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Title page 1

Contents 5

Foreword 4

Executive summary 7

1. Introduction 9

Generative AI: a transformative technology for SMEs? 9

Survey methodology 9

Brief literature review 11

References 15

Notes 16

2. How are SMEs using generative AI? 17

Which SMEs are using generative AI? 17

What are SMEs using generative AI for? 21

Generative AI helps SMEs achieve more by improving employee performance 25

References 27

Notes 29

3. How is generative AI impacting SMEs' skill and labour needs? 30

Generative AI helps SMEs compensate for labour and skill shortages 30

Generative AI reduces staff workload 34

Generative AI reduces SMEs' reliance on external contractors 35

Yet generative AI has little effect on overall staff need 36

SMEs associate generative AI with increased skill needs 37

References 39

Notes 40

4. Are SMEs prepared for generative AI? 42

The most common barrier to using generative AI is that it is not suited to the work the SME does 42

A small minority of SMEs report an unfavourable attitude towards generative AI 44

Some SMEs are taking measures to prepare workers to use generative AI in a trustworthy manner 45

References 49

Notes 51

Tables 6

Table 1.1. Descriptive statistics - number of surveys completed 10

Table 1.2. Descriptive statistics - composition of the weighted sample 11

Table 2.1. Illustrative examples of generative AI by sector 24

Table 4.1. The main barrier to using generative AI varies by country 43

Figures 5

Figure 1.1. AI use increases with company size 12

Figure 1.2. Natural language generation use among SMEs 13

Figure 2.1. SMEs' use of generative AI is highest in the information and communication sector 19

Figure 2.2. One-person companies are half as likely to use generative AI as the largest SMEs 20

Figure 2.3. SMEs' generative AI use is the highest in Germany and the lowest in Japan 20

Figure 2.4. Generative AI is mostly used for peripheral rather than core activities 22

Figure 2.5. Generative AI is used more for simple, one-off and trivial tasks than for complex, recurring and important tasks 23

Figure 2.6. Generative AI is used the most in marketing and sales 24

Figure 2.7. SMEs in all countries see enhanced performance as the main benefit of generative AI 25

Figure 2.8. Small SMEs are often more positive than larger SMEs on the benefits of generative AI 27

Figure 3.1. Large SMEs are most likely to report a labour shortage or skill gap 31

Figure 3.2. Some SMEs report that generative AI helps compensate for labour shortages and skill gaps 32

Figure 3.3. SMEs in Japan are most likely to say that generative AI helps compensate for labour and skill shortages 33

Figure 3.4. One-person businesses are most likely to report that generative AI has decreased workload 34

Figure 3.5. Generative AI reduces SMEs' reliance on external contractors and staff workload 35

Figure 3.6. Most SMEs report generative AI has had no effect on overall staff need 36

Figure 3.7. Twice as many SMEs associate generative AI with increased skill needs as with decreased skill needs 38

Figure 3.8. Generative AI has made data analysis and interpretation skills more important, along with other skills 39

Figure 4.1. The most common barrier to using generative AI is that it is not suited to the work the company does 43

Figure 4.2. Most SMEs have either a favourable or neutral attitude towards generative AI 45

Figure 4.3. Where SMEs use generative AI, employees' participation in AI-related training is not common 47

Figure 4.4. Austrian SMEs using generative AI are the most likely to have conducted research on copyright, legal or regulatory issues 48

Figure 4.5. SMEs using generative AI in Germany are the most likely to have guidelines in place 49

Boxes 10

Box 1.1. How respondents were recruited for the survey 10

Box 1.2. Connections between this survey and the 2025 OECD D4SME Survey 14

Box 2.1. How do the estimates of generative AI use reported in this survey compare to estimates from national statistical offices? 18

Box 2.2. What is driving lower use of generative AI among Japanese and Korean SMEs? 21

Box 2.3. There is uncertainty around the size of efficiency gains due to generative AI 26

Box 4.1. What risks related to copyright, data protection, and legal and regulatory issues are associated with generative AI? 46

출판사 책소개

알라딘제공
This report examines the potential for generative AI - tools that generate text, images, video or audio, such as ChatGPT, Copilot and Midjourney - to help SMEs address labour and skill needs. It presents evidence from a representative 2024 OECD survey of over 5 000 SMEs in Austria, Canada, Germany, Ireland, Japan, Korea and the United Kingdom, on how SMEs use generative AI, how its use may be helping to address labour and skill needs, and how SMEs are preparing employees to use generative AI. The survey shows that generative AI is in use in 31% of SMEs. SMEs report that generative AI improves performance, helps compensate for skill gaps and labour shortages, and increases the need for highly-skilled workers. SMEs have concerns about copyright, legal and regulatory issues, though negative attitudes towards generative AI are rare. The findings highlight the promise of generative AI but also the need for structured policy support to close digital and skills gaps between SMEs and larger firms and to ensure that any gains from generative AI are broadly shared across the economy and the workforce.

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