Short answer

Designers and brand managers can confidently explore AI tools for generating brand voice content, knowing that disclosure does not inherently lead to negative consumer perceptions.

Field
Innovation & Markets
Source
Journal of Product & Brand Management (2023)
Method
Experimental Design
Sample
624 participants
Evidence
Strong effect

Consumers do not perceive AI-generated brand voice as less authentic than human-written content, even when the AI source is disclosed. This innovation & markets research insight is drawn from a 2023 study published in Journal of Product & Brand Management. Using Experimental design with 624 participants, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Designers and brand managers can confidently explore AI tools for generating brand voice content, knowing that disclosure does not inherently lead to negative consumer perceptions.

Study
Innovation & MarketsRecentStrong effect

AI-Generated Brand Voice is Perceived as Authentic as Human-Written Content

Consumers do not perceive AI-generated brand voice as less authentic than human-written content, even when the AI source is disclosed.

Journal of Product & Brand Management · 2023

01

Key Findings

  • 01Text disclosed as AI-generated is not perceived as less authentic than that disclosed as human-written.
  • 02There is no negative effect on brand voice authenticity and brand attitude when an AI source is disclosed.
02

Application

Design takeaway

Designers and brand managers can confidently explore AI tools for generating brand voice content, knowing that disclosure does not inherently lead to negative consumer perceptions.

How to apply

When developing marketing copy, product descriptions, or chatbot responses, consider using AI tools and transparently disclose their involvement to consumers.

Project actions

  • 01When exploring AI in your design project, consider how you will communicate its use to potential users or stakeholders.
  • 02Investigate how different levels of AI involvement (e.g., AI-assisted vs. fully AI-generated) might influence perceptions.
03

Method & Evidence

AimTo investigate how disclosing AI as the source of brand voice affects consumer perceptions of brand authenticity and brand attitude.
MethodExperimental Design
ProcedureParticipants were presented with marketing texts from Adidas that were either disclosed as AI-generated, human-written, or not disclosed. Their perceptions of brand voice authenticity, brand authenticity, and brand attitude were then measured.
Sample624 participants
ContextMarketing and Brand Management

Variables

IV["Disclosure of AI source (AI-generated, human-written, not disclosed)"]
DV["Brand voice authenticity","Brand authenticity","Brand attitude"]
CV["Brand (Adidas)","Type of marketing text"]
04

Strengths & Limitations

Strengths

  • +Experimental design allows for causal inferences.
  • +Large sample size increases statistical power.

Limitations

The study's findings might differ for highly sensitive or personal communication channels.

Reliability & validity

The use of a controlled experimental design and a substantial sample size likely contributes to good reliability and validity. However, the specific measurement instruments for authenticity and attitude would need to be examined for their psychometric properties.

Think critically

To what extent does the specific AI model used and the complexity of the communication task influence consumer perception of authenticity?

05

Design Principles

"Transparency in AI-driven brand communication does not diminish perceived authenticity."

This finding challenges assumptions about consumer skepticism towards AI in branding. It suggests that transparency about AI usage in content creation, such as product descriptions or chatbot interactions, does not negatively impact perceived brand authenticity or consumer attitude.

06

What This Means for Your Design

It's okay to tell people if a computer wrote your brand's messages – they still think it's authentic.

How to use in your project

  • 1.Reference this study when discussing the ethical considerations and user perception of AI-generated content within your design project.
07

Add to My Project

08

Quick Cite

Paragraph starter

Research by Kirkby, Baumgarth, and Henseler (2023) indicates that consumers do not perceive AI-generated brand voice as less authentic than human-written content, even when the AI source is disclosed. This suggests that brands can be transparent about their use of AI in communication without negatively impacting consumer perception of authenticity or brand attitude, offering potential for efficiency gains.

09

Source

Journal of Product & Brand Management

To disclose or not disclose, is no longer the question – effect of AI-disclosed brand voice on brand authenticity and attitude

journal · 2023

View source

Questions About This Research

What does the research say about ai-generated brand voice is perceived as authentic as human-written content?
Designers and brand managers can confidently explore AI tools for generating brand voice content, knowing that disclosure does not inherently lead to negative consumer perceptions. Evidence: Journal of Product & Brand Management (2023).
Why does "AI-Generated Brand Voice is Perceived as Authentic as Human-Written Content" matter for design?
This finding challenges assumptions about consumer skepticism towards AI in branding. It suggests that transparency about AI usage in content creation, such as product descriptions or chatbot interactions, does not negatively impact perceived brand authenticity or consumer attitude.
How can designers apply this research?
Designers and brand managers can confidently explore AI tools for generating brand voice content, knowing that disclosure does not inherently lead to negative consumer perceptions.
What were the main findings?
Text disclosed as AI-generated is not perceived as less authentic than that disclosed as human-written.. There is no negative effect on brand voice authenticity and brand attitude when an AI source is disclosed.
What research method was used?
Experimental Design with 624 participants.
How strong is the evidence?
Evidence strength is rated Strong effect, based on a 2023 journal from Journal of Product & Brand Management.
What should I do differently in my next project?
When developing marketing copy, product descriptions, or chatbot responses, consider using AI tools and transparently disclose their involvement to consumers.
What are the limitations?
The study focused on a specific brand (Adidas) and a student demographic, which may limit generalizability to other brands or broader consumer populations.