As a result of advancements in technology and software, the artificial intelligence (AI) has integrated into

creative industries. AI has introduced novel approaches to various aspects of dance production, including

costume design, choreographic composition, and animated dance creation. As a result, dance has extended

beyond the boundaries of live stage performance and has increasingly become integrated into virtual and digital

platforms. The creation of dance animation is a complex and multi-layered process that involves the

anthropomorphizing of non-living or virtual characters into lifelike forms. It requires the integration of full-body

movement, expressive gestures, costume design, in to rhythmic cultural and traditional way to achieve a coherent

and believable performance. The primary problem of this research is to determine whether human-created or AI-

seeks to investigate the extent to which artificial intelligence influences dance animation in terms of visual

The study concludes that AI does not replace traditional dance practices but rather expands the possibilities of

dance as a hybrid digital art form.

Keywords: Artificial Intelligence, Animation, Dance Art, Audience Engagement, Digital Creativity

As a result of an advancement in technology and software, artificial intelligence (AI) has increasingly integrated

into creative industries, transforming traditional artistic practices into hybrid digital forms. Within the field of

dance, AI has introduced innovative approaches to choreographic composition, costume visualization, motion

capture, and animated dance creation. Consequently, dance has extended beyond the boundaries of live stage

performance and has become embedded within virtual, interactive, and digital platforms.

Dance, traditionally understood as a cultural expressive art form, is deeply connected to human emotion and

to achieve coherence and believability. AI has rapidly progressed in recent years, revolutionizing fields such as

computer vision, natural language processing, and human-computer interaction. A significant frontier in this

evolution is generating human-related content, including realistic facial synthesis, expressive gestures, and

complex motion sequences (LLM Lab Org, 2025).

This study seeks to explore the comparative impact of AI-generated and human-created animated dance on

audience engagement and creative transformation. Benedikte Wallace et al., 2021 evaluated AI-generated dance

improvisation against human performances, finding that while AI models successfully mimicked certain aspects

of “dance-likeness and expressivity,” they struggled with sound-motion mappings compared to human dancers.

This study adopts a mixed-method research design to provide a comprehensive understanding of audience

perceptions of AI-generated and human-created animation in a comparative context. The integration of

quantitative and qualitative approaches enables both measurable analysis and in-depth interpretation of audience

engagement. For the purpose of this study, two categories of animated dance were selected: AI-generated

animation and human-created dance animation. For the human animation, Moana film dance has been selected.

Following the viewing sessions, questionnaires were administered to collect quantitative data. A purposive

sampling method was employed to select fifty participants who are withing the 20- 40 age limit with prior

knowledge of dance and media studies without considering gender. This ensured that participants possessed the

necessary background to critically evaluate both the technical and aesthetic aspects of the animations. Structured

questionnaires were used to collect measurable data related to visual quality, realism, emotional engagement,

thematic analysis using Nvivo identifying recurring patterns related to engagement, realism, and creative

perception.

The findings of this study reveal significant differences between AI-generated and human-created animated

dance, particularly in relation to visual appeal, emotional expression, and audience engagement. The results

indicate that 90% of participants considered human-created animation to be highly effective in enhancing visual

realism and emotional depth. In contrast, 80% of participants noted that AI-generated content demonstrated

smooth motion quality and innovative creative compositions. According to the observational findings,

participants paid greater attention to AI-generated dance animations when viewed on social media platforms.

Many participants identified AI-generated dance as a novel and visually attractive form of content compared to

artificially enhanced. Participants also emphasized that the animation effectively represented cultural traditions,

symbolic gestures, and dance movements associated with a specific cultural identity and national background.

However, in addition to its technical strengths, 85% of participants mentioned that AI-generated dance was often

perceived as lacking emotional depth. Furthermore, 90% of participants indicated that human-created dance

conveys a stronger sense of emotional authenticity, as well as cultural and traditional identity. Participants were

able to identify the country or cultural background of the performance through costume design, symbolic

difficult to modify in terms of micro-movements, including eye blinking and toe movements. Participants further

noted that making post-production changes to such detailed movements is highly challenging in AI-generated

animation.

