AI-Driven Decision Making in Innovation

Artificial intelligence (AI) is reshaping the landscape of innovation by transforming how organizations generate ideas, make decisions, and develop products and services. This research paper comprehensively explores the role of AI in driving innovation through advanced technologies such as machine learning, natural language processing, generative models, and big data analytics. It examines AI’s integration into entrepreneurial ventures and corporate R&D settings and highlights key enablers and barriers. It also addresses ethical considerations including bias, explainability, and human–AI collaboration. Drawing on recent case studies and literature from 2024–2025, the study offers a multidimensional framework for understanding AI-driven decision-making in innovation. It concludes with strategic recommendations for leaders, policymakers, and educators, emphasizing the need for responsible, inclusive, and human-centered innovation ecosystems in the AI era.

Authors

Publication Details

Journal
Human computer interaction.
Published
2025-05-29
DOI
https://doi.org/10.62802/wr5yt023
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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AI-Driven Decision Making in Innovation

Aylin Işık Yener
Human computer interaction.
Big Data and Business Intelligence
article

AI-Driven Decision Making in Innovation

Aylin Işık Yener
article en

Abstract

Artificial intelligence (AI) is reshaping the landscape of innovation by transforming how organizations generate ideas, make decisions, and develop products and services. This research paper comprehensively explores the role of AI in driving innovation through advanced technologies such as machine learning, natural language processing, generative models, and big data analytics. It examines AI’s integration into entrepreneurial ventures and corporate R&D settings and highlights key enablers and barriers. It also addresses ethical considerations including bias, explainability, and human–AI collaboration. Drawing on recent case studies and literature from 2024–2025, the study offers a multidimensional framework for understanding AI-driven decision-making in innovation. It concludes with strategic recommendations for leaders, policymakers, and educators, emphasizing the need for responsible, inclusive, and human-centered innovation ecosystems in the AI era.

Human computer interaction.Vol. 9(1)
Openalex Percentile: Top 80%
Big Data and Business Intelligence
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