The AI Techno-Economic Segment Analysis

The Techno-Economics Segment (TES) analytical approach aims to offer a timely representation of an integrated and very dynamic technological domain not captured by official statistics or standard classifications. Domains of that type, such as photonics and artificial intelligence (AI), are rapidly evolving and expected to play a key role in the digital transformation, enabling further developments. They are therefore policy relevant and it is important to have available a methodology and tools suitable to map their geographic presence, technological development, economic impact, and overall evolution. The TES approach was developed by the JRC. It provides quantitative analyses in a micro-based perspective. AI has become an area of strategic importance with potential to be a key driver of economic development. The Commission announced in April 2018 a European strategy on AI in its communication "Artificial Intelligence for Europe", COM(2018)237, and in December a Coordinated Action Plan, COM(2018)795. In order to provide quantitative evidences for monitoring AI technologies in the worldwide economies, the TES approach is applied to AI in the present study. The general aim of this work is to provide an analysis of the AI techno-economic complex system, addressing the following three fundamental research questions: (i) Which are the economic players involved in the research and development as well as in the production and commercialisation of AI goods and services? And where are they located? (ii) Which specific technological areas (under the large umbrella of AI) have these players been working at? (iii) How is the network resulting from their collaboration shaped and what collaborations have they been developing? This report addresses these research questions throughout its different sections, providing both an overview of the AI landscape and a deep understanding of the structure of the socio-economic system, offering useful insights for possible policy initiatives. This is even more relevant and challenging as the considered technologies are consolidating and introducing deep changes in the economy and the society. From this perspective, the goal of this report is to draw a detailed map of the considered ecosystem, and to analyse it in a multidimensional way, while keeping the policy perspective in mind. The period considered in our analysis covers from 2009 to 2018. We detected close to 58,000 relevant documents and, identified 34,000 players worldwide involved in AI-related economic processes. We collected and processed information regarding these players to set up a basis from which the exploration of the ecosystem can take multiple directions depending on the targeted objective. In this report, we present indicators regarding three dimensions of analysis: (i) the worldwide landscape overview, (ii) the involvement of players in specific AI technological sub-domains, and (iii) the activities and the collaborations in AI R&D processes. These are just some of the dimensions that can be investigated with the TES approach. We are currently including and analysing additional ones.JRC.B.6-Digital Econom

THE 2020 PREDICT REPORT Key Facts Report: An Analysis of ICT R&D in the EU and Beyond

The 2020 PREDICT Key Facts Report provides a detailed analysis of the state of ICT R&D activities in the EU28 and 12 further economies worldwide. This is the 13th edition of a series that is published annually. Like the previous editions, an online version is available at: https://ec.europa.eu/jrc/en/predict. The report covers the period between 1995 and 2017, providing a long-term analysis of the European Union (EU) ICT sector and its R&D, covering a whole cycle from the initial expansion years, to the double recession that began in early 2008, and the most recent evolution up to 2017. Whenever possible, the report includes nowcasted data for 2018 and 2019. The statistical information provided by the figures allows the comparison between: the ICT sector and the total economy; the ICT manufacturing sector and the ICT services sector; the four ICT manufacturing sectors, two ICT services sectors, and MC and RS sectors; EU countries; the EU and the international context (including the most relevant countries in the world economy). The report focuses especially on the ICT R&D macroeconomic dynamics.JRC.B.6-Digital Econom

