The UK’s most comprehensive study to date on the integration of generative artificial intelligence (AI) into the film, television, and video game industries.

AI in the UK Screen Sector – Innovation, Challenges, and the Path Forward

by ChatGPT-4o

The CoSTAR Foresight Lab’s June 2025 report, AI in the Screen Sector: Perspectives and Paths Forward, represents the UK’s most comprehensive study to date on the integration of generative artificial intelligence (AI) into the film, television, and video game industries. Developed by the British Film Institute (BFI) with support from a broad network of experts, this report provides an insightful, multi-dimensional exploration of how AI is transforming storytelling, production, audience engagement, and the broader creative economy. It reveals a complex ecosystem of experimentation, caution, and ambition, underscored by calls for robust ethical, legal, and strategic frameworks.

Key Messages

1. The UK as a Silent Pioneer
   The report likens the UK’s AI engagement in the screen sector to an iceberg—only a small portion of its activity is visible. Beneath the surface, however, lies a rich and growing network of AI experimentation across development, production, and post-production. While the UK lacks prominent public-facing AI tools like those from the US or China, its creative professionals are actively integrating generative AI into their workflows in nuanced ways.

2. AI as an Engine of Democratization and Efficiency
   AI is increasingly used to automate time-consuming tasks like rotoscoping, upscaling, and subtitling, freeing up resources for more creative and high-level work. It also lowers barriers to entry, allowing independent creators and small studios to realize ambitious projects with limited budgets.

3. Creative Empowerment and New Storytelling Paradigms
   Tools such as text-to-image generators, real-time interactive storytelling engines, and AI-augmented production platforms are enabling new narrative formats and artistic expressions. The report documents innovations from companies like Flawless, Humain, and Metaphysic, which are pioneering “vubbing,” digital humans, and real-time facial aging/de-aging technologies.

4. The Rise of the AI-native Studio
   Studios that embed AI throughout the creative pipeline—from scripting to post—are emerging in the UK. These organizations challenge traditional production timelines, cost structures, and creative hierarchies.

5. Risks and Ethical Dilemmas Loom Large
   Despite its potential, generative AI introduces significant concerns about copyright infringement, authorship, job displacement, cultural homogenization, and sustainability. The report identifies copyright as the dominant issue, especially in light of AI models being trained on massive datasets of copyrighted content without permission or compensation.

6. An Urgent Need for Strategic Coordination
   The report warns that without targeted support, coherent frameworks, and collective action, the UK could fall behind global competitors or lose control of its cultural narrative to foreign-trained AI systems. It proposes three overarching goals: develop collaborative frameworks, provide targeted support to high-potential sectors, and dismantle barriers to growth.

Most Surprising Statements

• AI Adoption Is More Widespread Than Publicly Perceived:
  Contrary to media narratives suggesting the UK is lagging behind, the report uncovers extensive behind-the-scenes AI usage, especially in early-stage development and post-production.

• BBC’s Structured AI Approach:
  The BBC’s “scan > pilot > scale” methodology serves as a model for responsible adoption, balancing innovation with caution. It contrasts starkly with more chaotic or opportunistic approaches seen elsewhere.

• Rise of AI-first Studios:
  The emergence of studios that view AI not as a tool but as an intrinsic element of storytelling marks a significant industry shift. These startups, often funded by venture capital, aim to compete directly with traditional production houses.

• Low Engagement with UK-Trained Foundation Models:
  There is no major UK-developed large language model currently available for screen creatives. Instead, most creators rely on US- or China-based tools, raising concerns about cultural dependency and bias.

Most Controversial Statements

• OpenAI’s Push for TDM Exceptions in the UK:
  OpenAI’s lobbying for a broad text and data mining exception to UK copyright law is highly controversial. It pits Silicon Valley’s techno-libertarianism against the UK’s established IP ecosystem and raises fears of systemic exploitation of creators.

• Widespread Use of AI-Generated Content Despite Legal Uncertainty:
  Many creatives continue to use AI outputs in development, even as the legal foundations for such use remain uncertain. This reflects a dangerous normalization of rights infringement and legal ambiguity.

