The Influence of Artificial Intelligence on the Willingness to Pay for Digital Newspaper Subscriptions with Special Focus on Prompt Engineers

However, readers are still very skeptical about the use of artificial intelligence in news media. Even more dramatic: they punish the use of AI with a massively lower willingness to pay. For example, the willingness to pay for online news drops by 30 percent when AI is used to research, process or create news.

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Author

Brand Science Institute

Published

January 08, 2024

Views

2565

Content

What results were generated?

Implications of low willingness to pay through AI

Opportunity for publishers through AI

Tapping sales potential through AI

Users also differentiate between the extent to which AI is used for news production. Depending on whether artificial intelligence is used merely as an aid or for the fully automated creation of news and who operates the AI, the willingness to pay even falls by up to 33% depending on the type of AI used.

What results were generated?

General results

20% of respondents are generally willing to pay for online news
Increasing news consumption does not go hand in hand with a greater willingness to pay for online news.
The average willingness to pay among respondents is EUR 10.24, which is significantly lower than the average market price of EUR 17.38 for a monthly digital news subscription.
Respondents who have paid for online news in the last 12 months generally have a 15% higher willingness to pay.

Results on willingness to pay AI models

Among respondents who are generally willing to pay for online news, the willingness to pay for editorial content drops massively as soon as AI is used to research, process and create news.
The willingness to pay falls by up to 30% on average. Depending on the AI model used, the willingness to pay falls by up to 35%.
Among respondents who have paid for online news in the last 12 months, willingness to pay falls in the same proportion when different types of AI are used.
Familiarity and experience with AI have no influence on willingness to pay. AI amateurs and experts therefore show no difference in their willingness to pay.

Results on willingness to pay AI as a supporting tool

If AI is used as a supporting tool, the willingness to pay for content created by editors is around 10% higher than if it is created by AI experts (prompt engineers).
Confidence in the ability to develop high-quality editorial content with the help of AI is therefore attributed to editors.
The quality of the editorial articles created with the help of AI is rated higher by editors than that of Prompt Engineers in almost all areas of business, stock market & finance, science, sport, culture and politics.
Only in the area of weather do the respondents trust the prompt engineers to achieve the same high quality as editors in the AI-supported creation of news.

Results on willingness to pay AI fully automated

If AI is used for the fully automated creation of editorial content, the difference in willingness to pay between editors and prompt engineers becomes significantly smaller.
The AI expertise to create specific prompts is more appreciated by respondents in the context of fully automated and AI-generated content
Here too, however, the editor tends to generate a higher willingness to pay.

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Implications of low willingness to pay through AI

The use of AI represents a process innovation for publishers that can be used both to improve quality and reduce costs in the creation of journalistic content.

However, the survey results show that the quality improvements that can be achieved with AI, such as improved quality of journalistic content, better data and trend analysis, differentiated views and perspectives of big data evaluations, real-time monitoring of news and personalized content, are not appreciated with a higher willingness to pay.

On the contrary, there is a significantly lower willingness to pay for all content created with the help of AI or fully automated using AI.

A possible and possibly even legally enshrined labelling obligation for editorial content created with AI or with the help of AI thus poses a potential threat to publishers, as it would significantly jeopardize their earnings potential and the earnings gain generated by AI and, in case of doubt, would overcompensate for it.

However, the potential of this threat depends on the extent to which publishers use AI to reduce costs in the creation of editorial content. If the cost-cutting potential exceeds the declining willingness to pay, the use of AI can still be attractive.

Opportunity for publishers through AI

However, mandatory labeling of editorial content created with AI or with the help of AI also creates opportunities for publishers, as labeling leads to a differentiation of editorial and journalistic content, in which human-generated content is significantly upgraded from the customer's point of view compared to AI-generated content.

This results in a quality advantage and new revenue potential for publishers, particularly in comparison to traditional online portals and large tech companies,

which are thus able to better exploit the increased willingness to pay for explicitly humane editorial services in the upper price segment.
At the same time, publishers have the opportunity for the first time to skim off the lower willingness to pay in the lower price segment for content created using AI, which could not previously be skimmed off under previous cost and price structures

By means of product and price differentiation brought about by AI, publishers and media brands thus have the opportunity to specifically siphon off willingness to pay with new AI-generated media products under their existing media brands and thus address different and new customer groups with a low willingness to pay.

Tapping sales potential through AI

In this way, the diversity of the media offering can be increased and publishers have the opportunity to work in areas where it was previously not possible to offer media for cost reasons.
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Depending on willingness to pay and cost-cutting potential, three main revenue models are conceivable for publishers:

A: Comparatively high subscription prices in the premium segment with human-generated content
B: Comparatively low subscription prices in the lower price segment with content created with the help of AI
C: Pure advertising financing of fully automated and AI-generated content if it can achieve a correspondingly high reach

In the third revenue model in particular, the use of AI offers publishers and media companies the opportunity to compete more effectively with online portals such as T-Online, Watson or Google and Microsoft, among others, and possibly even to realize upselling potential for their own premium offerings.
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Online portals would not have this opportunity for upselling due to the presumably greater use of AI there, which means that the labeling obligation in this case could mean a clear advantage for publishers and strong media brands.

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