| dc.description.abstract | This study investigates the role of AI-powered self-assessment tools in enhancing innovation management for small and medium-sized enterprises (SMEs). The primary purpose is to provide SMEs with a cost-effective means to assess and develop their innovation capacities across eight key areas strategic orientation, innovation portfolio, innovation process, innovative talent and culture, innovation capabilities, technology adoption, strategic alliances, and innovation performance measurement. Utilizing a qualitative, exploratory approach, data was gathered through a Scopus database search and supplemented with relevant literature on AI and innovation management. Findings reveal that AI-driven assessments based on data analysis, pattern recognition, and predictive modeling significantly benefit SMEs by offering actionable insights and recommendations, enabling efficient decision-making, and promoting competitive dynamism. However, limitations such as data quality, algorithmic bias, and privacy concerns must be carefully managed to avoid potential risks associated with AI implementation. The study discusses the impact of AI on reducing the "innovation divide" by democratizing access to advanced innovation management tools, thus supporting SMEs in achieving strategic growth and market adaptability. This research concludes that AI-driven tools represent a valuable asset for SMEs, bridging gaps in consultancy access, and fostering economic inclusivity. | us_US |
