From Consumer Insights to Product Launch: An AI-Driven New Product Development Framework for Food-Based SMEs in ASEAN

Abstract

Food-based small and medium-sized enterprises (SMEs) play a vital role in employment generation, local entrepreneurship, and inclusive economic growth across ASEAN. Despite their importance, many food-based SMEs continue to develop new products through intuition-driven decisions, competitor imitation, and limited consumer feedback, increasing the risk of product failure, weak product-market fit, inefficient formulation, food waste, and unsustainable business performance. This paper proposes a Food-Specific AI Stage-Gate Framework, a conceptual framework that integrates artificial intelligence (AI) into a simplified Stage-Gate new product development (NPD) process tailored to the context of ASEAN food-based SMEs. Using a literature-based conceptual approach, this study synthesizes recent academic research and credible institutional reports on AI adoption, food innovation, nutrition, food safety, innovation management, and SME digital transformation. The proposed framework consists of six interconnected stages: consumer insight discovery, AI-assisted idea generation, concept screening, prototype and formulation development, market validation, and product lifecycle learning. Across the innovation cycle, AI functions as a decision-support capability through social listening, review mining, generative ideation, concept scoring, cost simulation, nutrition estimation, demand forecasting, sentiment analysis, and lifecycle monitoring. The novelty of this study lies in the development of a Food-Specific AI Stage-Gate Framework that integrates AI-enabled decision support with five food-specific gate criteria: Quality, Food Safety, Nutrition, Operational Feasibility, and Financial Viability, thereby extending conventional Stage-Gate approaches to better reflect the requirements of food product commercialization in ASEAN food-based SMEs. The framework aims to reduce product failure risks while improving product success rates, shortening time-to-market, reducing food waste, strengthening customer retention, enhancing innovation capability, and supporting sustainable business growth. This study contributes both theoretically and practically by offering a structured roadmap for AI-enabled food innovation in ASEAN.