Most AI tools will not exist in three years. The economics are brutal: Stanford HAI data shows enterprise AI spending has quadrupled while startups burn through cash twice as fast as a decade ago. Here is how to spot which ones survive and avoid betting your operations on doomed solutions.
Most AI vendor evaluation checklists obsess over model capabilities while ignoring what actually determines success: whether the vendor picks up the phone when your implementation breaks at 3am. RAND Corporation research shows more than 80% of AI projects fail, and 85% of companies miss AI cost forecasts by more than 10%.
When IDC data shows only 7% of organizations fully scale AI and up to 88% of pilots never reach production, the problem is not the technology. Most AI implementation checklists evaluate features when they should evaluate support, infrastructure readiness, and team preparation.
Most AI RFPs collect marketing slides instead of testing real performance with your data. RAND found more than 80% of AI projects fail, often because procurement focused on credentials rather than capability. Here is a practical approach that evaluates vendors through hands-on proof of concepts using your actual data and workflows, not polished presentations.