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AI Don’t Like It! Investigating the Barriers to Implementation of AI Influencers

XLRI Jamshedpur et al.

AIS Transactions on Human-Computer Interaction2025https://doi.org/10.17705/1thci.00219article
AJG 2ABDC A
Weight
0.37

Abstract

AI influencers, also known as virtual influencers, refer to computer-generated digital characters that have gained a large social media following in recent years. These computer-generated entities perform similar tasks to human influencers, such as promoting products, engaging with followers, and building online communities. Despite not being real individuals, AI influencers have become trusted tastemakers in various niches and offer companies various advantages, such as lower costs, greater content control, and more personalized content delivery. However, AI influencers have not yet achieved widespread adoption and face significant challenges. We used the fuzzy analytical hierarchy process (FAHP) method to identify and classify the various factors that impede organizations from adopting AI influencers using a multi-stakeholder perspective. We identified seven primary barriers and 38 subbarriers. We performed a sensitivity analysis to confirm our approach’s robustness.

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https://doi.org/https://doi.org/10.17705/1thci.00219

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@article{xlri2025,
  title        = {{AI Don’t Like It! Investigating the Barriers to Implementation of AI Influencers}},
  author       = {XLRI Jamshedpur et al.},
  journal      = {AIS Transactions on Human-Computer Interaction},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.17705/1thci.00219},
}

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AI Don’t Like It! Investigating the Barriers to Implementation of AI Influencers

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.