AI threatens authenticity yet boosts creativity in traditional arts

Ever wondered how artificial intelligence (AI) is reshaping the world of traditional art? A new study, “The Impact of Artificial Intelligence on Traditional Art Forms: A Disruption or Enhancement?”, published in the Indian Journal of Computer Science and Engineering, offers a detailed look at whether AI threatens artistic authenticity or enriches creative practices.

Submitted in arXiv, the paper explores both disruption and enhancement, presenting evidence from visual arts, performing arts, crafts, and cultural heritage. It raises pressing questions about job displacement, plagiarism, and creative homogenization, while also showing how AI can democratize access, boost productivity, and preserve heritage.

Is AI a disruptor to traditional art forms?

The research outlines multiple ways AI disrupts long-standing artistic practices. The most visible concern is the diminished sense of authenticity. AI-generated works, though visually striking, are often seen as lacking the cultural depth and emotional resonance tied to human experience. Critics argue that art is more than aesthetics - it is a reflection of lived struggle, context, and intentional communication.

The study also brings to light the ethical dilemma of plagiarism and consent. Generative AI tools are trained on vast datasets of artworks, often without the permission of original artists. This raises legal and moral concerns over intellectual property and the misuse of artists’ unique styles. Lawsuits have already surfaced, with creators challenging the unauthorized use of their works to train AI systems.

Another disruption is the decline in perceived artistic value and skill. When audiences learn that a piece was AI-assisted, they may assign it lower value, undermining the human contributor. The ease of producing high-quality results with minimal training may also discourage emerging artists from pursuing rigorous skill development.

Job displacement represents a further challenge. Creative roles in illustration, concept design, and music are at risk as AI increasingly produces first drafts or complete works at lower cost and faster speed. Industry estimates suggest that hundreds of thousands of jobs in entertainment and design could be disrupted in the coming years. Beyond job losses, the risk of cultural stagnation looms. Because AI generates outputs from past data, it tends toward imitation rather than bold innovation, potentially reinforcing familiar styles instead of fostering originality.

Can AI enhance creativity and cultural preservation?

Alongside its disruptive potential, the study highlights how AI can enhance art when used as a creative partner. Artists report higher productivity when incorporating AI tools, with the ability to experiment with more ideas in less time. Text-to-image systems, for example, allow visual artists to prototype rapidly, while composers and choreographers can use AI as a muse to expand creative boundaries.

AI also democratizes artistic participation, lowering barriers for people without formal training. Someone can generate a painting from a text prompt or create music from a simple melody. This widens access, allowing more voices and perspectives to contribute to artistic expression. Similarly, AI tutors for dance and other performing arts deliver personalized feedback, bringing high-quality training to students in remote or underserved regions.

The study also points to new hybrid art forms, where human imagination and algorithmic output combine. Choreographers, for instance, are using AI-generated movement patterns to inspire innovative performances. Visual artists are blending human intention with algorithmic variation to create pieces that neither could have achieved alone.

In addition, AI offers important tools for cultural heritage. Restoration projects use computer vision to reconstruct damaged murals or predict original colors. Machine learning models help analyze calligraphy styles, digitize archives, and revive fading traditions. These applications underscore AI’s role in both preserving and reinterpreting culture through a contemporary lens.

On the economic side, AI has spurred new professional opportunities, from AI art curators to prompt engineers. While automation removes some roles, it also creates demand for expertise at the intersection of art and technology. Artists adept at using AI can scale their work, diversify income streams, and engage in cross-disciplinary collaborations that were previously out of reach.

What challenges and future directions lie ahead?

Integrating AI into the arts poses serious technical, ethical, and socio-economic challenges. Technically, AI lacks true creativity and intentionality. It generates patterns from data but cannot replicate the cultural or autobiographical meaning of human-made works. Limitations in precision and bias in training data also risk misrepresenting artistic traditions. High costs and energy demands further restrict access, particularly for smaller studios and artists in developing countries.

Ethically, unresolved issues include copyright, ownership, consent, and cultural appropriation. Current legal frameworks struggle to address works with significant AI involvement. Without reform, human creators may be disadvantaged, while corporations profit from exploiting artistic data. There are also growing concerns about AI replicating sacred or culturally specific motifs without context or permission.

Socio-economic impacts are equally pressing. The widespread adoption of AI could worsen inequality in the art world, favoring well-resourced organizations while marginalizing small creators. Overproduction of AI-generated content may also devalue original human works, leading to market saturation. Some communities and competitions have already banned AI submissions to preserve human-only creative spaces.

Moving ahead, the authors recommend human–AI collaboration models, emphasizing AI as a partner rather than a replacement. They call for clear ethical guidelines, including consent frameworks, attribution standards, and potential compensation mechanisms for artists whose works inform AI training. Equal access to AI tools must also be prioritized to prevent widening disparities.

The study further urges cultural institutions to champion human artistry. Exhibitions could present AI and human works side by side, reinforcing the unique emotional and cultural depth of human creativity. Certification systems or human-only grants may also protect the value of traditional art in an AI-driven era.

Furthermore, long-term studies on AI’s impact across different art forms can inform policy and education, while successful case studies should be shared widely as models of responsible integration.