The techno-economic segment analysis of the Earth observation ecosystem

This report analyses the worldwide landscape of the Earth observation ecosystem to identify opportunities, synergies, and obstacles that need to be addressed to foster the development of a vibrant space data economy in Europe. The report uses the Techno-Economic Segment (TES) analytical approach to provide a holistic view of the EO and geospatial ecosystem in Europe and worldwide through the identification of players and key clusters of activities. It also takes into consideration the potential flows of knowledge resulting from shared activities, locations and technological fields. The approach adopts a micro-based perspective considering a wide range of both horizontal and segment specific data sources. The outcome is a compelling characterisation of the key features of this very dynamic ecosystem. The TES EO ecosystem shows a very diverse global landscape with three distinguished global hubs, namely EU28, China and the US, as possible incubators for EO-linked innovation. Those hubs have the largest number of players in case of R&D and well as in case of industry. Nevertheless, the distribution of EO activities and concentration of those activities look quite different in the three leading macro areas. As far as the R&D activities are considered, the EU28 has the highest overall number of players involved in the all types of R&D activities, but scores quite low if only the patents are taken into account. Out of the three big players, the US has the smallest number of players involved in the overall EO R&D and stable position in number of patenting. In case of China, the largest number of R&D activities is concentrated in hands of relatively few players. In conclusion, the findings of this report confirm a general expectation about the growth in the EO downstream segment. However, up to 2017 the growth has not been staggering. Since 2017, there have been continuous policy efforts to increase the uptake of EO data in order to enable market growth.JRC.B.6-Digital Econom

Academic Offer of Advanced Digital Skills in 2019-20. International Comparison: Focus on Artificial Intelligence, High Performance Computing, Cybersecurity and Data Science

This work aims at supporting policy initiatives to ensure the availability in the EU27 of an adequate education offer of advanced digital skills in the domains of artificial intelligence (AI), high performance computing (HPC), cybersecurity (CS) and data science (DS). The study investigates the education offer provided in the EU27 and six additional countries: the United Kingdom, Norway, and Switzerland in Europe, Canada and United States in America, and Australia, with a focus on the characteristics of the detected programmes. It analyses the number of programmes offered in these domains, considering the distinction based on programme’s scope or depth with which education programmes address the technological domain (broad and specialised), programme’s level (bachelor programmes, master programmes and short courses), as long as the education fields in which these programmes are taught (e.g. Information and communication technologies, Engineering, manufacturing and construction, Business, administration and law), and the content areas covered by the programmes. The analysis is conducted for each technological domain separately, first addressing the features of the overall education offer detected in the countries covered by the study, and followed by an in-depth analysis of the situation in the EU27. Among the many results that this work provides, those associated to the most relevant insights can be listed as follows. First of all, the main role in the offer of advanced technological skills is held by the US, which leads in terms of number of programs provided in almost all combinations of technological domain, scope and level. Secondly, another important player is the UK, with a very consistent offer of bachelor and master degree programs (in both cases, the UK’s share is around 25% of the total offer detected). The consequences of the Brexit have, therefore, to be considered and faced also in terms of the education offer of advanced technological skills in the EU27. Thirdly, the role of the EU27 is notable but more varying (depending on the combination of domain, scope and level of programmes) than that of the UK. Regarding more specific aspects related to the EU27 offer, we detect a good amount of programmes offered in the domain of DS. As this domain is found out to be remarkably associated to the field of education of Business, Administration and Law, this is a positive finding suggesting a good supply of competences that are suitable to economic activities of various types. Therefore, what observed for the EU27 suggests a good alignment between the offer and the demand of DS-related skills. In the EU27 we observe a large share of programmes belonging simultaneously to both DS and AI. Considering the relatively high offer in DS, and the fact that AI is currently a techno-economic domain that is attracting a lot of attention and of private and public resources, a consistent connection between these two domains can be considered as an important key to favour synergies and future economic growth. Additionally, we find DS programmes quite widespread among the fields of education, which may facilitate the role of DS as a vehicle to further introduce AI, HPC and CS in the fields of education barely addressing these technological domains. We also observe a relatively large offer of AI master degree programmes in the EU27, which is an important finding given the role of this education level in the provision of competences for the workforce. Finally, it is important to note that we detect potential elements of weakness in the EU27’s education offer related to CS. These competences are increasingly crucial to prevent and fight cyber-related incidents, concerning both private and public spheres. Therefore, the detection of a relatively modest CS education offer (in comparison to other geographic areas) is a point that deserves attention. Many other findings are described throughout this report, but what discussed in this abstract has to be retained as the most relevant content aimed at supporting EU policies.JRC.B.6-Digital Econom

Estimation of supply and demand of tertiary education places in advanced digital profiles in the EU: Focus on Artificial Intelligence, High Performance Computing, Cybersecurity and Data Science

