The EU has one of the strongest research and development sectors in the world. However, in the area of AI and machine learning, the EU is lagging behind countries such as the USA, China, and the United Kingdom[1]. One of the main reasons for this lag is that the EU workforce does not have as many AI specialists, and such specialists are fundamental for capitalizing on the many opportunities AI and related technologies can provide a society and economy.[2] The EU lacks skills in key innovative technologies, including those associated with IoT devices and enabling technologies, namely in AI, and robotics, cyber security, and big data and analytics[3]. Indeed, data shows that graduates trained in AI related skills will migrate to countries where employment opportunities for AI are better, perhaps unsurprisingly, the USA and China. The fact that AI specialists are in short supply is a well-documented fact and needn’t be revisited at length here. What is of interest however is to consider the question: why it is so difficult to provide more AI education opportunities in the EU and its member states?

While of course many initiatives are no doubt underway to address the challenges to teaching AI discussed here, this article aims to highlight and summarise key challenges areas for teaching AI. We also provide some insights into the types of approach and ideas which could be implemented to address those challenges.

Unmet demand for AI and related skills amongst students

The reality of the current situation is that the demand for programmes teaching AI and related skills far outstrips the supply of said educational programmes. As such there is certainly room for educational institutions to invest in developing more programmes to fill the gap. At the bachelor level in particular there is unmet demand for places in these types of studies suggesting that there is untapped human capital potential in the EU. Between 2019 and 2020, The EU’s Joint Research Council (JRC) indicates that between 2019 and 2020 at the bachelor level, the unmet demand for AI constituted some 273,300 places, 53,300 places for high performance computing (HPC) studies, 159,300 for cybersecurity (CS), and 213,400 places for data science (DS) courses. At the master level the unmet demand constituted 150,400 places for AI, 33,200 places in HPC, 59,100 places in CS, and 167,000 places in DS.[4] These statistics demonstrate there is a huge demand for these study areas. The JRC also posits that the unmet demand for such study areas is in part due to the lack of properly qualified teaching staff in these high-tech study areas.

Key challenges to teaching AI skills

Drawing on work conducted by Technopolis on AI education programmes and on the EU innovation dependence with China, we identify a number of key issues which make teaching AI a challenge. These include:

While there are many education institutions across Europe teaching or starting to teach AI, AI related skills, and the application of AI in particular sectors, the unmet demand for teaching programmes remains. Given the challenges above it may well be that we must reflect on different ways of designing educational programmes and consider how higher educational institutions can become better equipped to teach AI.

Possible steps to increase the supply of AI education programmes

While the above discussion sketches some very real challenges to teaching AI, steps are being taken across the EU with member states implementing practices and new approaches to address them. Some possible steps include:

[1] IT Chronicles, (2019), The AI Skills Shortage,

[2] Cedefop, (2019), Building a Better Working Europe – Cedefop Seminar, 25 June 2019, available at: .

[3] Cedefop, (2019), Building a Better Working Europe – Cedefop Seminar, 25 June 2019, available at: .

[4] JRC, (2020), Estimation of supply and demand of tertiary education places in advanced digital profiles in the EU, available at: .

[5] JRC, (2020), Estimation of supply and demand of tertiary education places in advanced digital profiles in the EU, available at:

[6] NL AIC, (2020), NL AIC Trainingsplatform, .

[7] An example is the Kickstart AI initiative, an educational course on AI established by a several large Dutch enterprises, including Phillips, KLM, ING Bank, Ahold Delhaize and the National Railservice (NS):

[8] An example from the UK is the new National AI Centre in Tertiary Education in the UK being set up by non-profit Jisc in collaboration with UK innovation universities to amongst others, assess AI teaching approaches and to promote effective approaches. .

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