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The debate about Artificial Intelligence (AI) is reaching a level of collective hyperventilation. One question that frequently surfaces and fascinates us is whether AI will one day develop its own consciousness. Companies such as Anthropic, developer of the Claude chatbot, already employ researchers to investigate the “model well‑being” of their systems and to estimate the likelihood of future consciousness—some put it at around 15 %. As exciting as this discussion is, it easily distracts from the essential, already tangible effects of AI on our everyday lives. While we ponder whether machines have a “soul”, the world is changing at breathtaking speed—“stealthily at light speed”: technology is racing ahead, yet social perception and strategic action lag behind.
One of the most profound consequences of AI deployment is the shift in job profiles and competency requirements. Generative models can partially or fully take over tasks in many sectors; in the creative industries, up to 50 % of all activities are potentially automatable. Ajit Singh estimates that each additional percentage point of automation potential translates into an average loss of 15 000 jobs—though he leaves precise definitions vague.
The World Economic Forum’s Future of Jobs Report 2025 shows that by 2030 roughly 39 % of core skills will have changed. Although technological skills such as “AI and Big Data” gain importance most rapidly, more than 60 % of employers simultaneously expect a rising demand for abilities traditionally attributed to the human “soul”: resilience, creativity, self‑awareness, leadership, empathy, active listening. These inner qualities arise from self‑perception, memory, imagination and self‑regulation—and cannot simply be automated.
The report also forecasts a sweeping structural shift of the labour market: around 22 % of today’s jobs will be subject to macro‑economic transformation by 2030. In total, this is expected to create 170 million new positions (about 14 % of current employment), while 92 million jobs (8 %) will be displaced or disappear. Net of both effects, employment still grows by 78 million jobs—roughly 7 % more than today.
Despite clear data, a perception conflict persists: where the objective automation risk is greatest, it is often underestimated—and vice versa. The statistical link between perceived threat and actual risk is weak. That hampers targeted strategies and leaves the most vulnerable groups unprotected.
Investment, up‑skilling and regulatory decisions made today will shape tomorrow’s outcomes. Lacking appropriate decision frameworks, incentive structures and rules, there is a danger that technology will primarily drive the replacement of human labour, deepening inequality and increasing unemployment.
Companies worldwide respond differently. In Israel, 80 % of firms plan a strategic realignment to seize AI‑driven opportunities. Globally, employers focus above all on reskilling and upskilling (77 %), hiring talent to develop AI‑based tools (69 %), and recruiting people who can collaborate effectively with AI (62 %).
Yet productivity gains do not materialise automatically. A study by the University of Lausanne finds that many employees—even managers—neither notice nor consciously use the time saved by AI. Harnessing freed‑up capacity for value‑creating, creative or personal activities requires deliberate, continuous processes.
If work in future rests increasingly on psychological competences, it is not enough to talk only about “skills”. Crucial are the mental prerequisites that enable these abilities in the first place. The model of the inner economy sees the mind as a dynamic resource system: emotions and memories act within it like economic goods. Those who are mentally overloaded have no capacity for innovation, self‑regulation or empathy.
Companies that want to remain future‑proof must therefore build a “mental infrastructure”—spaces for self‑reflection, collective memory and emotional regulation. Especially people in the most affected sectors need not only technical training but also support to co‑shape the transformation actively.
The question of AI consciousness remains fascinating, but it is not the most urgent. Far more relevant are the already palpable and accelerating changes to the world of work. The shift towards psychologically shaped core competences, the need for strategic responses to job displacement and the challenge of using productivity gains wisely demand immediate attention. It may not be too late, but the clock is ticking. A new political and entrepreneurial reality is required to shape a future in which technology serves humanity—rather than the other way around.
Sources:
Engeler, I. et al. (2024). What Do You Do with the Time Saved by Generative AI Tools? Many Waste It, Managers Included. Working paper.
Prof. Dr. Dr. Oliver Hoffmann. (2024). Die Zukunft der Arbeit ist psychologisch - und kaum jemand spricht darüber. LinkedIn post.
O'Donnell, J. (2025, 28. April). The Algorithm.
Schmidt, H. (Datum unbekannt). KI: Bedrohung für den Arbeitsmarkt wird unterschätzt. faz.net (Frankfurter Allgemeine Zeitung). https://www.faz.net/pro/digitalwirtschaft/kuenstliche-intelligenz/ki-bedrohung-fuer-den-arbeitsmarkt-wird-unterschaetzt-110431298.html.
Singh, A. (2024/2025). Generative AI: Superintelligence with Unprecedented Opportunities and Harrowing Risks. SSRN (Social Science Research Network). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5208276).
The New York Times. (2025, 24. April). The A.I. Conscience: Will Future A.I. Systems Need Human Rights?. https://www.nytimes.com/2025/04/24/technology/ai-welfare-anthropic-claude.html.
World Economic Forum. (2025, Januar). Future of Jobs Report 2025. World Economic Forum. ISBN: 978-2-940631-90-2. https://www.weforum.org/reports/the-future-of-jobs-report-2025/.