In 2024, an indie film titled The Last Screenwriter was set to premiere at the Prince Charles Cinema in Leicester Square, London. I say set to because, at the last minute, the cinema pulled the screening. Why? The film, directed by Swiss filmmaker Peter Luisi, was scripted entirely by ChatGPT.
The story follows Jack, a celebrated screenwriter whose career is upended when an AI matches — and arguably surpasses — his storytelling abilities. Its premise, and the fact it was written by an AI, sparked outrage. The Prince Charles Cinema reportedly received around 200 complaints, with concerns ranging from ethical questions about AI creativity to fears of an AI-dominated future (Dams, 2024). One critic summed it up as more than a debate about a film — it was a battle over the future of human work.
But this controversy isn’t limited to cinema. It mirrors a much larger transformation sweeping through the labour markets of the Global North. As highlighted by the recently released OECD report, Job Creation and Local Economic Development 2024: The Geography of Generative AI, generative AI is reshaping industries and redefining work, particularly for high-skilled professionals in urban areas. Unlike earlier waves of automation, which primarily affected repetitive, low-skill tasks (blue-collar), this time it’s cognitive and creative roles feeling the heat. The implications are as vast as they are unsettling.
AI Exposure
The OECD’s report lays bare an uncomfortable truth: generative AI is different. While earlier technologies replaced repetitive, manual labour, this innovation targets the kinds of tasks long considered uniquely human — creativity, analytical thinking, and problem-solving.
The report uses what it terms “AI exposure metrics” to gauge how much a job’s tasks overlap with what AI is capable of doing. It then uses this to help predict which jobs and occupations will be most affected by AI. Using this metric, the report estimates that 25% of workers in OECD countries are already “exposed” to generative AI, meaning at least 20% of their job tasks could be automated or significantly accelerated using AI (OECD, 2024). This exposure is concentrated in urban areas, where industries like technology, finance, education, and media thrive. In these metropolitan regions, 32% of workers face high exposure compared to just 21% in rural areas.
Creative industries are particularly vulnerable. The controversy surrounding The Last Screenwriter illustrates how AI can encroach on roles once thought untouchable. But it’s not just artists and writers feeling the pressure. Data analysts, educators, software engineers, and even healthcare professionals are now grappling with the possibility that parts of their work could be performed faster, cheaper, and perhaps better by a machine.
Industries in Flux
If you’re a financial analyst, a software engineer, or a teacher, you might feel the tremors of change in your profession already.
In the tech sector, generative AI tools are writing and debugging code, transforming the role of software developers. GitHub’s Copilot, for instance, acts as a highly efficient coding assistant, completing tasks that once required hours of human labour. In finance, AI systems are crunching data and generating reports with astonishing speed, reshaping what it means to be an analyst. Education isn’t immune either; AI-powered platforms are personalising learning and automating administrative tasks. Meanwhile, in healthcare, AI tools assist in diagnostics, interpreting medical images with remarkable accuracy.
The report emphasises that this isn’t just about speeding up workflows — it’s about fundamentally redefining them. The OECD notes that roles requiring a mix of technical expertise and interpersonal skills are likely to become more valuable, while tasks heavily reliant on routine cognitive work may disappear altogether (OECD, 2024).
But here’s the twist: the report doesn’t predict mass unemployment. Instead, it sees a reconfiguration of work. Jobs aren’t vanishing en masse — they’re evolving. This evolution can feel like a tightrope walk: precarious, terrifying, and thrilling all at once.
The Paradox of the Global North
If you are interested in supply chains originating in the Global South — where much of our manufacturing has been outsourced — the OECD is keen to disabuse you of the idea that AI will have the greatest impact there. In fact, it emphasises that AI’s impact is especially pronounced in the Global North, where economies are heavily reliant on high-skilled, cognitive jobs. Urban areas in these regions tend to adopt new technologies early, amplifying their exposure to disruption.
Economies in the Global South, often more dependent on manual labour and routine tasks, face less immediate risk from generative AI. This creates a paradox: the regions that have historically benefited most from technological innovation now find themselves among the most vulnerable. Policymakers and business leaders in the Global North must confront this reality and consider how to spread the benefits of AI more equitably.
Not Mass Unemployment, But Mass Change
The OECD doesn’t predict a robot apocalypse or the coming of Blade Runner, but it does foresee seismic shifts in the nature of work. Generative AI will likely lead to job restructuring rather than outright replacement. Tasks where machines excel — efficiency, precision, scalability — will be taken over, leaving humans to focus on areas where they retain a comparative advantage: creativity, empathy, and nuanced decision-making.
This isn’t just an economic adjustment; it’s a societal one. Workers in exposed roles will need to upskill or risk being left behind, while new opportunities will arise in fields that integrate AI technologies. But the path to these opportunities is not guaranteed — it requires preparation, investment, and an understanding of how to navigate this rapidly changing landscape.
What’s Next?
The OECD offers a pragmatic starting point: upskilling and reskilling programmes, investments in digital infrastructure, and support for small businesses (OECD, 2024). These measures are critical, but they touch only the surface of the challenge. At its core, this is a story about balance — between innovation and inclusion, growth and fairness.
Historically, technological revolutions have widened inequalities. Researchers like Acemoglu and Restrepo (2020) argue that automation has often reduced the labour share of income, consolidating wealth among capital owners. Generative AI, with its potential to supercharge productivity, risks repeating this pattern unless interventions are made.
One approach is to rethink how productivity gains are distributed. Policies encouraging profit-sharing schemes or employee ownership programmes could align corporate success with worker wellbeing. At the same time, updating antitrust regulations might prevent a handful of tech giants from monopolising generative AI development, ensuring more competitive and diverse markets.
For businesses, generative AI should be seen as a tool to enhance human potential rather than replace it. Organisations that integrate AI alongside investments in human capital are more likely to achieve sustainable success. Arntz et al. (2016) highlight that firms adopting this dual approach report stronger long-term productivity gains and employee satisfaction.
For individuals, adaptability remains crucial. Workers will need to cultivate skills where humans retain a clear advantage — creativity, complex problem-solving, and emotional intelligence. These “human” skills are expected to grow in demand as automation accelerates (World Economic Forum, 2023). Lifelong learning and an openness to technological collaboration will be essential in this new economic reality.
But beyond practical solutions lies a broader question: what kind of society do we want to build? Generative AI presents an opportunity to rethink not just how we work, but why.
References
- Acemoglu, D. and Restrepo, P. (2020) ‘The race between man and machine: Implications of technology for growth, factor shares, and employment’, American Economic Review, 108(6), pp. 1488–1542. Available at: https://doi.org/10.1257/aer.20160696.
- Arntz, M., Gregory, T. and Zierahn, U. (2016) ‘The risk of automation for jobs in OECD countries: A comparative analysis’, OECD Social, Employment and Migration Working Papers, №189, OECD Publishing, Paris. Available at: https://doi.org/10.1787/5jlz9h56dvq7-en.
- Dams, T. (2024) ‘Director of AI-written feature The Last Screenwriter speaks out after London cinema cancels screening’, Screen Daily. Available at: https://www.screendaily.com/news/director-of-ai-written-feature-the-last-screenwriter-speaks-out-after-london-cinema-cancels-screening/5194712.article.
- OECD (2024) Job Creation and Local Economic Development 2024: The Geography of Generative AI. Paris: OECD Publishing. Available at: https://doi.org/10.1787/83325127-en.
- World Economic Forum (2023) The Future of Jobs Report 2023. Geneva: WEF. Available at: https://www.weforum.org/publications/the-future-of-jobs-report-2023/.
