Dutch AI monitor 2024

Summary

Chapter 1 Introduction

The term artificial intelligence (AI) describes machine-based systems that can, based on the inputs provided, infer how to generate output for specific purposes. AI is an example of a systems technology, and in this sense can be compared with electricity or the internal combustion engine. AI has been high on the agenda of policymakers in recent years. Any new technology with the potential significance of AI demands systematic, ongoing monitoring. The current report is another step towards the development of a national AI monitor. It reports on the development of methods for creating new statistics, but it also provides (preliminary) figures. The report focuses on companies that produce AI, companies that use AI, educational programmes that focus on AI and how these are feeding through into the labour market, and the demand for workers with AI skills. The research was commissioned by TNO (the Netherlands Organisation for Applied Scientific Research) and also represents a contribution to the monitoring activities of the AiNed programme.  

Chapter 2 Use of AI by businesses

  • Statistics Netherlands’ survey of ICT Usage in Enterprises includes questions regarding the use of seven AI technologies by businesses in sectors C to N and Q that have 10 or more employees. The seven technologies are: machine learning, service robots or autonomous vehicles, robot-assisted process automation, speech recognition, image recognition, text mining and natural language generation.
  • In 2024, 23 percent of companies with ten or more employees made use of one or more of the AI technologies listed. This represents an increase of nearly 8 percentage points since 2023.
  • Companies that use AI technology accounted for more than half (51 percent) of the total revenue of companies in the Netherlands in 2024.
  • In 2024, among companies that used AI technology, it was used most widely for marketing and sales (36 percent) and administrative processes or management tasks (30 percent).
  • The most common way in which companies obtained AI technology in 2024 was the direct use of commercially available software.
  • Among those companies which, in 2024, had considered adopting AI technology at some point, but which were not currently using it, ‘lack of experience’ was by far the most commonly given reason for this (75 percent).

Chapter 3 Companies that produce AI technology

  • In order to ascertain the number of companies in the Netherlands produce AI technology, a method based on machine learning was developed to differentiate ‘AI companies’ from ‘non-AI companies’ by analysing the text on their websites.
  • ‘AI system’ was defined using the definition of the OECD. An ‘AI company’ was defined as ‘a company whose principal activity is the production of AI systems’.
  • By applying this method, we produced a set of 450 websites belonging to 402 AI companies with a presence in the Netherlands that were active in 2024.
  • Of the AI companies identified in 2024, 97 percent were small and medium-sized enterprises, defined as companies with fewer than 250 workers.
  • Most AI companies are active in sector J, the Information and Communications sector (63 percent).
  • Most AI companies were limited liability companies (83 percent)
  • The provinces with the most AI companies were Noord-Holland (32 percent) and Zuid-Holland (24 percent). 5 percent of the companies identified were subsidiaries of companies based abroad.
  • In 2023, the majority of AI companies (43 percent) had a turnover of between 100 thousand euros and one million euros. AI companies often have higher than average revenues compared with other companies in the Netherlands.
  • Among AI companies with at least one worker, the majority (85 percent) had a turnover of less than 5 million euros in 2022. A small proportion (5 percent) had a turnover of over 50 million euros. The remainder (10 percent) had a turnover of between 5 and 50 million euros.
  • The majority of AI companies with at least one worker (81 percent) had operating expenses of less than 5 million euros in 2022. Around 7 percent had operating expenses of more than 25 million euros. The remainder (13 percent) had operating expenses of between 5 and 25 million euros.
  • This research method is still under development, and therefore these figures remain provisional.

