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