The impact of artificial intelligence extends far beyond the digital world, influencing our daily lives through cars, appliances, and medical devices.
Increasingly, engineers are turning to AI to enhance, validate, and streamline product design.

Pragmatic Adoption of AI

The use of AI in product engineering follows a disciplined and pragmatic path. Most companies in the sector are increasing their AI investments, but in a measured way. This approach reflects the typical priorities of engineers, where errors have concrete consequences ranging from structural failures to safety recalls, even endangering lives. The main challenge is realizing the value of AI without compromising product integrity.

Key Research Findings

  • Verification, governance, and explicit human accountability are mandatory. Product failures can lead to real-world risks. Engineers are adopting layered AI systems with distinct trust thresholds.
  • Predictive analytics, AI-powered simulation, and validation are the top near-term investment priorities. These capabilities offer clear feedback loops, allowing companies to audit performance, obtain regulatory approvals, and demonstrate ROI.
  • Nine in ten leaders plan to increase AI investments in the next one to two years. The focus is on optimization rather than innovation, with a short-term ROI-oriented approach.
  • Sustainability and product quality are the main measurable outcomes for AI in product engineering. These results, visible to customers, regulators, and investors, take precedence over competitive metrics such as time-to-market and innovation.