Artificial Intelligence (AI) is rapidly transforming how organizations work, but what does this mean for the social economy sector? Nonprofits, charities, cooperatives, and collectives are beginning to engage with AI technologies, facing both promise and peril in equal measure. This special issue invites papers that explore how AI is being adopted, adapted, or resisted within Canada and elsewhere in diverse social economy landscapes, and how these experiences connect to global movements for ethical, equitable, and community-led technology.

We aim to gather critical and creative scholarship that speaks to the unique role of social economy organizations in shaping AI’s future. These organizations are not only users of technology; they are also key actors in articulating alternative values and governance approaches—ones rooted in equity, human rights, and the well-being of communities (Lantero, 2018).

Social economy organizations in Canada are distinct in their missions and values, yet they often rely on AI tools built by for-profit vendors and shaped by global and multinational business priorities. This raises important questions: How can these organizations adopt AI in ways that align with their social goals? What risks and opportunities does AI present? And how can Canadian experiences contribute to a different kind of AI development, one that resists purely commercial logics and reflects a broader public interest?

This special issue invites empirical studies, theoretical essays, case analyses, and practice-informed perspectives from both Canadian and international contexts. Our goal is to center the voices of those working in and with the social economy, to highlight underexplored tensions and possibilities in the AI space.

Key Themes and Questions:

How are nonprofits, cooperatives, and other social economy organizations in Canada currently engaging with AI (Statistics Canada, 2024a)?
What barriers to AI adoption are specific to the social economy, including concerns around capacity, privacy, and value alignment (Statistics Canada, 2024b)?
How do AI systems reflect or clash with the missions of equity-oriented organizations (Lantero, 2018; Moss et al., 2021)?
What are the implications of using AI in sensitive areas such as healthcare (Abdullah et al., 2020; Anawati et al., 2024), homelessness (VanBerlo et al., 2021; Liyanage et al., 2023), and sport (Yang, Byers, & Koenigstorfer, 2025)?
How can the social economy contribute to shaping a distinct, values-driven model of AI development—different from those dominated by large tech firms (Brandusescu, 2021; Attard-Frost, Brandusescu, & Lyons, 2024)?
What international experiences offer insights for the Canadian context?

Why This Special Issue Now?

The growing use of AI by social economy organizations in Canada (CICP-PCPOB, 2022; 2023; 2024) is happening alongside widespread concerns about readiness, ethical risks, and knowledge gaps. Recent data show that organizations cite a Lack of knowledge on the capabilities of AI (7.3%), concerns about privacy or security (6.0%), and AI is not a mature enough technology yet (4.8%) as top reasons for non-adoption (Statistics Canada, 2024b). These findings point to an urgent need for more shared knowledge, grounded research, and sector-specific strategies.

Despite Canada’s early national AI strategy, regulation remains fragmented. The recent failure of the Artificial Intelligence and Data Act (AIDA) to pass through Parliament further highlights a governance gap. In the meantime, private-sector-aligned intermediaries are positioning themselves to capture funding and influence AI implementation (Brandusescu, 2021), often sidelining social economy and local community-led priorities.

This special issue is a space to bring in the voices, research, and lived experiences from social economy organizations. We aim to foster new frameworks for understanding, using, and reinventing AI through the lens of social values.

We welcome contributions that:

Are grounded in the work of social economy organizations in Canada or offer relevant international perspectives;
Address theoretical, ethical, and practical dimensions of AI use in the social economy;
Explore the relationship between AI and values such as equity, justice, human rights, and ecological well-being;
Consider how social economy organizations can shape AI development and policy beyond adoption.

We accept contributions in English or French.

References

Abdullah, S. S., Rostamzadeh, N., Sedig, K., Lizotte, D. J., Garg, A. X., & McArthur, E. (2020). Machine Learning for Identifying Medication-Associated Acute Kidney Injury. Informatics, 7(2), Article 2. https://doi.org/10.3390/informatics7020018

Anawati, A., Fleming, H., Mertz, M., Bertrand, J., Dumond, J., Myles, S., Leblanc, J., Ross, B., Lamoureux, D., Patel, D., Carrier, R., & Cameron, E. (2024). Artificial intelligence and social accountability in the Canadian health care landscape: A rapid literature review. PLOS Digital Health, 3(9), e0000597. https://doi.org/10.1371/journal.pdig.0000597

Attard-Frost, B., Brandusescu, A., & Lyons, K. (2024). The governance of artificial intelligence in Canada: Findings and opportunities from a review of 84 AI governance initiatives. Government Information Quarterly, 41(2), 101929. https://doi.org/10.1016/j.giq.2024.101929

Brandusescu, A. (2021). Artificial intelligence policy and funding in Canada: Public investments, private interests. Centre for Interdisciplinary Research on Montreal, McGill University. https://www.mcgill.ca/centre-montreal/files/centre-montreal/aipolicyandfunding_report_updated_mar5.pdf

CICP-PCPOB. (2024). CICP-PCPOB Weekly Report- Rapport Hebdomadaire (No. 2.10.39) Philanthropy and Social economy Leadership, Carleton University. https://carleton.ca/cicp-pcpob/homepage/research-data/

CICP-PCPOB. (2023). CICP-PCPOB Weekly Report- Rapport Hebdomadaire (No. 1.10.42). Philanthropy and Social economy Leadership, Carleton University. https://carleton.ca/cicp-pcpob/homepage/research-data/

CICP-PCPOB. (2022). CICP-PCPOB Weekly Report- Rapport Hebdomadaire (No. 1.4.14). Philanthropy and Social economy Leadership, Carleton University. https://carleton.ca/cicp-pcpob/homepage/research-data/

Lantero, M. (2018). Governing Artificial Intelligence Upholding Human Rights & Dignity (p. 38). Data & Society. https://datasociety.net/library/governing-artificial-intelligence/

Liyanage, C. R., Mago, V., Schiff, R., Ranta, K., Park, A., Lovato-Day, K., Agnor, E., & Gokani, R. (2023). Understanding Why Many People Experiencing Homelessness Reported Migrating to a Small Canadian City: Machine Learning Approach With Augmented Data. JMIR Formative Research, 7, e43511. https://doi.org/10.2196/43511

Moss, E., Watkins, E. A., Singh, R., Elish, M. C., & Metcalf, J. (2021). Assembling Accountability: Algorithmic Assessment for the Public Interest (p. 64). Data & Society. https://datasociety.net/library/assembling-accountability-algorithmic-impact-assessment-for-the-public-interest/

Statistics Canada (2024a). Table 33-10-0878-01 Use of artificial intelligence (AI) by businesses or organizations in producing goods or delivering services over the next 12 months, third quarter of 2024. DOI: https://doi.org/10.25318/3310087801-eng

Statistics Canada (2024b). Table 33-10-0879-01 Reasons business or organization does not plan to use artificial intelligence (AI) in producing goods or delivering services over the next 12 months, third quarter of 2024. DOI: https://doi.org/10.25318/3310087901-eng

VanBerlo, B., Ross, M. A. S., Rivard, J., & Booker, R. (2021). Interpretable machine learning approaches to prediction of chronic homelessness. Engineering Applications of Artificial Intelligence, 102, 104243. https://doi.org/10.1016/j.engappai.2021.104243

Yang, Y., Byers, T., & Koenigstorfer, J. (2025). A Machine‐Learning Approach to Understanding Performance of Canadian Social economy Sport Organizations. Social economy Management and Leadership, 35(3), 663–675. https://doi.org/10.1002/nml.21651