The DOI matches its Crossref record, with a small difference in title or year; 66 of the 66 references it cites were found in a registry or an index.
Generative AI as a transformative force for innovation: a review of opportunities, applications and challenges
Abstract
Purpose This study examines the existing literature on generative artificial intelligence (Gen AI) and its impact across many sectors. This analysis explores the potential, applications, and challenges of Gen AI in driving innovation and creativity and generating ideas. Design/methodology/approach The study adopts a comprehensive literature review approach, carefully assessing current scientific articles on Gen AI published from 2022 to 2024. The analysis examines trends and insights derived from research. Findings The review indicates that Gen AI has significant potential to augment human creativity and innovation processes as a collaborative partner. However, it is imperative to prioritize responsible development and ethical frameworks in order to effectively tackle biases, privacy concerns, and other challenges. Gen AI is significantly transforming business models, processes, and value propositions in several industries, but with varying degrees of effect. Findings indicate also that despite the theory-driven approach to investigating Gen AI's creative and innovative potential, cutting-edge applications research prioritizes examining the possibilities of Gen AI models. Research limitations/implications Although this review offers a picture of great possibilities, it concurrently underlines the necessity for a deep knowledge of Gen AI nuances to fully harness its capabilities. The findings indicate that continuous research and exploration efforts are required to address the…
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“Mass marketing, which dominated the last century, operated on broadcast principles: a single message (a TV commercial, print ad, or billboard) was disseminated to millions, with minimal personalization.”
From Surveillance Capitalism, Consumer Subjectivity and Marketing in the Age of Artificial Intelligence (2025) · cites this paper as Sedkaoui & Benaichouba, 2024
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Metadata
- Authors
- Sedkaoui, S., & Benaichouba, R.
- Affiliations
- Université Djilali Bounaama Khemis Miliana (DZ)
- Venue
- European Journal of Innovation Management
- Publisher
- Emerald
- Published
- 2024-08-01
- Volume
- 29
- Issue
- 3
- Pages
- 677-701
- ISSN
- 1460-1060 (ISSN-L)
- 1758-7115
- OpenAlex
- W4401203858
- Cited by
- 142
- References
- 65
- Citations by year
- 2026: 58 · 2025: 74 · 2024: 10
- FWCI
- 20.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Journal of Innovation Management (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- generative AI, innovation, creativity, human-AI collaboration, AI ethics, responsible AI, algorithmic bias, privacy, business model transformation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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