Generative Artificial Intelligence (GenAI) in Social Work Education and Accreditation Standards: From Recognition to Curriculum Authorisation

The emergence of Generative Artificial Intelligence (GenAI) raises important questions about how social work education prepares graduates for ethical practice. Using the Australian Social Work Education and Accreditation Standards (2024) (ASWEAS 2024) as a case study, we examined how accreditation frameworks respond to technological change. We identify a gap between recognition of GenAI as a significant issue and its inclusion within curriculum-authorising elements shaping curriculum, assessment, and graduate outcomes. Drawing on accreditation literature and emerging scholarship, we identified accreditation design tensions and argue that emerging issues become curriculum authorised only when embedded within accreditation mapping architecture. We propose directions for accreditation approaches.IMPLICATIONS GenAI is increasingly recognised as significant for social work education and practice, but remains only partially reflected in accreditation curriculum mapping requirements.Without explicit expectations embedded within accreditation mapping requirements, implementation is likely to vary across programs.Future approaches should incorporate a critical framing of GenAI; explicit curriculum mapping requirements; higher-order capabilities; hybrid competency design; updateable, profession-led guidance.

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Publication Details

Journal
Australian Social Work
Published
2026-10-28
DOI
https://doi.org/10.1080/0312407x.2026.2736125
Primary Topic
Social Work Education and Practice
Type
article
Field-Weighted Citation Impact
0.00
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article

Generative Artificial Intelligence (GenAI) in Social Work Education and Accreditation Standards: From Recognition to Curriculum Authorisation

Kerryn Bagley, Sophie Goldingay, Christina Sadowski, Matthew Crane
Australian Social Work
Social Work Education and Practice
article

Generative Artificial Intelligence (GenAI) in Social Work Education and Accreditation Standards: From Recognition to Curriculum Authorisation

Kerryn Bagley, Sophie Goldingay, Christina Sadowski, Matthew Crane
article en

Abstract

The emergence of Generative Artificial Intelligence (GenAI) raises important questions about how social work education prepares graduates for ethical practice. Using the Australian Social Work Education and Accreditation Standards (2024) (ASWEAS 2024) as a case study, we examined how accreditation frameworks respond to technological change. We identify a gap between recognition of GenAI as a significant issue and its inclusion within curriculum-authorising elements shaping curriculum, assessment, and graduate outcomes. Drawing on accreditation literature and emerging scholarship, we identified accreditation design tensions and argue that emerging issues become curriculum authorised only when embedded within accreditation mapping architecture. We propose directions for accreditation approaches.IMPLICATIONS GenAI is increasingly recognised as significant for social work education and practice, but remains only partially reflected in accreditation curriculum mapping requirements.Without explicit expectations embedded within accreditation mapping requirements, implementation is likely to vary across programs.Future approaches should incorporate a critical framing of GenAI; explicit curriculum mapping requirements; higher-order capabilities; hybrid competency design; updateable, profession-led guidance.

Australian Social Work
Federation University (AU), Deakin University (AU), La Trobe University (AU)
Openalex Percentile: Top 7%
Social Work Education and Practice
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