An AI-Assisted Framework for Improving Innovativeness in Small Businesses: A Human–AI Collaboration Perspective

Abstract

Innovation is crucial for small businesses to remain competitive and adaptable in dynamic markets. Recent advancements in AI, particularly machine learning and natural language processing, offer promising tools for enhancing product innovation. However, small businesses often face significant challenges in adopting AI due to limited financial resources, data infrastructure, technical expertise, operational and cultural barriers. This paper presents a novel and holistic human–AI-assisted product innovation (HAIAPI) framework designed to address these challenges by integrating an advanced large language model approach across four key stages of the product innovation process: (1) AI-augmented problem articulation, (2) human expert problem selection, (3) AI-augmented solution generation and (4) human expert solution selection. Through an in-depth case study of an Australian e-retailer, this paper provides practical insights into how AI can enhance problem articulation and solution generation, while human expertise ensures relevant problem and solution selection. The detailed instructions on implementing this framework, including Generative Pre-Trained Transformers prompts, for small businesses are supported by a comprehensive resource toolkit and checklist detailing necessary financial, technical and human resources. Last, three key principles of human–AI collaboration are synthesised, offering further actionable strategies for small business managers/owners looking to effectively integrate AI into their product innovation processes.