In order to investigate the extent to which the education offer of advanced digital skills in Europe matches labour market needs, this study estimates the supply and demand of university places for studies covering the technological domains of Artificial Intelligence (AI), High Performance Computing (HPC), Cybersecurity (CS) and Data Science (DS), in the EU27, United Kingdom and Norway. The difference between demand and supply of tertiary education places (Bachelor and Master or equivalent level) in the mentioned technological domains is referred in this report as unmet students’ demand of places, or unmet demand. Demanded places, available places and unmet demand are estimated for the following dimensions: (a) the tertiary education level in which this demand is observed: Bachelor and Master or equivalent programmes; (b) the programme’s scope, or depth with which education programmes address the technological domain: broad and specialised; and (c) the main fields of education where this tuition is offered: Business Administration and Law; Natural sciences and Mathematics; Information and Communication Technology (ICT); and Engineering, Manufacturing and Construction, with the remaining fields grouped together in a fifth category. From these estimations, it is concluded that the number of available places in the EU27, at Bachelor level, reaches 587,000 for studies with AI content, 106,000 places offered in HPC, 307,000 places in CS and 444,000 places offered in the domain of DS. At Master level this demand is comparatively lower, except for the DS domain, were it equals the offer at bachelor level. DS outnumbers AI in demand of places at Master level, with 602,000 and 535,000 demanded places, respectively. The unmet demand for AI, HPC, CS and DS in EU27 at MSc level is approximately 150,000, 33,000, 59,000 and 167,000 places, respectively. At BSc level, the unmet demand reaches 273,000, 53,000, 159,000 and 213,000 places, respectively. Another finding is that the unmet demand for broad academic programmes is higher than for specialised programmes of all technological domains and education levels (Bachelor and Master). Higher availability of places for AI, HPC, CS and DS domains is found for academic programmes taught in the ICT field of education, both at Bachelor and Master levels. For Bachelor studies, Germany and Finland are estimated as the countries with the highest unmet demand in AI, HPC, CS and DS, either with a broad or specialised scope. United Kingdom is the only studied country offering places for all fields of education and technological domains at Bachelor level and Master level. For Master studies, this is also found in Germany, Ireland, France and Portugal.JRC.B.6-Digital Econom

AI Watch : AI Uptake in Health and Healthcare, 2020

This document presents a sectoral analysis of AI in health and healthcare for AI Watch, the knowledge service of the European Commission monitoring the development, uptake and impact of Artificial Intelligence for Europe. Its main aim is to act as a benchmark for future editions of the report to be able to assess the changes in uptake and impact of AI in healthcare over time, in line with the mission of AI Watch. The report recognises that we are still at an early stage in the adoption of AI and that AI offers many opportunities in the short term for improved efficiency in administrative and operational processes and in the medium-long term for clinical applications, patients’ care, and increased citizen empowerment. At the same time, AI applications in this sensitive sector raise many ethical and societal issues and shaping the direction of development so that we can maximise the benefits whilst reducing the risks is a key issue. In the global context, Europe is well positioned with a strong research base and excellent health data, which is the pre-requisite for the development of beneficial AI applications. Where Europe is less well placed is in translating research and innovation into industrial applications and in venture capital funding able to support innovative companies to set themselves up and scale up once successful. There are however noticeable exception as the case of the BioNTech that is leading the development of one of the COVID-19 vaccines. It should also be noted that in AI-enabled health start-ups, many of them are in the area of drug discovery, i.e. the domain of BioNTech. Investment in education and training of the healthcare workforce as well as creating environments for multidisciplinary exchange of knowledge between software developers and health practitioners are other key areas. The report recognizes that there are many important policy developments already in the making that will shape future directions, including the European Strategy for Data which is setting up a common dataspace for health, a riskbased regulatory framework for AI to be put in place by the end of 2020, and the forthcoming launch of the Horizon Europe programme as well the Digital Europe Programme with large investments in AI, computing infrastructure, cybersecurity and training. The COVID-19 crisis has also acted as a booster to the adoption of AI in health and the digital transition of business, research, education and public administration. Furthermore, the unprecedented investments of the Recovery Plan agreed in July 2020 may fuel development in digital technologies and health beyond expectation. We are therefore at the junction of a potentially extraordinary period of change which we will be able to measure in future years against the baseline set by this report.JRC.B.6-Digital Econom