• Job Losses and De-skilling Risks:
  Automation threatens to eliminate many entry-level roles in the industry, jeopardizing talent pipelines and limiting future access to senior creative positions. This concern is particularly acute for younger and marginalized creatives.

• Opaque Energy Costs and Environmental Impact:
  Generative AI’s carbon footprint is largely hidden from users in the creative industries. As AI-generated imagery and video processing grow, so too does its unsustainable energy consumption—a fact often ignored in mainstream discourse.

Most Valuable Contributions

• Three Horizons Framework for Strategic Action
  The report’s “Three Horizons” model (present challenges, rising disruptions, and desirable futures) offers a practical and adaptable structure for sector-wide transformation. This framework aids in synchronizing policy, investment, and industry strategy.

• Clear, Actionable Roadmap (Figure 1)
  The roadmap links recommendations to strategic outcomes across time horizons. It includes proposals such as:

  • Making the UK a global leader in IP licensing for AI.

  • Embedding sustainability standards into AI adoption.

  • Supporting independent creators with accessible tools.

  • Enhancing transparency around AI use in public content.

• Table 3: Legal and Ethical Matrix
  The legal and ethical issues table provides a concise yet comprehensive mapping of key risks (e.g., copyright, employment, carbon, bias) and plausible mitigations (licensing, transparency, training, standards). It’s a valuable tool for educators, lawyers, and policy designers.

• Evidence-based yet Multidisciplinary Methodology
  By combining case studies, survey data, interviews, and international comparative insights, the report achieves both depth and breadth, providing an unusually holistic view.

Recommendations

For the Creative Sector

1. Collectively Advocate for Licensing Frameworks:
   Industry actors must push for enforceable standards on AI training data usage and advocate for equitable licensing structures.

2. Invest in Skills Development and AI Literacy:
   Upskill creatives at all levels—not just in technical know-how, but in critical thinking, ethics, and legal literacy related to AI.

3. Protect and Promote Distinct Cultural Narratives:
   Counter the flattening influence of US-centric AI models by developing locally tuned tools, styles, and datasets that reflect the UK’s cultural diversity.

4. Prioritize Authenticity and Transparency:
   Adopt labelling standards for AI-generated content and promote provenance verification tools to maintain public trust.

For AI Developers

1. License Before You Train:
   Build training pipelines based on ethically licensed content and pay rightsholders fairly. Treat the creative sector as a partner, not a dataset.

2. Localize Models and Fine-Tune for Cultural Sensitivity:
   Develop or collaborate on UK-focused models to ensure outputs reflect diverse perspectives and avoid cultural homogenization.

3. Design Energy-Responsible Models:
   Prioritize models with lower computational costs and disclose environmental impacts, as part of broader sustainability goals.

4. Develop Creative-Aware Guardrails:
   Prevent regurgitation of copyrighted material and bias by embedding filters and controls that understand artistic boundaries.

For Regulators and Policymakers

1. Mandate Transparency in Training Data and Outputs:
   Require AI developers to disclose sources of training data and provide means for authors to opt out or seek compensation.

2. Reject Broad TDM Exceptions:
   Strengthen, not weaken, the UK’s copyright framework. An opt-out model undermines the fundamental premise of consent in IP law.

3. Support AI Infrastructure for the Creative Sector:
   Establish publicly funded AI compute and data hubs tailored to creative needs, especially for independent artists and SMEs.

4. Promote Cross-sector Collaborations:
   Facilitate dialogue between technologists, creatives, and policymakers through dedicated forums, sandboxes, and grants.

Conclusion

The BFI’s AI in the Screen Sector report is not merely a snapshot of technological disruption—it is a foundational call to action. It highlights the UK’s vibrant yet often hidden engagement with generative AI, while warning of structural challenges that must be addressed to ensure sustainable, inclusive, and ethical adoption. By aligning creative ingenuity, technological capability, and policy foresight, the UK can remain not only a global cultural leader, but also a model for responsible AI integration in the arts.