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Annex: Summary of impact responses

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Generally, the levels of engagement with the impact aspects of our calls for evidence were low and limited impact evidence was provided.

Across the five calls for evidence, the overall balance of sentiment around the impact of our regulatory position was inconclusive. The majority (35, 39%) of respondents indicated that our regulatory approach would result in both costs and benefits for organisations. 

However, for our positions on lawful basis, purpose limitation and accuracy of training, the net anticipated impact was positive excluding those who were unsure.

The main benefits identified that the proposals would result in improved regulatory certainty for their organisation (39 respondents) and public trust in the adoption of generative AI models (30 respondents). 

The majority of respondents that identified costs highlighted that the proposals would result in increased:

time costs of understanding and implementing the regulatory approach (20 respondents);

costs associated with making changes to organisations’ business models (10 respondents); and 

resource costs associated with people exercising their information rights (seven respondents).

Overview 

In developing our policy position, it is important to consider whether regulatory action is proportionate and not unduly burdensome on those that we regulate. Through the calls for evidence, we have collected impact responses from those we regulate to ensure our final policy positions are informed and evidence-based. 

Overview of impact respondents 

We received 192 responses from organisations and 22 from members of the public. Respondents could submit evidence through an online survey link or by email. Of the total respondents, approximately 100 answered the impact-related questions in some form. Of these:58

  • 16 respondents were developers of generative AI;
  • 14 respondents were suppliers of generative AI;
  • 24 respondents were current users of generative AI;
  • 32 respondents were potential users; and 
  • 33 respondents were advisors to organisations using or developing generative AI. 

Figure 1 below shows the breakdown of respondents across the five calls for evidence. 

Figure 1: Which of the following describes your organisation?59

This figure shows a bar chart that provides a breakdown of the types of respondents to each chapter of the consultation. It shows that for the first chapter on lawful basis, the total number of respondents that answered the impact questions in the survey was 44, of which six were suppliers of generative AI, 14 were advisors to organisations developing or using generative AI, nine were developers of generative AI, seven were current users of generative AI, while 18 identified as ‘Other’, and 12 as potential users of generative AI. For the second chapter on purpose limitation, 17 respondents answered the impact questions in the survey. Two of these were suppliers of generative AI, seven were advisors to organisations developing or using generative AI, two were developers of generative AI, five were current users of generative AI, while seven respondents identified as ‘Other’ and a further seven identified as potential users of generative AI. For the third chapter on accuracy, a total of 11 respondents answered the impact questions. Of these, two were suppliers of generative AI, five were advisors to organisations developing or using generative AI, two were developers of generative AI, three were current users of generative AI, and four identified themselves as ‘Other’, while five identified as potential users of generative AI. For the fourth chapter on individual rights, a total of 15 respondents answered the impact questions. Of these, two were advisors to organisations developing or using generative AI, four were current users of generative AI, eight identified as ‘Other’ and four were potential users of generative AI. For the final chapter on controllership, 13 respondents answered the impact questions. Of these, three were suppliers of generative AI, three were advisors to organisations developing or using generative AI, three were developers of generative AI, four were current users of generative AI, while four identified as ‘Other’ and three identified as potential users of generative AI.

Source: ICO analysis

58 Multiple responses were permitted. 

59 Totals do not add to total sample size as multiple answers were permitted.