Chapter 4: Educational programmes featuring AI

  • Statistical information on educational programmes that focus on AI (e.g. numbers of current students and graduates) is produced by identifying - using existing data on educational programmes - which programmes have AI as their core focus (‘AI-narrow’), and programmes in which AI forms one aspect, but is not the core focus (‘AI-broad’, which includes all AI-narrow programmes).
  • Students enrolled in AI-narrow programmes were a very small proportion (4-7 percent) of the total number of AI students (AI-broad).
  • The number of students enrolled in AI-broad programmes increased by 23 percent between 2018/’19 and 2022/’23. The number of students in AI-narrow programmes doubled between 2018/'19 and 2023/'24.
  • AI-broad programmes had a total of nearly 104 thousand students enrolled in the 2023/’24 academic year.
  • Within AI-broad, programmes concerning ‘information technology general’ had the most students in 2023/'24 (34 thousand), followed by programmes on ‘marketing, commercial economics’ (21 thousand students).
  • In AI-narrow programmes, the share of women was around 22 percent during the period studied. The majority of students were enrolled in Bachelor’s or Master’s programmes.
  • In higher education, 128 thousand international students were enrolled in the 2023/’24 academic year: 18 thousand in AI-broad and 2,500 in AI-narrow.
  • Choices around how to define which educational programmes focus on AI affect the numbers greatly. Because this definition remains under development, these figures on AI study programmes remain provisional.

Chapter 5 Position of students leaving AI-related programmes in the labour market

  • We looked at students who had left a study programme that includes AI (i.e. a programme where AI is at least one aspect of the programme, even if it is not the only focus of the programme), and how they fared in the subsequent years.
  • The number of students leaving AI study programmes in the academic years 2018/'19 to 2022/'23 ranged between around 15 thousand (2019/’20 academic year) and nearly 22 thousand (2022/’23 academic year).
  • Around two-thirds (67 percent) of them left with an AI diploma. In the case of ‘AI-narrow’ programmes (i.e. programmes where AI is the core focus), the share was 73 percent.
  • Women were more likely to graduate with an AI diploma from an AI programme (77 percent) than men (63 percent).
  • Most of the almost 16 thousand graduates from AI programmes in the 2018/'19 academic year (with or without diplomas) found employment immediately. Self-employment or living on welfare were rare, and remained so for the first four years after leaving such a study programme.
  • Students who leave with a degree from an AI study programme were most likely to find employment in the information and communication sector, specialised business services sector or trade sector. Those leaving without a degree from an AI study programme were mainly employed in trade (particularly in supermarkets) and in renting/leasing and other business services (particularly for temporary employment agencies).
  • Among international students leaving AI study programmes, 26 to 29 percent found employment in the Netherlands, but the majority left the Netherlands.
  • The majority of workers who had left an AI study programme in the previous four years earlier were working 35 hours or more.
  • Choices around how to define which educational programmes focus on AI affect the numbers greatly. Because this definition remains under development, these figures on students leaving AI study programmes remain provisional.

Chapter 6 Demand for workers with AI skills

  • In order to understand the demand for workers with AI skills, we assessed the effectiveness and feasibility of a method that, using job vacancies and modelling, can distinguish AI vacancies from non-AI vacancies.
  • An ‘AI vacancy’ was defined as ‘a job vacancy involving the use or production of AI systems (based on the OECD definition). One criterion is therefore that the job, as described in the job vacancy, can only be done by a person with (in-depth) knowledge of AI systems.’
  • Various models were trained using a manually labelled set of AI vacancies and non-AI vacancies. The best-performing model was a machine learning model using tf-idf encoding.
  • This model was applied to a dataset of 7.5 million online job ads, which produced a set of 8,725 AI job ads in the period 2018-2024.
  • An increase in AI vacancies can be seen over the period 2018 to 2022, with a peak at the beginning of 2022. After this, the number of vacancies drops, and remains stable at around 430 per quarter.
  • The total number of AI vacancies between Q1 2018 and Q2 2024 was highest in the provinces of Noord-Holland (2,770), Zuid-Holland (1,435) and Noord-Brabant (1,205).
  • Among AI vacancies, the five most common occupational groups are: systems analyst; statistical and mathematical specialists; software developers; professors and other teaching staff in higher education; and managers in the field of information and communication technology.
  • The most common industrial sectors for companies with AI vacancies are: education; information and communication; specialist business services; trade; and manufacturing.
  • The 10 organisations with the most AI vacancies to their name advertised 2,000 AI vacancies during the period studied. Of these, seven were universities in the Netherlands.
  • This research method is still under development, and therefore these figures on AI vacancies remain provisional.