Future of Mobile App Development: AI Agents, Edge AI, Spatial Computing, and On-Device AI

Google's current Android guidance similarly highlights the ability to choose between on-device, cloud, and hybrid inference depending on the complexity and requirements of the feature.

Edge AI Will Reduce Latency

Edge computing extends AI processing beyond centralized cloud infrastructure.

Instead of sending every request to a distant data center, selected workloads can execute closer to the user or device.

This matters for applications where milliseconds affect the user experience.

Potential use cases include:

• Real-time computer vision
• Industrial mobile applications
• Autonomous systems
• Voice interfaces
• Augmented reality
• Connected vehicles
• Healthcare devices
• Retail applications
• Smart infrastructure

Edge AI can also reduce the amount of raw data sent to centralized infrastructure.

For example, a camera-enabled application could perform initial object detection locally and send only relevant metadata or selected frames to the backend.

This can reduce bandwidth requirements while improving responsiveness.

AI Agents Will Need Stronger Mobile Security

More capable agents also create a larger security surface.