Engineering teams are undergoing far-reaching digital transformation in complex engineering and product lifecycle management, and generative AI can help. However, in engineering domains where accuracy and compliance are non-negotiable, and results must be correct, applying generative AI cannot be done naïvely.

Even a single wayward requirement can lead to costly rework, schedule delays and low-quality outcomes that can risk product and sometimes company viability. This is especially vital for safety-critical, regulated industries such as automotive, aerospace, or medical devices, where mistakes can impact product and business success. AI applications that lack enterprise-grade rigor or skip critical safeguards can undermine the promise of speed and automation they aim to deliver.   

Doing it right can lead to greater speed, clarity and build confidence for your engineering teams and stakeholders.