AI Leadership Blind Spots: 5 Mistakes Executives Make with AI Investment

Most AI projects don't fail because the technology doesn't work. They fail because the project was never set up to succeed. The model was fine. The data wasn't. The use case was real. The scope wasn't defined. The pilot worked. Nobody planned for production.The failure pattern is consistent enough that it stops being surprising. What's surprising is how many organizations repeat it.

Ask a developer how much it costs to build an app and they'll say "it depends." They're right. They're also unhelpful. Here's what it actually depends on, and how to get a number before you get a sales pitch.