The Rise of the AI Influencer: What the Research Tells Marketing Practitioners
Influencer marketing has been one of the most powerful tools in the digital marketer's arsenal for the past decade. But the influencer landscape is changing in a way that many practitioners have not yet fully reckoned with. Artificial intelligence is no longer just a tool that human influencers use to create content. AI is producing the influencers themselves. Virtual, AI-generated personalities are now posting on Instagram, endorsing products, and building followings of millions. This week's evidence draws on five peer-reviewed studies to examine what AI influencers are, how consumers respond to them, and what practitioners and business owners need to understand to make effective decisions in this rapidly evolving space.
What Is an AI Influencer and Why Do They Work?
The foundational study in this field comes from Thomas and Fowler (2021). Their research was among the first to rigorously test whether AI influencers (computer-generated personalities) that interact with and influence consumers on social media could produce the same brand benefits as traditional human celebrity endorsers. Across two experimental studies, they found that AI influencers can indeed generate positive brand outcomes comparable to those of human endorsers, including favourable brand attitudes and purchase intentions.
This finding was significant because it challenged the assumption that the effectiveness of influencer marketing depended on a real human being behind the account. Consumers, it turns out, can form meaningful parasocial connections with AI-generated personalities in ways that translate into genuine commercial outcomes for endorsed brands.
However, Thomas and Fowler (2021) also identified a critical risk. Consumers are less likely to perceive AI influencers as unique individuals as they would a human celebrity. This means that when an AI influencer behaves negatively or is involved in a transgression, consumers tend to generalise that negative behaviour to all AI influencers rather than treating it as an isolated incident. The brand damage from an AI influencer controversy can therefore be broader and more difficult to contain than the equivalent situation with a human endorser. For practitioners, this has immediate strategic implications: the risk management considerations for AI influencer partnerships are structurally different from those for human influencer partnerships.
What Drives Consumer Trust in AI Influencers?
Understanding what makes consumers trust an AI influencer is the central question for any practitioner considering this channel. Sands, Campbell, Plangger and Ferraro (2022), conducted two empirical studies comparing consumer responses to AI and human social media influencers. Their findings show that in some ways, an AI influencer can be as effective as a human influencer, and they identify a notable spill-over effect from consumers' prior experiences with other AI recommendation systems. Consumers who are already comfortable with AI-driven recommendations, such as those from Netflix or Amazon, show greater openness to AI influencer recommendations. This suggests that as AI literacy grows across the population, the effectiveness of AI influencers as marketing vehicles is likely to increase.
Alboqami (2023) identifies the specific combinations of factors that drive high levels of consumer trust in AI influencers. The research found that no single factor is sufficient to generate trust on its own. Instead, trust emerges from configurations that combine source attractiveness including physical attractiveness and homophily, meaning how similar the influencer feels to the consumer with source credibility, including authenticity and perceived expertise, and congruence across three dimensions: fit between the influencer and the product, between the influencer and the consumer, and between the product and the consumer.
The configurational finding is particularly valuable for practitioners because it shifts the question from "is this AI influencer credible?" to "does this AI influencer, this product, and this audience form a coherent and trustworthy combination?" A highly attractive AI influencer with strong aesthetic credentials will not necessarily build trust for a product that feels incongruent with their persona or distant from the interests and values of the target audience.
The Attributes That Shape Effectiveness
Feng, Chen and Xie (2024) developed a validated AI Influencer Attributes Scale that identifies and quantifies the key attributes through which AI influencers shape consumer attitudes, trust, and perceived influencer-product fit. Their research identifies that humanlike attributes, specifically the perceived attractiveness, intelligence, interactivity, and anthropomorphism of the AI influencer are the primary drivers of consumer receptivity.
The research found that AI influencers' humanlike appearances have a positive impact on consumers' message reception. The more convincingly human an AI influencer presents not just visually, but in terms of their apparent intelligence, responsiveness, and personality that the more favourably consumers respond to their endorsements. This finding has direct implications for how practitioners should evaluate and select AI influencer partners: the quality and sophistication of the AI influencer's humanlike presentation is not merely an aesthetic consideration but a commercial one.
A Surprisingly Practical Finding: The Role of Colour
One of the most practically actionable findings in this week's research comes from Chan, Septianto, Kwon and Kamal (2023). This study analysed 6,132 Instagram posts from ten AI influencers and conducted two experimental studies to examine how colour features in AI influencer content affect consumer responses to product recommendations.
The findings are clear: warm colours in AI influencer posts generate more favourable consumer responses than cool colours, with brightness significantly moderating this effect. The underlying mechanism operates through perceived warmth and emotional trust. Warm-coloured content makes the AI influencer feel more emotionally approachable and trustworthy, which in turn increases the effectiveness of their product recommendations.
This is a finding that practitioners and creative teams can act on immediately. For brands working with AI influencers, the colour palette of sponsored content is not merely a design preference. It is a variable that measurably affects how consumers emotionally process and respond to the recommendation. Warm, well-lit imagery is not just aesthetically appealing; according to the evidence, it actively builds the emotional trust that makes AI influencer endorsements more commercially effective.
Practical Recommendations for Marketing Practitioners and Business Owners
The collective evidence from these five studies points to a coherent and actionable framework for any practitioner considering AI influencers as a marketing channel.
• Evaluate AI influencer fit across three dimensions. Trust in AI influencers depends on congruence between the influencer, the product, and the consumer. Before partnering with an AI influencer, rigorously assess whether their persona, audience, and content style genuinely align with your brand and your target customers. A mismatch on any of these dimensions undermines the trust that makes the partnership commercially valuable.
• Prioritise humanlike attributes when selecting AI influencer partners. Perceived attractiveness, intelligence, interactivity, and anthropomorphism are the primary drivers of consumer receptivity to AI influencer endorsements. Evaluate potential AI influencer partners on these dimensions, not just on follower count or aesthetic appeal.
• Manage transgression risk proactively. Negative behaviour by an AI influencer tends to be generalised to all AI influencers by consumers. This means that a controversy involving your AI influencer partner carries a broader reputational risk than the equivalent situation with a human influencer. Build clear contractual and monitoring frameworks around AI influencer partnerships and have contingency plans in place.
• Use warm colour palettes in sponsored AI influencer content. When briefing AI influencer content for product recommendations, specify warm, well-lit imagery. The research shows this increases perceived warmth and emotional trust, which measurably improves the effectiveness of the endorsement.
• Factor in your audience's AI familiarity. Finding suggests that audiences already comfortable with AI-driven recommendation systems such as streaming platforms, e-commerce recommendations will be more receptive to AI influencer endorsements. Assess your target audience's AI literacy and adjust your expectations and communications accordingly.
References
• Alboqami, H. (2023). Trust me, I'm an influencer! — Causal recipes for customer trust in artificial intelligence influencers in the retail industry. Journal of Retailing and Consumer Services, 72, 103242.
• Chan, K. W., Septianto, F., Kwon, J., & Kamal, R. S. (2023). Color effects on AI influencers' product recommendations. European Journal of Marketing, 57(9), 2290–2315.
• Feng, Y., Chen, H., & Xie, Q. (2024). AI influencers in advertising: the role of AI influencer-related attributes in shaping consumer attitudes, consumer trust, and perceived influencer–product fit. Journal of Interactive Advertising, 24(1), 26–47.
• Sands, S., Campbell, C. L., Plangger, K., & Ferraro, C. (2022). Unreal influence: leveraging AI in influencer marketing. European Journal of Marketing, 56(6), 1721–1747.
• Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: use of AI influencers as brand endorsers. Journal of Advertising, 50(1), 11–25.