Additionally, although AI-generated movements are technically accurate and visually refined, they often appear

emotionally neutral and less expressive when compared to human-created performances. This finding highlights

a critical distinction between computational precision and human expressiveness within artistic performance.

The study further highlights that artificial intelligence should not be viewed merely as a tool, but rather as a

collaborative creative agent. It expands the possibilities of dance by enabling experimentation with non-human

forms, generating new choreographic patterns, and bridging traditional and digital art forms. However, the

creative process remains fundamentally dependent on human input, particularly in terms of conceptualization,

living or virtual characters as dynamic dance performers. This process of anthropomorphizing non-living

characters creates visually attractive and imaginative performances that effectively capture audience attention,

particularly on digital platforms and social media environments.

The results of this study indicate that AI-generated dance animation is highly effective in enhancing visual

quality and creative experimentation. Approximately 80% of participants noted that AI-generated content

demonstrated smooth motion quality, innovative choreography, and visually refined compositions.

Observational findings further revealed that audiences paid greater attention to AI-generated dance content when

viewed on social media platforms. Participants identified AI-generated dance as a novel and visually attractive

form of content compared to traditional human-created performances, which increased its appeal within

contemporary digital viewing cultures. AI-generated animation feels believable in dance conceptualization. It is

audience reach and participation. Participants in this study emphasized that AI-generated dance content is

particularly suitable for online viewing due to its visual complexity, technological novelty, and adaptability to

digital platforms.

However, despite these technical strengths, the findings also reveal that AI-generated dance lacks the emotional

depth and authenticity associated with human-created performances. Approximately 85% of participants

mentioned that AI-generated dance often appears emotionally neutral despite its technical precision. In contrast,

90% of participants indicated that human-created dance conveys a stronger sense of emotional authenticity,

cultural identity, and traditional expression. Participants were able to identify the country or cultural background

of performances through costume design, symbolic gestures, and movement patterns. These findings suggest

that emotional engagement in dance is closely connected to human embodiment, cultural understanding, and

lived experience, which remain difficult to replicate through artificial intelligence systems (Foster, 2011).

dance elements, symbolic gestures, and cultural identity. In addition, human-created animation presented subtle

performance details such as natural eye blinking, toe and finger movements, facial expressions, and micro-

movements, all of which contributed to the realism and believability of the performance.

The study also identified substantial differences between the production processes of human-created animation

and AI-generated animation. Traditional animation involves manual keyframing, motion capture, choreographic

planning, modeling, texturing, rigging, lighting, and rendering, all guided by human creativity and artistic

intention. This process requires a deep understanding of rhythm, body movement, emotional expression, and

subtle gestures, is significantly more difficult in AI-generated animation. Participants further noted that making

post-production changes to such detailed movements remains highly challenging within AI-based workflows.

As a result, AI-generated performances often appear mechanically accurate but less expressive when compared

to human-created animation.

Another important limitation identified in this study is that AI systems depend heavily on pre-existing datasets,

which may restrict originality and creative interpretation. Unlike human artists, who create performances based

on personal experience, cultural understanding, and emotional interpretation, AI systems generate outputs

according to learned patterns and computational data. Therefore, the creative process in AI-generated dance

animation still requires substantial human involvement, particularly in conceptual development, storytelling,

emotional expression, and cultural interpretation.In terms of audience engagement, the findings indicate that AI-

generate animated dance content, thereby increasing participation within the creative industry. This demonstrates

that AI supports not only professional production practices but also emerging creators within digital creative

spaces.

In conclusion, the discussion highlights that AI-generated dance animation presents both advantages and

limitations. While artificial intelligence enhances visual quality, accessibility, efficiency, and creative

innovation, it lacks the emotional depth, authenticity, and cultural expressiveness associated with human-created

a hybrid creative approach in which human artistic expression and artificial intelligence technologies work

collaboratively to produce more engaging, meaningful, and innovative performances.