{"id":117813,"date":"2026-09-17T16:43:07","date_gmt":"2026-09-17T14:43:07","guid":{"rendered":"https:\/\/www.hiig.de\/?p=117813"},"modified":"2026-09-17T17:00:11","modified_gmt":"2026-09-17T15:00:11","slug":"narratives-on-ai-and-the-future-of-work","status":"publish","type":"post","link":"https:\/\/www.hiig.de\/en\/narratives-on-ai-and-the-future-of-work\/","title":{"rendered":"Brave new world of work? Narratives on AI and the future of work"},"content":{"rendered":"\n

Many stories are told about AI and the future of work, ranging from mass unemployment to a life of abundance. These narratives are not neutral. They spread values, mobilise resources and, to some extent, bring about the very future they describe. This becomes especially visible when comparing Germany and the United States: where sovereignty and human control take centre stage in Germany, the image of a race dominates in the US. This article examines who tells these futures and who benefits from them.<\/strong><\/p>\n\n\n\n

The debate on the future of work in the age of AI is more contentious than ever. While Dario Amodei, CEO of Anthropic and thus himself a provider of one of the leading AI models, warns that AI is displacing entry level positions and that young adults in particular face major challenges (Morris, 2026), Elon Musk paints the picture of a utopian future, a “brave new world” in the sense of Aldous Huxley (Huxley, 1932). In this vision, we would no longer have to toil away at work but could live in abundance, since AI and machines would handle literally everything for us (Rogelberg, 2026). Such meaning making stories, which shape how the environment is perceived, are known as narratives. The sheer volume and contradictory nature of these narratives leaves behind a confusing, often chaotic debate. That is reason enough to take a closer look at the ideas surrounding AI’s role in the future of work. After all, behind these forecasts and stories lie concrete political and economic interests that influence regulation such as the AI Act, the world’s first comprehensive law by the European Union for the uniform regulation of artificial intelligence. Studies also show that ideas and narratives about AI shape how employees prepare for the future and pursue further training (von Richthofen et al., 2027). American narratives are particularly powerful in this respect. Large models from companies such as OpenAI, Anthropic, Google, Meta and Microsoft not only dominate the market for AI tools but, in doing so, also influence which topics and perspectives find a hearing in public debate.<\/p>\n\n\n\n

Why do narratives and public debate matter so much?<\/h2>\n\n\n\n

There are several reasons to take a closer look at the media debate on AI. Research has repeatedly shown the central role mass media play in shaping public knowledge, beliefs, values and social identities (Fairclough, 1995; Bohn et al., 2026). Against this backdrop, the analysis of public discourse represents one of the few conceivable methods for empirically studying the future: since the future has not yet arrived, we lack access to traditional data sources (Augustine, Soderstrom, Milner & Weber, 2019; G\u00fcm\u00fc\u015fay & Reinecke, 2022). Competing visions of the future are therefore not neutral but instruments of power. Once they are internalised by a sufficient number of people, they hold the potential to shape reality itself (Dries, 2024). This is precisely where our project “Narratives and Power in the Debate on AI and Work<\/a>” at the HIIG comes in, funded by the Hans B\u00f6ckler Foundation. We are conducting a country comparison between Germany and the United States to examine which narratives about AI and the future of work dominate public debate, which actors spread them and what interests may lie behind them.<\/p>\n\n\n\n

How does one study public discourse?<\/h2>\n\n\n\n

To examine public discourse on the future of work, we analysed coverage in German and American quality newspapers over the past fifteen years. The newspapers were selected to reflect the political spectrum in both countries.<\/p>\n\n\n\n

To identify relevant articles, we compiled a list of search terms combining words related to “work” with AI specific terms. From the articles we found, we then filtered out only those passages that actually engaged with the topic.<\/p>\n\n\n\n

We subsequently analysed these text passages using topic modelling, a method that uses machine learning to automatically identify recurring themes in large volumes of text. This allowed us to determine which themes appear most frequently in the discourse and to track them over time as well as compare them between Germany and the US.<\/p>\n\n\n\n

