The State of Engineering AI 2025.

In-Depth Analysis: The State of Engineering AI 2025

SimScale’s latest report, The State of Engineering AI 2025—developed in collaboration with Global Surveyz—sets a valuable benchmark for understanding how artificial intelligence is being adopted in engineering.

Drawing insights from 300 senior engineering leaders across the UK, US, and Germany, the report covers a wide range of sectors including industrial machinery, automotive, electronics, life sciences, energy, and the built environment.

Expectations vs Execution

There’s strong belief in AI’s transformative potential:
93% of engineering leaders expect productivity gains from AI in design and simulation, and nearly a third predict dramatic improvements. This consensus—particularly strong in the UK—reflects growing confidence that AI will be central to future competitiveness.

But the present reality tells a different story.
Only 3% of organisations report meaningful productivity gains today. This reveals a clear “expectation-execution gap”, where strategic ambition is outpacing operational delivery.

What Sets High Performers Apart?

The top 3%—those already realising benefits—share several key traits:

• Cloud-native platforms: These firms have moved away from legacy, desktop-based CAE tools. Their data is centralised, open-standard, and accessible—enabling tighter AI integration.

• Embedded AI agents: AI is built directly into workflows, supporting design and simulation decisions as an active partner—not a bolt-on tool.

• Rapid deployment: AI tools are implemented quickly, allowing for early wins, iteration, and momentum-building.

• Infrastructure mindset: Engineering data and models are treated as critical assets—versioned, traceable, and portable.

Barriers to Adoption

The report identifies several systemic hurdles:

• Siloed data (55%) and legacy tools (42%) are the top technical blockers.

• A leadership disconnect may be present: while 42% of CTOs believe technical teams resist AI, only 29% of engineers report this—suggesting potential misperception within organisations.

What Engineering Leaders Want from AI

Beyond operational efficiency, AI is seen as a growth enabler:

• 54% cite design innovation

• 51% cite productivity

• 47% cite faster time to market

Interestingly, cost reduction ranks low—pointing to a capability-led approach over short-term savings.

Implications for the UK Engineering Sector

For UK firms, this report serves as both a warning and a roadmap.
Bridging the gap between ambition and execution will require:

• Embracing cloud-native tools

• Embedding AI more deeply into workflows

• Building scalable, well-governed data infrastructure

Those who act decisively may gain not just in productivity, but in the innovation edge that will define the next decade of global engineering.