Most AI budgets focus on software and infrastructure while ignoring the massive human time investment. RAND research confirms more than 80% of AI projects never reach production, and 85% of organizations misestimate project costs because they do not count employee hours, integration work, productivity losses, and opportunity costs. Here is a framework for calculating the true total cost of AI implementation.
Traditional project budgeting assumes you know the outcome before you start. AI budgeting assumes you will discover the outcome through iteration. RAND research shows more than 80 percent of AI projects fail because of this mismatch. Here is a practical framework mid-size companies can use to budget for AI projects without setting money on fire.
MIT research shows 95% of generative AI pilots fail to achieve results. When they do, most companies bury failures instead of extracting lessons. A structured post-mortem process paired with proper iteration budgeting transforms project failure into organizational knowledge that prevents repeating mistakes.