2 weeks Ago
A curious phenomenon has emerged in recent years—ordinary images and media transformed into artworks echoing the timeless charm of hand-drawn animation. Known as the “Ghibli trend,” this wave of AI-generated imagery mimics the nostalgic, emotive aesthetics of classic animation, symbolising how artificial intelligence is now capable of replicating styles once considered uniquely human. Yet the implications of this trend extend far beyond animation, affecting music, literature, design, film, and creative business alike.
This article explores how generative AI is reshaping creative industries, examines the associated risks and opportunities, and proposes forward-thinking policy measures to safeguard and enrich our cultural landscape. How AI is Transforming Creative Industries Generative AI is revolutionising the creative process across a broad spectrum of sectors. By automating routine tasks and offering innovative tools for expression, AI is redefining how art is conceived, produced, and distributed.
Animation and Visual Arts: AI tools can generate detailed backgrounds, character sketches, and even entire scenes in a style reminiscent of classic hand-drawn animation. These technologies accelerate production and expand creative possibilities by allowing artists to experiment with traditional techniques at a fraction of the time. However, this rapid reproduction of styles also raises concerns about the dilution of individual artistic signatures.
Literature and Media: In writing and journalism, AI-driven text generators assist in drafting articles, stories, and scripts, overcoming writer’s block and enabling mass production of content. This has transformed the creative process in media, with AI serving both as a co-writer and an editor. Yet questions remain about authorship, originality, and the ethical implications of mass-produced literary content.
Music: AI is now capable of composing original scores, synthesising vocals, and emulating the styles of iconic musicians. From generating ambient soundscapes to creating pop hits, AI tools are expanding the possibilities in music composition and production. While this enhances creative expression, it also challenges traditional notions of musicianship and raises concerns about the devaluation of human artistry.
Design and Creative Business: Graphic designers and marketers are increasingly leveraging AI to produce logos, branding materials, and ad campaigns with unprecedented speed. AI-driven design platforms can iterate multiple concepts in minutes, enabling creative businesses to be more agile and cost-effective. However, this efficiency might commoditise design, making it harder for uniquely talented designers to differentiate their work in a crowded market.
Films: In filmmaking, AI supports a range of tasks from pre-visualisation and storyboarding to post-production visual effects. Directors and editors can use AI to streamline the editing process, generate CGI elements, and even enhance dialogue or sound design. This integration boosts productivity but also raises questions about the authenticity of human creativity and the potential marginalisation of traditional film-making skills.
Risks to the Creative Ecosystem While the transformative potential of generative AI is vast, it also brings significant challenges that span every creative sector: Intellectual Property Erosion: AI models are trained on vast datasets of copyrighted material. This practice risks unauthorised replication of artistic styles and techniques, blurring the lines between inspiration and infringement. Without robust legal frameworks, creators may lose control over their distinctive artistic expressions, undermining the incentive to innovate.
Commodification of Artistic Style: The ease of replicating an artist’s unique style through AI reduces the exclusivity and economic value of original work. When a signature style becomes merely a filter, the market may be flooded with derivative content that lacks depth, eroding cultural appreciation for genuinely handcrafted art. Synthetic Media and Disinformation: The same technology that produces enchanting visuals can also generate hyper-realistic fake media.
AI-generated deepfakes and manipulated images risk being used to spread misinformation, potentially undermining public trust in authentic media and destabilising cultural narratives. Labour Displacement and Job Insecurity: As AI assumes routine creative tasks, professionals across sectors—be it illustrators, writers, composers, or designers—face the threat of displacement. The devaluation of human skill, especially in entry-level roles, may lead to job losses and undermine the traditional creative workforce, leaving many workers feeling undervalued and at risk of redundancy.
Homogenisation of Culture: AI systems often optimise for what is commercially successful or popular, which can lead to the overproduction of formulaic, mainstream content. This tendency risks marginalising niche and local art forms, resulting in a homogenised cultural landscape that stifles diversity and innovation. Ecological and Data Ethics Concerns: The environmental cost of training and running large-scale AI models is significant, with high energy consumption and carbon emissions contributing to ecological strain.
Additionally, the ethical implications of harvesting vast amounts of data—including personal and culturally sensitive material—without consent raise critical concerns about privacy and the equitable use of creative content. Algorithmic Bias and Cultural Misrepresentation: Generative AI models rely on extensive datasets that often over-represent mainstream narratives while under-representing minority voices. This imbalance risks perpetuating biases and homogenising creative outputs, thereby marginalising diverse artistic expressions.
Without intentional bias-correction, AI-generated content may distort cultural narratives and reinforce stereotypes in modern societies. Loss of Creative Autonomy and Overdependence on Technology: As AI becomes integral to creative workflows, there is a risk that artists over-rely on automation, reducing their unique creative input. Overdependence on technology may yield predictable, formulaic outputs, stifling innovation and devaluing traditional artistic skills, which ultimately diminishes the diversity of creative expression further.
Opportunities from Generative AI in Creative Industries Alongside these risks, generative AI offers transformative opportunities that can invigorate creative industries if embraced responsibly: New Distribution Models and Democratised Creation: AI-driven tools lower the barriers to entry, empowering creators from all backgrounds to produce high-quality content. This democratization enables independent artists and small studios to bypass traditional gatekeepers, fostering a more inclusive and diverse creative landscape. New distribution models, such as direct-to-consumer digital platforms, further empower creators to reach global audiences.
