Billions are being poured into the “AI Gold Rush II,” yet the results tell a very different story: 85% of AI projects never deploy, and 95% fail to deliver business value. Even technologies labeled “fully mature”—like speech recognition—still stumble in everyday use. And when these same systems are pushed into mission-critical environments, the cracks quickly show. The problem isn’t just the AI. It’s the way we’re building Human-AI teams.

At RCS, our AI Engineering experts close that gap. By combining advanced AI/ML with proven Cognitive Systems Engineering, we turn AI capabilities into actual performance—systems people trust, understand, and rely on in real-world complexity. The result: faster decisions, fewer errors, and AI that genuinely helps instead of overwhelms.

Check out the full story to move beyond hype and finally unlock operational value from AI, this is where it starts.

In this episode of PTC TechVibe podcast, Bill Elm from RCS explains the hype around AI and why 92% of corporate AI projects fail to meet business objectives, and how AI engineering—not experimentation—can prevent costly failures. Bill explains how RCS’s analytic engineering process, Brittalytics, exposes hidden flaws that can cause these failures and how to avoid costly or dangerous system breakdowns.

The Carnegie Mellon University policy brief, emphasizes the altruistic nature of AVs compared to potentially selfish HVs.

However, real-world experiences with AVs challenge the envisioned benefits. A survey reveals concerns, with people expressing anxiety and distrust toward AVs, particularly in unpredictable pedestrian interactions.