Engineering firms fail to achieve desired productivity gains from AI despite 93% of leaders expecting improvements. Only 3% report realizing significant gains. Organizations utilizing cloud-native simulation show greater confidence in meeting AI goals within a year. Barriers include siloed data and legacy tools, with over half stating these as major challenges. Many CTOs perceive resistance to AI adoption, though engineering teams show less resistance. AI is anticipated to drive innovation, productivity, and expedite market entry, though reduction in costs is seen as a lower priority.
Engineering leaders see the potential of AI - but knowing isn't doing. The challenge is no longer about believing in AI's promise, but about overcoming the very real systemic blockers that stop teams from scaling it successfully.
According to the State of Engineering AI 2025 report from SimScale, organizations using cloud native simulation tools are twice as confident about achieving their AI goals within the next 12 months.
The biggest barriers to achieving AI ambitions are siloed data and legacy tools, with more than half (55%) citing siloed data and 42% legacy desktop CAE tools as major blockers.
AI is seen by engineering leaders as a growth driver, expected to fuel greater design innovation (54%), engineering productivity (51%), and faster time to market (47%).
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