You will be provided with a reference and some statements. Please determine whether each statement is 'supported', 'unsupported', or 'unknown' with respect to the reference. Please note:
First, assess whether the reference contains any valid content. If the reference contains no valid information, such as a 'page not found' message, then all statements should be considered 'unknown'.
If the reference is valid, for a given statement: if the facts or data it contains can be found entirely or partially within the reference, it is considered 'supported' (data accepts rounding); if all facts and data in the statement cannot be found in the reference, it is considered 'unsupported'.

You should return the result in a JSON list format, where each item in the list contains the statement's index and the judgment result, for example:
[
    {
        "idx": 1,
        "result": "supported"
    },
    {
        "idx": 2,
        "result": "unsupported"
    }
]

Below are the reference and statements:
<reference>
EconPapers: AI and the labour market: opening the black box

By Nathalie Greenan, Dario Guarascio and Jelena Reljic; Abstract: Abstract This work aims at discussing some of the main (open) questions about the labour impact of AI technologies.

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AI and the labour market: opening the black box

Nathalie Greenan
,

Dario Guarascio
and

Jelena Reljic

Eurasian Business Review
, 2025, vol. 15, issue 4, No 1, 925-951

Abstract:

Abstract This work aims at discussing some of the main (open) questions about the labour impact of AI technologies. First, we provide an in-depth literature review focusing on concepts and measurement approaches and distinguishing between up (invention and knowledge creation), mid (technological innovation and development) and downstream (adoption and diffusion) components of the AI value chain. Second, we summarise the six articles included in the Special Issue ‘AI and labor markets: opening the black box’, distinguishing between contributions focusing on AI exposure, occupations and skill demand; the relationship between AI and automation technologies and their impact on income distribution; and, finally, the effect on organisational structures, management practices, and power dynamics within workplaces. Our analysis emphasises that AI’s employment effects are neither predetermined nor uniform, but shaped by implementation contexts, organisational choices, and institutional frameworks. We find that heterogeneity matters at multiple levels—across countries, sectors, firms, and demographic groups—challenging deterministic narratives and highlighting the need for adaptive policy responses that recognise these asymmetries.

Keywords:

Artificial Intelligence
;
Industry 4.0
;
Labour markets
;
Employment
;
Skill demand
;
Organisational change
(search for similar items in EconPapers)

Date:
2025

References:

View references in EconPapers

View complete reference list from CitEc

Citations:

View citations in EconPapers
(1)

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http://link.springer.com/10.1007/s40821-025-00324-8
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https://EconPapers.repec.org/RePEc:spr:eurasi:v:15:y:2025:i:4:d:10.1007_s40821-025-00324-8

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DOI:

10.1007/s40821-025-00324-8

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Handle: RePEc:spr:eurasi:v:15:y:2025:i:4:d:10.1007_s40821-025-00324-8
</reference>

<statements>
1. Rather than generating uniform technological unemployment, AI is driving job transformation, task reconfiguration, and organizational restructuring, with heterogeneous outcomes shaped by sectoral conditions, firm strategies, and institutional frameworks.
2. This broad reach means AI can reshape economic structures and institutional dynamics, amplifying existing trends such as skill-biased technological change, creative destruction, and the rise of superstar firms, while also introducing new forms of algorithmic management and platformization.
3. The net effect is a reconfiguration of job composition and internal labor markets rather than simple elimination of employment.
4. At the same time, AI systems can support new forms of collaboration, knowledge sharing, and decentralized decision-making, depending on how they are integrated into organizational processes.
5. The literature concludes that AI’s employment effects are not predetermined by the technology itself but are shaped by implementation choices, worker participation, and institutional constraints, reinforcing the importance of governance and social dialogue.
6. Reviews of high-quality journal articles between 2020 and 2025 emphasize that technological progress is not inherently inclusive; its distributional effects depend on how AI is integrated into organizational and social frameworks and whether workers and their representatives have a voice in shaping implementation.
7. The literature therefore frames AI’s restructuring impact as contingent and path-dependent, shaped by cumulative policy and organizational decisions rather than determined solely by technical capabilities.
8. Third, aggregate employment impacts appear modest so far, but distributional consequences in terms of inequality and polarization are substantial and likely to intensify without supportive institutions and policies.
9. As AI continues to evolve as a central driver of the Fourth Industrial Revolution, understanding and shaping its labor market restructuring dynamics remains a critical research and policy frontier.
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.