Business Horizons · 2023 · 105 citations · 29 references
ComputingComputer ScienceArtificial IntelligenceMachine LearningSoftware EngineeringArtificial Intelligence AdoptionArtificial Intelligence GovernanceAi CapabilitiesMachine Learning Analytics
Organizations are increasingly seeking to generate value and insights from their data by integrating advances in artificial intelligence (AI) such as machine learning (ML) systems into their operations. However, there are several managerial challenges associated with ML operations (MLOps). In this article we outline three key challenges and discuss how an emerging form of AI platforms – ‘no-code AI’ – may help organizations to address and overcome them. We outline how no-code AI can leverage MLOps by closing the gap between business and technology experts, enabling faster iterations between problems and solutions, and aiding infrastructure management. After outlining important remaining challenges associated with no-code AI and MLOps we propose three managerial recommendations. By doing so, we provide insights into an important novel, emerging phenomenon in AI software and set the stage for further research in the area.
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Participatory design and "democratizing innovation"
Erling Björgvinsson, Pelle Ehn, Per-Anders Hillgren · 2010 · 699 citations