Hyper-Personalised Media Experiences: Generative AI enables content to be tailored to individual tastes, creating hyper-personalised experiences across music, literature, film, and visual art. By adapting narratives, visuals, or soundscapes in real time, AI can enhance engagement and deliver media that resonates on a personal level. This personalisation enriches audience experiences and broadens the appeal of creative works.
Cultural Memory Preservation and Revival: AI serves as a powerful tool for archiving and revitalising cultural heritage. Techniques such as AI-driven colourisation and restoration breathe new life into historical artefacts, while reconstruction algorithms can reimagine lost or damaged works. This capability ensures that cultural legacies endure, making them accessible to future generations and preserving diverse narratives for posterity.
Co-Creative Pipelines and Augmented Creativity: Instead of replacing human creativity, AI can act as a collaborative partner. Co-creative processes allow artists to generate a wealth of ideas quickly and refine them with their unique vision. This augmented creativity fosters cross-disciplinary innovation, blending human intuition with machine efficiency to produce work that is both imaginative and technically sophisticated.
Enhanced Production Efficiency and Cost Reduction: In sectors where speed and resource efficiency are paramount, AI offers significant operational benefits. Automated workflows reduce the time and cost of production, allowing creative teams to focus on high-level conceptual work. This increased efficiency can lead to faster turnaround times and lower production costs, enabling more experimental and risk-taking creative projects.
AI as Accessibility and Inclusion Technology: Generative AI has the potential to make creative expression more accessible to everyone. Assistive technologies help individuals with disabilities or limited technical skills to participate in creative endeavours. By enabling voice-command interfaces, adaptive software, and accessible design tools, AI breaks down barriers and fosters a more inclusive creative community.
Systemic Consequences of Unchecked Automation If the integration of generative AI into creative industries proceeds without careful oversight, the broader cultural landscape could suffer long-term consequences: Impoverishment of Cultural Narratives: An overreliance on AI-generated content risks reducing the diversity of cultural expressions. As AI systems tend to reinforce mainstream trends, minority voices and unconventional narratives may be sidelined, leading to a cultural monoculture that lacks depth and variety. Concentration of Cultural Power: Advanced AI development is currently dominated by a small number of large technology firms.
Their control over generative models could concentrate cultural power in the hands of a few, limiting the diversity of voices and stifling independent creative expression. This centralisation poses risks for cultural pluralism and freedom of expression. Erosion of Human Craftsmanship: The ubiquity of machine-generated content might diminish appreciation for the artisanal skill and human effort behind traditional creative processes.
As audiences become accustomed to rapidly produced, polished outputs, the labour-intensive craft of human creation may be undervalued, leading to a gradual loss of specialised artistic skills. Alienation of Audiences: A cultural ecosystem saturated with AI-generated content may leave audiences feeling disconnected from the authentic human experience. The emotional and narrative depth that comes from human creativity might be lost, prompting a backlash and a renewed desire for art that is unmistakably human in its imperfections.
Forward-Thinking Responses and Policy Proposals To harness the benefits of AI while mitigating its risks, a series of strategic interventions and policy measures are needed: Intellectual Property Reforms: Legal frameworks must be updated to address AI’s impact on copyright. New policies should clarify how copyrighted material is used in AI training and ensure that artists are fairly compensated when their work contributes to machine-generated output. This could include establishing clear guidelines around the replication of artistic styles and creating mechanisms for rights holders to opt in or out of data usage.
Provenance and Authenticity Infrastructure: Robust systems for tracking content provenance are essential. Digital watermarks, metadata tags, and blockchain-based registers can help verify the origins of creative works, ensuring that AI-generated content is transparently labelled. Such measures would facilitate proper attribution and support a fairer distribution of revenue to original creators.
Transparent Model Governance: AI developers should be required to disclose information about their training data and methodologies. Regular impact assessments and third-party audits can ensure that AI systems operate ethically and without undue bias. Transparent governance will help build trust among creators and consumers alike, paving the way for responsible AI innovation.
Artist Support and Labour Market Interventions: To counter the potential displacement of creative professionals, governments and cultural institutions should implement support mechanisms such as subsidies, tax incentives, and reskilling programmes. These measures will help artists adapt to the evolving technological landscape while preserving the cultural value of human creativity. Collective Licensing and Benefit-Sharing Models: A collective licensing framework could be established to ensure that creators receive fair remuneration for the use of their works in AI training.
Similar to systems in the music industry, this model would enable AI companies to pay royalties into a shared fund, which would then distribute compensation to the contributing artists. Such models promote a more equitable creative economy in the AI era. The emergence of the Ghibli trend is a vivid illustration of how AI is reshaping creative industries across the board—from music and animation to literature, design, and film.
While the rapid adoption of generative AI presents significant opportunities for efficiency, personalisation, and cultural preservation, it also brings profound challenges related to intellectual property, job security, and cultural homogenisation. The future of our creative ecosystem depends on our ability to embrace AI as a collaborative tool while instituting robust policies that protect human ingenuity and diversity. By implementing forward-thinking reforms in intellectual property law, establishing transparent governance, and supporting creators through collective licensing and targeted subsidies, we can steer the AI revolution towards a future where technology enhances rather than diminishes the value of human creativity.
The challenge is to balance innovation with the preservation of cultural and artistic authenticity—a task that will require cooperation between policymakers, industry leaders, and the creative community. In this brave new world, it is our shared responsibility to ensure that the digital brushstrokes of AI contribute to a richer, more diverse canvas of global culture. —The author, Hersh Shah, is Chief Executive Officer, IRM India Affiliate, the world’s leading professional certifying body for Enterprise Risk Management.
The views are personal..
