Cambashi attended ASSESS 2026 in Atlanta, Georgia (11–13 March 2026), the premier C-level conference bringing together engineering simulation end-users and industrial software leaders. This year marked the beginning of a new era for ASSESS under the leadership of Nick Appleyard, with a sharper focus on the practical experience of industry users compared to the more academically oriented format of previous years.
Cambashi was represented by Keith Hanna and Petra Gartzen. As an independent market research and analyst firm Cambashi was able to provide a distinctive, independent, perspective on the conversations shaping the near-term future of the mechanical CAE and simulation software market.
Who Was in the Room
Of approximately 70 attendees, around 60% were senior-level practitioners from major commercial end-users — such as Heads of Engineering Simulation and CTOs. Companies represented included Caterpillar, Ford, Boeing, Nike, Cummins, Procter & Gamble, John Zink and Koch Engineering, among others. Representatives from the major PLM and simulation vendors — Synopsys, Siemens, Dassault Systèmes and Cadence — attended alongside a growing contingent from AI-for-CAE companies such as Synera, Rescale and ESTECO. A presenter from McKinsey and a journalist from Desktop Engineering completed the picture.
The seniority and commercial depth of the end-user representation made this one of the most practically grounded simulation industry events of the year.
The Dominant Theme was: AI — Pressure From the Top Down
The preoccupation with AI adoption was unmistakable throughout the event. In the opening afternoon’s roundtable, it was the overwhelming topic raised again and again by attendees. The pattern is consistent across the industry: CEOs are pushing AI mandates down to CTOs in major manufacturing organisations, asking them to identify where AI can deliver measurable productivity gains in engineering simulation workflows.
Cambashi’s analysis, as presented at ASSESS, is grounded in a rigorous view of where AI genuinely changes outcomes — and where the hype exceeds the reality. Several key conclusions emerged from the event that reinforce and extend Cambashi’s existing research:
AI will deliver its clearest near-term value by making existing simulation engineers more productive. Skilled simulation engineers are expensive and difficult to find. AI tools that accelerate pre-processing, geometry creation, meshing and post-processing deliver immediate ROI without requiring a fundamental redesign of workflows. This is where the most credible value lies today.
Democratisation of CAE remains a goal more than a reality. In a session chaired by Cambashi, it became clear that only around 5% of companies have achieved any meaningful democratisation of simulation tools, and even fewer companies are actively pursuing it as a formal strategic goal today. The barriers are largely human rather than technical: senior simulation specialists can be resistant to changes that reduce their controlling status within organisations, while junior designers fear making costly errors with complex, high-stakes software. AI agents that encapsulate best practices and deliver reliable results for less experienced users represent the most credible path to changing this — but the cultural transformation required should not be underestimated.
Multi-physics simulation and digital twins represent the most compelling longer-term AI opportunity. The real world is multi-physical, and AI has the potential to serve as the connective tissue that makes concurrent, near-real-time multi-physics simulation practical at scale — something that has been a theoretical aspiration for decades. Combined with increasingly mature digital twin architectures, this is the area where AI could most fundamentally change what engineering simulation software delivers.
Physics AI engines remain subject to well-founded scepticism among experienced practitioners. One expert with four decades in the CAE industry, observed at ASSESS that AI represents the most significant disruption to the sector he has witnessed — yet he shares Cambashi’s cautious position on claims that AI will replace established physics-based solvers. The empiricism and complexity inherent in high-end MCAE make a wholesale AI substitution for these tools highly unlikely in the foreseeable future. The most effective results today come from AI algorithms applied to a combination of real measured data and virtual MCAE simulation outputs.
One of the most informative presentations at the conference, in Cambashi’s assessment, was delivered by Professor Gary Fedder of Carnegie Mellon University, whose keynote set out both the theoretical foundations and practical guardrails for applying AI in physics-dominated, highly regulated engineering domains. Gary observed that the release of ChatGPT in 2022 was a ‘tectonic plate shift in AI and engineering simulation’ and ‘MCAE in particular will never be the same again’. Indeed, some older CAE practitioners noted that AI is the biggest disruption – for the good – to the CAE Software industry in the last 40 years.
Consolidation and Customer Frustration With Pricing
A session on the cost of simulation surfaced significant tension around software pricing in the wake of recent major acquisitions. Senior end-users from organisations were direct: in their experience, acquisitions results in higher software costs and reduced quality of service. A strong preference was expressed for focused, dedicated simulation companies over large conglomerate vendors — a finding with direct implications for how the newly formed Big 3 (Synopsys/Ansys, Siemens/Altair, Cadence/Hexagon D&E) manage and develop their acquired portfolios over the coming years.
Further Reading
- Cambashi’s View: Mechanical CAE and Simulation — Review of 2025 and Opportunities in 2026
- CAE/Simulation Market Observatory
- Request a sample or briefing
Cambashi is a global market research, industry analysis, consulting and training firm focused on engineering and industrial software markets. For over 40 years, Cambashi has delivered objective market intelligence to software vendors, investors and industry stakeholders worldwide. 80% of leading BIM and manufacturing design and engineering software vendors rely on Cambashi data.