From Conventional to Cutting-Edge: A Comparative Study of AI-Enhanced and Traditional Management of Innovation Projects

Abstract

Innovation projects increasingly rely on advanced technologies to remain competitive, with Artificial Intelligence (AI) emerging as a transformative tool in their management. While traditional approaches are grounded in human intuition and experience, AI offers data-driven support for tasks such as idea generation, resource allocation, and trend detection. This study aims to evaluate the impact of AI on the management of innovation projects and to compare AI-enhanced methods with traditional approaches across different project phases. A mixed-method research design was applied. First, a bibliometric analysis using the Web of Science database was conducted to identify leading research trends, institutions, and collaborations related to AI and the management of innovation projects. Second, a focused literature review of studies published between 2019 and 2024 examined how AI tools are being applied across various phases of innovation projects. The results indicate that AI significantly improves efficiency by automating processes, enabling earlier trend recognition, and supporting more accurate decision-making. However, its integration faces barriers, including technical complexity, data quality limitations, and ethical concerns. The study concludes that AI cannot fully replace human creativity and strategic thinking, but can effectively complement them. A hybrid approach, combining AI’s analytical capabilities with human judgment, is recommended for the management of innovation projects. Future research should focus on developing and testing such hybrid models, with attention to explainable AI, ethical decision-making, and the role of AI in supporting collaboration within geographically dispersed teams.