Artificial intelligence capital stock in Europe, UK, USA and Japan 1995 - 2020

Following (Rimmington et al., 2018), we target the EUKLEMS & INTANProd database data on capital stocks, categorized by SIC code and country, including software, databases, computer hardware, and machinery. From their definition of AI, we measure four distinctive AI capital stock categories:
1. Data and equipment: computing equipment, communication equipment and compute software and databases, chained linked volumes (2015), millions of national currencies.
2. Research and development: chained linked volumes (2015), millions of national currency.
3. Intangible assets: organizational capital, brand, industrial design, chained linked volumes (2015), millions of national currency.
4. Skills: training, labor compensation for NACE_R2 Computer programming, consultancy, and information service activities and NACE_R2 Education, chained linked volumes (2015), millions of national currency.
Building on our methodology, we get a closer proxy for AI stock using the data from (Bontandini et al., 2023) and (Rimmington et al., 2018) approach. We improve them to get more reliable and exact AI stock measurements using four AI dimensional coefficients. The AI dimensional coefficients approach we develop here builds on AI intensify coefficient applied to calculate AI investments (Evas et al., 2022).
We derive four AI dimensional coefficients following (Evas et al., 2022) analysis of AI investments in the EU. These coefficients will enable us to calculate the AI net stock per country accurately.
1. AI dimensional coefficient 1 (AI1): number of AI economic players / GDP in billion € (ratio). For details, see G2: AI player intensity (Righi et al., 2021),
2. AI dimensional coefficient 2 (AI2): number of AI players in AI R&D / GDP in billion € (ratio). For details, see R1: AI players in AI R&D (Righi et al., 2021),
3. AI dimensional coefficient 3(AI): University places with AI content in the EU(Bachelor and master level) / GDP in millions € (ratio). For details, see S6: University places with AI content in the EU (Righi et al., 2021). Data for the USA, UK, and Japan for AI dimensional coefficients AI3 were derived using (OECD.AI, 2023),
4. AI dimensional coefficient 4 (AI4): AI investments in the EU in million € / GDP in billion €, (ratio). For details, see G6: AI investments in the EU (Righi et al., 2022). Data for the USA, UK, and Japan for AI dimensional coefficients AI4 were derived using - venture capital investments in AI start-ups (OECD.AI, 2023).
We have developed and implemented AI dimensional coefficients (AI1 - AI4) to improve the accuracy of data analysis. Our revised data is presented as follows: Total revised AI net capital stock = AI data and equipment net capital stock x (AI1) + AI research and development net capital stock x (AI2) + AI skills stock net x (AI3) + AI net intangible assets stock x (AI4).