Cambashi’s View: The Impact of AI on Computer-Aided Engineering and Simulation

Cambashi, with its associates, has completed an extensive market research study of the CAE simulation software market for emerging and start-up companies offering AI and Machine Learning (ML) infused CAE solutions. Over 120 companies have been identified globally and tracked. About half were founded after the COVID Pandemic of 2019-20. The release of ChatGPT in 2022 enabled a substantive shift within the CAE landscape as a surge of start-up companies hit the market at an average rate of ten per year.

Fastest Growing Segment

CAE simulation leads all manufacturing software with a CAGR of ~10%.

10–1,000x Speedups

AI start-ups claim dramatic speedups by compressing existing CAE simulation workflows

120+ AI Start-ups

Cambashi tracked 120+ ‘AI for CAE’ companies globally — EMEA 51%, AMER 35%, APAC 14%.

Design Space ROI

AI accelerates early-stage Design Space Exploration — where CAE delivers its biggest ROI

~$2.3Bn in venture capital has been invested in AI for CAE start-ups. Successful solutions address clear business needs through cross-functional workshops and pilot projects.

CAE/Simulation Software Growth – historic and projected 

The chart shows CAE/Simulation Software Growth from 2023 to 2030. It is consistently the strongest out of all the engineering/manufacturing software segments that we cover. 

Until recently, CAE’s main use was to analyze new CAD-produced designs and provide virtual test environments – both extremely valuable functions. CAE is now being used within the design cycle to automatically produce ‘candidate designs’ based on constraints and design space optimization. 

Traditional workflows in CAE require numerical solvers such as Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Computational Electromagnetics (CEM), Model Based System Engineering (MBSE), and Multibody Dynamics (MBD) to simulate and analyze highly complex product engineering designs using multi-physics simulations. Depending on the complexity of the product design process – and the computational resources available – CAE simulations typically take from a few minutes to hours, days, or even weeks just to achieve one simulation, never mind a complete design space exploration.

The AI for CAE Start-up Landscape

120 start-ups tracked by region. EMEA leads with hubs in London and Berlin. PhysicsX raised $300M Series C at a $2.4Bn valuation. AMER clusters on both coasts with the highest VC funding per company. APAC hubs in Seoul, Tokyo, and emerging Indian players.

Automotive (34%) and Aerospace & Defense/Marine (26%) are most advanced. Emerging niches include Med Tech, Manufacturing Shaping Processes, and AECO.

9 Key Trends in Industrial AI for CAE

The emergence of ‘AI for CAE’: Challenges, Trends, and New Market Entrants

For detailed analysis and market insights, download our latest Cambashi’s View: The Impact of AI on Computer-Aided Engineering and Simulation.

Table of Contents:
Executive Summary — p. 2
How AI Startups Are Transforming the CAE Sector — p. 2
CAE/Simulation Software Growth – Historic and Projected — p. 3
Emergence of a Wave of Industrial AI for CAE Start-Up Companies — p. 5
Key Trends in Industrial AI for CAE — p. 8
Engineer Productivity
Design Space Optimisation
Accelerating Engineering Simulation Outputs
Machine Learning, Surrogate and Reduced Order Model (ROM) AI
Workflow Automation
Software Development & Validation
Knowledge Capture & Reporting
Key Challenges for Industrial AI for CAE and Potential Solutions — p. 9
Trust & Adoption Barriers
Integration & Interoperability
Upskilling the Workforce
Pilot Projects and Dedicated AI Resources
Key Future Trends — p. 10
Multi-Physics Simulation & Digital Twins
Autonomous & Agentic AI: Realistic Expectations
Coupling Physics Types for Near Real-Time Simulation
Convergence of EDA, CAE & PLM
Democratisation of CAE
Regulatory Compliance & Verification
Data Sovereignty & Geopolitics
CAE for Large Mechanical Models (LMMs)
AI as a Force Multiplier for CAE Growth
Conclusions — p. 12

Download our recent “Cambashi’s View: The Impact of AI on Computer-Aided Engineering and Simulation”


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