Technological determinism<\/h2>\n\n\n\n

Many narratives, particularly those spread by the large digital platforms, are based on the theory of technological determinism. This theory holds that technological progress follows an inevitable dynamic of its own, to which society can merely adapt (Schlogl et al., 2021; Gobena, 2024). In this worldview, technology appears largely autonomous, while society and people appear as passive objects that must follow technology and its associated technological imperative, a kind of inescapable “command” issued by technology itself. In other words, it rests on the assumption that whatever is technically possible must be implemented, and that technological developments bring about social change more or less automatically, regardless of how people might shape or regulate them.<\/p>\n\n\n\n

Dominant narratives of the debate<\/h2>\n\n\n\n

These narratives appear throughout public debate in both countries. Although various stories about AI’s impact on the future of work compete with one another in the discourse, most of them follow a logic of technological determinism. The first influential narrative is that of impending job destruction. It warns of mass unemployment, since automation and AI threaten established occupations and structures.<\/p>\n\n\n\n

Standing in contrast to this is the narrative of augmentation, which emphasises collaboration between humans and machines (Dries et al., 2024). In this view, AI is understood as a tool that extends human capabilities and takes over tedious routine tasks, a framing especially favoured by technology experts as a path towards greater productivity and prosperity (Richter et al., 2025; Dries et al., 2024).<\/p>\n\n\n\n

The narrative of reskilling and upskilling plays a further role. It promises to preserve the relevance of human labour through continuous learning and adaptation (Gobena, 2024). Critics, however, point out that this strong focus on individual responsibility neglects political and societal scope for shaping change, and thus ultimately follows the same logic of technological determinism (Schlogl et al., 2021).<\/p>\n\n\n\n

Closely related to this is the vision of work deintensification, the idea that machines will eventually generate prosperity entirely independently of human labour. A universal basic income would take over social protection, giving people more time for care, community and creative self fulfilment (Deranty et al., 2023; Dries et al., 2024).<\/p>\n\n\n\n

AI narratives in country specific comparison<\/h2>\n\n\n\n

All of these narratives are far more than mere ideas dreamed up by individual tech entrepreneurs. They have a performative effect and are used by companies and politics alike to spread convictions and values in public and thereby shape the future (Dries et al., 2024). This becomes especially clear when comparing debates about AI across different countries. It reveals that technological development is not a natural process but a socio-technical phenomenon deeply rooted in cultural contexts and political traditions (Richter et al., 2025; Richter et al., 2026). Country specific comparisons are therefore of central interest: they reveal, for example, how companies and governments deliberately exploit context specific fears and hopes to mobilise resources and enforce rules that serve their own advantage (Schlogl et al., 2021). Silicon Valley tech firms, for instance, stoke fears of falling behind China in a bid to prevent strict government regulation (Richter et al., 2025).<\/p>\n\n\n\n

Germany: sovereignty through AI<\/h3>\n\n\n\n

In Germany, AI is negotiated in particular within the framework of “digital sovereignty” (Richter et al., 2025), understood as the goal of technological independence from American and Chinese providers. Here, the technology is framed as a “smart tool” or “co-pilot” that is meant to support people and free them from repetitive work rather than replace them. This reflects a high degree of trust in state regulation and European values such as human dignity, self-determination and democratic processes of negotiation, which are understood as a long-term competitive advantage over the US and China (Richter et al., 2026).<\/p>\n\n\n\n

USA: dominance through AI<\/h3>\n\n\n\n

The US, by contrast, promotes the narrative of the “AI race”, a global contest for technological, economic and political supremacy (Richter et al., 2025). Here, AI is seen as the decisive key technology for securing and expanding America’s political and economic power (Richter et al., 2025). In this reading, society and individuals must adapt to change and secure their relevance in the labour market and the system through constant self improvement and optimisation (Gobena, 2024; Schlogl et al., 2021).<\/p>\n\n\n\n

The future is made, not given<\/h2>\n\n\n\n

This brief comparison of these differing visions of the future makes clear that AI is not a force of nature to which we must adapt without alternative, as the theory of technological determinism would suggest (Schlogl et al., 2021; Gobena, 2024). Rather, the future of work is an expectation that is created and steered by today’s dominant narratives (Dries et al., 2024). Because these visions of the future are not neutral, various interest groups deliberately deploy them as instruments of political or economic power (Dries et al., 2024; Richter et al., 2025).<\/p>\n\n\n\n

