There is much confusion around two of the most exciting technologies in the software world: artificial intelligence (AI) and machine learning (ML). However, automotive suppliers and aerospace and defense manufacturers must determine how to best apply them ― and to consider how the state of their factory data impacts the results.

This research report examines the difference between AI and ML and:

• Confirms the state of AI and ML in the industrial sector today
• Explains the correlation between AI / ML and enterprise performance 
• Describes why companies are falling behind with AI and ML, and the consequences of not catching up
• Illustrates what a data model is, and why it's critical for good outcomes using AI and ML
• Addresses how automotive and aerospace and defense companies should choose the right use cases
• Provides recommendations for companies considering AI and ML