Engineering AI Is Redefining Product Design as Teams Test Nearly 4x More Design Options
New global study from SimScale finds organizations using AI with modern cloud infrastructure can evaluate significantly more design possibilities, helping teams iterate faster and bring products to market more quickly
MUNICH, March 24, 2026 (GLOBE NEWSWIRE) -- SimScale, the world's first AI-native cloud engineering simulation platform, today released its 2026 State of Engineering AI Report. The report reveals how AI is reshaping engineering design and simulation workflows as organizations face mounting pressure to innovate faster and manage rising product complexity, with many now embedding AI into core operations rather than treating it as a standalone tool.
Surveying 350 engineering leaders across the United States, United Kingdom, and Germany, the report finds that engineering teams using AI-enabled workflows generate nearly four times as many design variants per program as those relying on conventional approaches. Rather than simply accelerating existing workflows, AI is expanding the scope of engineering creativity, allowing teams to test more ideas, iterate faster, and identify optimal designs earlier in the development process.
"For years, AI in engineering was viewed primarily as potential," said David Heiny, CEO and co-founder of SimScale. "What we're seeing now is a shift from experimentation to scaled execution. Compared with our 2025 report, the share of organizations actively experimenting with pilots and running mature, scaled AI programs has nearly doubled, signaling a clear wave of adoption. The teams pulling ahead are not just adopting AI tools, they're embedding AI into real engineering workflows built on cloud-native platforms, expanding the design space in ways that simply aren't possible with legacy infrastructure. That's when you move beyond incremental efficiency gains and start seeing measurable impact on both innovation and commercial performance.”
Organizations making progress are not waiting for perfect data conditions. They are more likely to scale Engineering AI successfully when they have the right operational foundations in place. The report findings point to several defining themes shaping how engineering organizations are adopting, scaling, and operationalizing AI today:
Modern Infrastructure, Not Perfect Data, Unlocks Scale
- 75% of organizations with mature AI programs cite cloud-native infrastructure as a key enabler.
- 70% of respondents cite secure data governance and access controls as critical enablers of scaling AI initiatives.
The data reinforces what leading engineering organizations are already discovering: scale is less dependent on perfect data architecture and more closely associated with infrastructure readiness and governance maturity. The broader opportunity hinges on modernizing infrastructure so AI can deliver value within real engineering processes now, while data foundations continue to mature.
Engineering AI Is Creating Commercial Advantage
- Organizations using AI-enabled workflows reported an average 2.8x speedup in servicing simulation requests compared to conventional workflows.
- Organizations using AI-enabled workflows report request for quote (RFQ) and technical bid turnaround times approximately three times faster than those using conventional workflows
- Accelerating simulation turnaround and RFQ response times helps organizations respond to customer requirements faster and compete more effectively in time-sensitive markets.
Agentic AI is Becoming Embedded into Engineering Processes
- Across every major stage of product development, AI copilots are significantly more common than autonomous agents, with adoption ranging from 67% in requirements engineering to 76% in simulation/computer-aided engineering (CAE), while only about 10% reported deployment of fully autonomous AI agents.
- 87% of organizations have the necessary governance in place for AI to take autonomous pass/fail decisions at design gates, with 8% routinely adopting this practice. This trend indicates a widespread expectation of increasing autonomy of AI agents.
While adoption of AI in engineering workflows is accelerating, the data reveals that organizations are progressing deliberately when it comes to full autonomy. Copilots are becoming embedded in day-to-day engineering tasks, assisting with simulation setup, analysis, and workflow coordination. However, fully autonomous agents remain limited in deployment, reflecting the high-consequence nature of engineering decisions. In environments where product performance, safety, and compliance are at stake, maintaining human oversight and governance remains central, even as AI capabilities continue to mature.
Engineering AI Is Expanding the Design Space across Industries
- In Machinery and Industrial Equipment teams, 88% of organizations using AI workflows iterate daily or multiple times per day, compared with just 12% using conventional workflows.
- In Life Sciences and Healthcare teams, 64% of organizations using AI workflows iterate daily, while conventional workflows show virtually no daily iteration.
Across industries, the survey results show that AI-enabled workflows are significantly changing how quickly engineering teams can explore and refine designs. Instead of running simulations only periodically due to time and compute constraints, many teams can now iterate on designs daily or even multiple times per day. This faster pace of experimentation allows engineers to test more configurations, identify potential issues earlier, and converge on optimized solutions more quickly, expanding the practical design space within a single development cycle.
The full 2026 State of Engineering AI Report, including detailed findings and analysis, is available here.
Methodology
SimScale partnered with Global Surveyz to survey 350 senior engineering leaders at organizations with more than 1,000 employees across the United States, United Kingdom, and Germany. The survey was conducted in February 2026.
About SimScale
SimScale is the world’s first AI-native cloud platform for engineering simulation. Trusted by over 800,000 users globally, SimScale empowers engineering teams to innovate faster by exploring thousands of design decisions in seconds. By integrating Engineering AI workflows with high-fidelity CFD, FEA, Electromagnetics, and Thermal simulation in a single cloud platform, SimScale eliminates the constraints of on-premise hardware and software, helping customers engineer the irreplaceable. For more information, visit www.simscale.com.
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