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AI and Analytics in Augmented Reality Implementations

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Actionable Benefits

  • Understand AI and machine learning technologies and how they are used in augmented reality scenarios.
  • Align roadmaps with timelines around AI usage across AR use cases and processing location trends.
  • Formulate educated messaging around AI usage in AR for future use cases and enabling platforms and technologies.

Critical Questions Answered

  • How is AI being leveraged across the augmented reality market today and how is this impactful?
  • What novel AR use cases are made possible with AI?
  • How can AR-related data, such as spatial data, be used for analytics and processing in expert and recommendation systems?
  • Where is AI processing happening across local device and the cloud, and how does this location impact users and implementations?

Research Highlights

  • Analysis of eleven impactful use cases of AI in augmented reality across machine vision, prediction, and data processing.
  • Forecasts for AI chipsets in AR, AI active users for AR use cases, location of processing.
  • Recommendations for companies across the value chain to prepare for, implement, and extract maximum value from AI in augmented reality scenarios.

Who Should Read This?

  • AI chipset solution providers looking to understand the overlap between AI and AR.
  • Cloud service providers to identify AI and AR processing movement towards the cloud.
  • Software developers and systems integrators in AR that are implementing content and solutions that can and/or do leverage AI.

Table of Contents

1. EXECUTIVE SUMMARY

2. AI/ML VERSUS ANALYTICS

2.1. Foundational AI Terms

3. PRIMARY AI USE CASES AND VALUE

3.1. Machine Vision
3.2. Data Processing and Insight
3.3. Prediction
3.4. Looking Forward to Next Generation Applications

4. LOCATION OF AI PROCESSING

5. MARKET TRENDS AND FORECASTS

6. RECOMMENDATIONS