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Democratizing artificial intelligence: How no-code AI can leverage machine learning operations

Leif Sundberg, Jonny Holmström

2023Business Horizons106 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Leverage (statistics)Computer scienceArtificial intelligenceBusiness intelligenceCode (set theory)Key (lock)Closing (real estate)Source lines of codeMachine learningKnowledge managementData scienceSoftwareSet (abstract data type)Software engineeringComputer securityProgramming languageBusinessFinanceBlockchain Technology Applications and SecurityBig Data and Business IntelligenceEthics and Social Impacts of AI
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