A Comparative Study of AI and Low-Code Platforms for SMEs: Insights into Microsoft Power Platform, Google AutoML and Amazon SageMaker

Artificial Intelligence (AI) and Machine Learning (ML) have become critical tools for enhancing business efficiency and innovation, traditionally accessible only to large enterprises with specialized resources. However, the emergence of low-code and no-code platforms has democratized AI, enabling small and medium-sized enterprises (SMEs) to leverage these technologies without requiring extensive technical knowledge. This paper explores three leading low-code AI platforms—Microsoft Power Platform, Google AutoML, and Amazon SageMaker—highlighting their unique capabilities, strengths, and suitability for SMEs. Microsoft Power Platform integrates AI with business process automation, providing a versatile toolkit for app development, data analytics, and workflow automation. Google AutoML focuses on simplifying the creation of custom machine learning models, offering user-friendly interfaces for non-experts to develop and deploy image classification, natural language processing, and structured data models. Amazon SageMaker delivers a comprehensive ML lifecycle management system tailored to more technically skilled users, enabling complex model development and deployment at scale. Through a comparative analysis, this paper evaluates the usability, scalability, and cost-effectiveness of each platform, helping SMEs choose the most appropriate AI solution. Additionally, a step-by-step guide to setting up and deploying an image classification model using Google AutoML Vision is provided to demonstrate the practical application of AI for SMEs.