New Report:
State of AI In Engineering 


forrester vince pre order report with monolith stats 3

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.  


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. 

forrester report landing page with monolith
  • 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

Who should read this report?

Engineers spending time doing repetitive, costly & time-intensive tests

Engineers working on cutting edge projects and products in engineering R&D

Engineers who want to test less, learn more, and explore their test data

Anyone interested in using self-learning models for complex systems

Pre-order now: