The problem isn't the technology
Most AI projects fail before a single line of code is written. The failure mode isn't technical — it's organizational. Teams jump to solutions before understanding the problem.
We've seen this pattern dozens of times: a company reads about a competitor using AI, gets excited, hires a team or an agency, and starts building. Six months later, they have a proof-of-concept that nobody uses.
The questions that matter
Before any AI initiative, ask: What manual process are we replacing? Who benefits? How do we measure success? What happens if the AI is wrong 10% of the time? These questions seem basic, but they're almost never asked with enough rigor.