The Purpose:

We asked engineering executives what challenges and costs they face when developing complex, non-linear products and the expected benefits of AI.

The Outcome:

AI is ideally suited to solve intractable physics of non-linear products by accelerating time to test data insights, reducing test costs, and speeding time to market.  

Findings:

Here are a few findings - pre-register in the form to get your copy:

• 71% need to speed new product development to stay competitive
• 67% feel pressure to adopt AI to avoid losing competitive advantage
• 63% risk delaying launch schedules due to too many iterations
• 57% say the #1 benefit in adopting AI is increased engineering productivity

*Survey responses from over 150 engineering executives at major automotive, aerospace and industrial companies in Europe and the U.S. 

• Challenges:
  • Agree or strongly agree
    • 75%: Speeding up the ideation and launch of new, complex products to stay competitive
    • 75%: Reducing the cost of design iterations
  • Very/extremely challenging
    
    • 54%: Knowing we can trust our data and that it doesn't contain measurement errors
    • 52%: Running a lot of tests but still not getting needed insights to design the product
• Expected benefits of adopting AI
  • 61%: Increased engineering productivity
  • 57%: Improved insights about testing processes
  • 54%: Less time calibrating complex physical models