AI in Engineering

GD&T errors cause RFIs, scrap, and supplier friction. This guide compares 4 categories of AI tools—from drawing checkers to data extraction—to improve outcomes.

Only 5.5% of companies get real ROI from AI. McKinsey's data shows why: 20% of digital budget, agentic workflows, and senior ownership. Here's what it means for engineering leaders.

Learn the critical difference between passive LLMs (like ChatGPT) and active AI Agents. A practical guide for engineering leaders on automating workflows.

Explore the 2025 guide to AI DFM tools, comparing rules-based automation vs. AI to help your engineering team reduce ECOs, scale senior expertise, and accelerate development.

90% of leaders believe AI will outperform humans in drawing checks. Read the guide on integrating AI into your review workflow to cut cycle times and improve quality without replacing engineering judgment.

Compare the best AI tools for manufacturing drawing checks. From AI agents to CAD rule checkers, find the right software to automate reviews and catch errors early.

The 2025 Bond Report shows that some industry leaders are adept at artificial intelligence innovation much better than others, creating a widening gap between early winners and losers.

MIT's GenAI Divide report explained, with CoLab's analysis of what it means for engineering and manufacturing leaders.

Most enterprise AI projects collapse before they scale. Yet engineering leaders know AI adoption is no longer optional. The question isn’t if to deploy AI, but how to avoid the 95% failure trap.

Regardless of when tariffs stabilize, one thing is clear: some suppliers will see an influx of RFQs as companies look to either reshore or diversify supply chains.