When companies focus on practical, user-centered implementation, AI can stop being an experiment and start having a real impact.

Even as we emerge from generative AI’s tire-kicking phase, it’s still true that many (most?) enterprise artificial intelligence and machine learning projects will derail before delivering real value.

Although 95% of AI projects fail, research shows that successful initiatives focus on infrastructure. Top hurdles include poor integration, lack of skill sets, and difficulty building in-house AI ...

AUSTIN (KXAN) — Artificial intelligence is showing up in more places, from chatbots to image generators, and it is even changing how we work and create every day. However, while AI can be a powerful ...

R&D leaders constantly face a deluge of promising project ideas competing for limited resources. The overarching challenge is objectively choosing and justifying which projects to pursue, which is ...