Digital Transformation of The Moroccan SSE: AI and Blockchain at the Service of Social Innovation

Abstract : This study examines the impact of artificial intelligence (AI) and blockchain on the Social Solidarity Economy (SSE) in Morocco, in a context where digitalisation represents both an opportunity and a challenge for this key sector. Using a mixed methodology combining a quantitative survey (41 SSE structures) and qualitative interviews (20 players), we analyse the adoption rates, benefits and obstacles associated with these technologies. The results show that adoption is still limited, but promising: 28% of organisations are using AI, mainly for stock management and data analysis, while 12% are using blockchain, particularly for the traceability of local produce. These technologies are significantly improving operational efficiency (30% reduction in administrative costs), transparency (+45%) and beneficiary satisfaction (+22%). However, major obstacles remain, such as the lack of technical skills (67%), investment costs (58%) and connectivity problems in rural areas (42%). To maximise this potential, we recommend training adapted to local realities, the creation of funds dedicated to social innovation, and the strengthening of public-private partnerships for inclusive infrastructures. In conclusion, this research highlights that AI and blockchain can strengthen the Moroccan SSE, provided that a balanced approach is adopted, combining innovation and respect for socio-cultural specificities. It also opens up avenues for future research into hybrid models integrating technologies and traditional know-how.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-29
DOI
https://doi.org/10.5281/zenodo.16993262
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Digital Transformation of The Moroccan SSE: AI and Blockchain at the Service of Social Innovation

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Digital Transformation of The Moroccan SSE: AI and Blockchain at the Service of Social Innovation

article en

Abstract

Abstract : This study examines the impact of artificial intelligence (AI) and blockchain on the Social Solidarity Economy (SSE) in Morocco, in a context where digitalisation represents both an opportunity and a challenge for this key sector. Using a mixed methodology combining a quantitative survey (41 SSE structures) and qualitative interviews (20 players), we analyse the adoption rates, benefits and obstacles associated with these technologies. The results show that adoption is still limited, but promising: 28% of organisations are using AI, mainly for stock management and data analysis, while 12% are using blockchain, particularly for the traceability of local produce. These technologies are significantly improving operational efficiency (30% reduction in administrative costs), transparency (+45%) and beneficiary satisfaction (+22%). However, major obstacles remain, such as the lack of technical skills (67%), investment costs (58%) and connectivity problems in rural areas (42%). To maximise this potential, we recommend training adapted to local realities, the creation of funds dedicated to social innovation, and the strengthening of public-private partnerships for inclusive infrastructures. In conclusion, this research highlights that AI and blockchain can strengthen the Moroccan SSE, provided that a balanced approach is adopted, combining innovation and respect for socio-cultural specificities. It also opens up avenues for future research into hybrid models integrating technologies and traditional know-how.

Zenodo (CERN European Organization for Nuclear Research)
Université Sultan Moulay Slimane (MA), Université Hassan 1er (MA), Université Hassan II Mohammedia (MA)
Partnerships for the goals
Openalex Percentile: Top 59%
Geochemistry and Geologic Mapping
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Digital Transformation of The Moroccan SSE: AI and Blockchain at the Service of Social Innovation · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS