for both low- and high-skilled workers. The problem is particularly pronounced in STEM fields, where supply lags far behind demand. The urgency to address these skill shortages in Europe is clear, especially as projections for 2035 indicate even more pronounced labor shortages in high-skilled, non-manual occupations.
“Around 42% of Europeans lack basic digital skills”Right now, European organizations are underperforming in adult learning. This hinders the possibility for professionals to adapt to advanced technologies in data & AI. Participation in adult education and training is relatively low overall and varies significantly across the EU. For example, only 37% of adults participated in training in 2016, and this rate has hardly increased since. To achieve the target of having at least 60% of adults participating in training every year set by the 2020 European Skills Agenda, some 50 million more workers would need to receive training. Some European corporates believe they can simply update the e-learning they developed a few years ago. The EU report gives a clear recommendation here: organizations need to become more responsive to changing skill needs and skill gaps. Curricula need to be continuously evaluated based on effectiveness and completely revised. Collecting reliable, granular, and comparable information about skill gaps in your organization is important for aligning your workforce with the strategic goals of your business. Understanding where the gaps exist allows you to focus your data and AI literacy investments on the areas that matter most, maximizing the return on your training efforts. It also empowers employees to perform at their best, fostering higher productivity and satisfaction. As technology continues to transform industries, staying competitive means having a workforce that is not only proficient but confident in using data and AI tools. Platforms like Workera and Techwulf are helping organizations achieve this by offering advanced assessments that provide a detailed picture of current skill levels. These platforms enable organizations to map their skill gaps with precision and create personalized learning paths that directly address the needs of their teams.
“The key driver of the rising productivity gap between the EU and the US has been digital technology (“tech”) – and Europe currently looks set to fall further behind”Europe has long faced a productivity gap compared to the US and parts of Asia, where faster adoption of technology and innovation has driven higher economic output. This gap is particularly evident in the effective use of emerging technologies like AI. However, not all is lost in the report is stated that we still have the potential to carve out a leading position in selected segments. However, we do need to make sure that we can leverage it effectively. Currently, AI makes the European worker rather anxious; almost 70% of respondents in a recent survey favoured government restrictions on AI to protect jobs. To achieve this, organizations need to prioritize AI and data literacy programs that empower employees with the skills to leverage these new tools effectively. By doing so, they not only enhance individual productivity but also strengthen Europe’s competitiveness in the global economy. By investing in lifelong learning, you can enable your professionals to enhance what they do—instead of being replaced. Don’t limit yourself to only the data organization or only existing employees. And keep in mind that some groups might need extra attention. In short – we have a job to do.