Most artificial intelligence (AI) efforts fail. They don’t fail because of the tool, the core software, or bad data. They fail because they don’t integrate with business and wind up being more of a hindrance than a help.
This isn’t just an AI problem; it’s true of most forms of automation. Projects fail because the people building the solution have no clue about the actual goal, the nature and dependencies of their current operations, or even whether those operations are optimized. (In some ways that last one suggests an AI failure might be more beneficial – if you have a bad process in place, the last thing you want to do is speed it up!)
To achieve success, you first need to fix the process or operation, fully define it, set forth a set of achievable goals for the AI project and staff, and then execute on it. That’s why I’m fascinated by BCG, a consultancy that is increasingly focused on AI; its tactics evolved out of efforts to help companies improve operations with a strategic goal in mind.