This raises the question: who tells these futures, whose interests do they serve, and who appears within them? And which narratives remain untold? This is, on the one hand, a highly political question. On the other, it is an empirical puzzle we continue to work on.<\/p>\n\n\n\n

References<\/h2>\n\n\n\n

Augustine, G., Soderstrom, S., Milner, D., & Weber, K. (2019). Constructing a distant future: Imaginaries in geoengineering. Academy of Management Journal, 62(6), 1930\u20131960. https:\/\/doi.org\/10.5465\/amj.2018.0059<\/a><\/p>\n\n\n\n

Bohn, S., Lohmeyer, N., Jha, H. K., Reinecke, J. (2026). Hostile Frame Takeover: Co-opting the Security Frame in the Nuclear Energy Debate. Academy of Management Journal, (online first). https:\/\/journals.aom.org\/doi\/10.5465\/amj.2024.0656<\/a><\/p>\n\n\n\n

Deranty, J.-P., Rhodes, C., & Yeoman, R. (2023). Does work have a future? The need for new meanings and new valuings of work. Organization, 30(5), 799\u2013808. https:\/\/doi.org\/10.1177\/13505084231186236<\/a><\/p>\n\n\n\n

Dries, N., Luyckx, J., & Rogiers, P. (2024). Imagining the (distant) future of work. Academy of Management Discoveries, 10(3), 319\u2013350. https:\/\/doi.org\/10.5465\/amd.2022.0130<\/a><\/p>\n\n\n\n

Fairclough, N. (1995). Media discourse. Edward Arnold.<\/p>\n\n\n\n

Gobena, E. (2024). Unboxing reskilling narratives: Analysing practice, agency and signifier in social media. New Technology, Work and Employment, 39(2), 335\u2013361. https:\/\/doi.org\/10.1111\/ntwe.12299<\/a><\/p>\n\n\n\n

G\u00fcm\u00fcsay, A. A., & Reinecke, J. (2022). Researching for desirable futures: From real utopias to imagining alternatives. Journal of Management Studies, 59(1), 236\u2013242. https:\/\/doi.org\/10.1111\/joms.12709<\/a><\/p>\n\n\n\n

Huxley, A. (2013). Sch\u00f6ne neue Welt. Ein Roman der Zukunft (H. E. Herlitschka, \u00dcbers.). Fischer. (Original erschienen 1932)<\/p>\n\n\n\n

Morris, C. (2025, 28. Mai). Anthropic CEO warns AI could eliminate half of all entry-level white-collar jobs. Fortune. https:\/\/fortune.com\/2025\/05\/28\/anthropic-ceo-warning-ai-job-loss<\/a><\/p>\n\n\n\n

Richter, V., Dergacheva, D., Kuznetsova, V. et al. Who\u2019s driving the AI hype in its formative phase? A longitudinal analysis of stakeholders in the US and German AI discourse on Twitter 2012\u20132021. AI & Soc (2026). https:\/\/doi.org\/10.1007\/s00146-026-03079-6<\/a><\/p>\n\n\n\n

Richter, V., Katzenbach, C., & Zeng, J. (2025). Negotiating AI(s) futures: Competing imaginaries of AI by stakeholders in the U.S., China, and Germany. JCOM, 24(2), A08. https:\/\/doi.org\/10.22323\/2.24020208<\/a><\/p>\n\n\n\n

Rogelberg, S. (2026, 19. Januar). Elon Musk says that in 10 to 20 years, work will be optional and money will be irrelevant thanks to AI and robotics. Fortune. https:\/\/fortune.com\/2026\/01\/19\/when-does-elon-musk-say-work-will-be-optional-and-money-will-be-irrelevant-ai-robotics\/<\/a><\/p>\n\n\n\n

Schlogl, L., Weiss, E., & Prainsack, B. (2021). Constructing the “future of work”: An analysis of the policy discourse. New Technology, Work and Employment, 36(3), 307\u2013326. https:\/\/doi.org\/10.1111\/ntwe.12202<\/a><\/p>\n\n\n\n

von Richthofen, G., K\u00f6hne, S., & Golf-Papez, M. (2027). Adapting to generative AI in creative work: a technological frames perspective on creative advertising. Journal of Business Research, 218<\/em>, 116483. https:\/\/doi.org\/10.1016\/j.jbusres.2026.116483<\/p>\n