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Editorial Board

The Machine Leadership Journal is led by an editorial board that consists of diverse backgrounds in AI, executive leadership, professors of practice, and luminaries. Their collective experience spans every geographic region, sector, industry, and AI use case. This allows our Editorial Board to utilize a truly global approach to supporting research findings that advance the field of Machine Leadership​​.

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Our Editors are Listed Below (Alphabetical Order)

Research Associates

The Machine Leadership Journal relies on a robust peer review process to maintain high quality standards for thought leadership articles and DOI publications. The research team is responsible for managing the peer review process with the Editorial Board including the abstract and proposal review, committee decisions, citation and generative AI evaluation, and DOI assignment.

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