AI and Spatial Computing Applications

This unit examines the current landscape and capabilities of AI-driven spatial computing, surveying the evolution of technologies, categories of AI software, and real-world business applications including AR, autonomous systems, and enhanced user experiences. Students will assess business benefits, integration challenges, technology selection criteria, and future trends to prepare for hands‑on design and implementation in subsequent units.

Learning Objectives

• Analyze the evolution and categories of AI and spatial computing technologies and explain how they enable new business models and redefined customer engagement
• Evaluate real-world case studies of companies using AR, AI, and autonomous systems to identify business benefits, human impacts, and common implementation challenges, producing a written report with recommendations
• Apply technology-selection and integration criteria to develop a preliminary implementation plan for a given business scenario that addresses 3D needs, UX enhancement, interoperability, and risk mitigation
• Design and present a concise forecast that outlines future trends, ethical considerations, and strategies to mitigate technical and social challenges associated with spatial computing and autonomous technologies