Multiple industry analyses find vendor quotes typically represent only 20–40% of true implementation costs — with nearly one in four organizations underestimating by 50% or more.3,4,5 Our calculator uses published research to show you the full picture.
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TrueAICost was built by Brian Crusoe — a manufacturing operations leader with 8+ years on production floors, a Lean Six Sigma Black Belt, and hands-on experience building data pipelines and analytics systems in food & CPG plants.
After watching vendors quote $200K for projects that actually cost $800K+, he built the tool he wished existed: an independent, research-backed cost calculator with no vendor commissions or referral fees.
Every number on this site is sourced from RAND, S&P Global, Gartner, McKinsey, and Stanford HAI — not vendor marketing.
Sources
1 Ryseff, J., De Bruhl, B.F., & Newberry, S.J. (2024). The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed. RAND Corporation, RR-A2680-1. “By some estimates, more than 80 percent of AI projects fail — twice the rate of failure for information technology projects that do not involve AI.” Based on interviews with 65 data scientists and engineers. rand.org
2 S&P Global Market Intelligence (2025). Survey of 1,000+ enterprises in North America and Europe. “The share of companies abandoning most of their AI initiatives jumped to 42%, up from 17% last year. The average organization scrapped 46% of AI proof-of-concepts before they reached production.” Via CIO Dive
3 Pertama Partners (2025). AI Total Cost of Ownership: Beyond the License Fee. “License fees represent only 20–40% of true AI costs… True AI costs typically run 2–5× the sticker price.” Industry procurement analysis. pertamapartners.com
4 Gowan, I. (2026). AI Integration Costs: The Hidden Expenses of AI Adoption. Opagio. “The licensing fee represents 20–30% of the total cost of getting AI operational.” Cites Gartner data showing 2.3× average budget overrun for AI projects. opag.io
5 Keyhole Software (2026). AI Software Development Costs 2026. Synthesis of 15+ industry reports (Gartner, McKinsey, a16z, Menlo Ventures) across 100+ enterprise organizations. Citing CIO.com survey: “Nearly a quarter of organizations underestimate costs by 50% or more.” Post-deployment lifecycle costs estimated at ~65% of total spend. keyholesoftware.com
6 Gartner (July 2024). “At least 30% of generative AI projects will be abandoned after proof of concept by the end of 2025, due to poor data quality, inadequate risk controls, escalating costs or unclear business value.” GenAI deployment costs range $5M–$20M. gartner.com
7 Gartner (June 2025). “Over 40% of agentic AI projects will be canceled by end of 2027, due to escalating costs, unclear business value or inadequate risk controls.” gartner.com
8 IDC survey of 1,000+ IT professionals and line-of-business executives (October 2024). 46% cited pricing unpredictability as a primary obstacle to generative AI adoption. Via CIO.com
9 Deloitte (2026). State of AI in the Enterprise, 7th Edition. Survey of 3,235 senior leaders across 24 countries. Organizations with ≥40% of AI projects in production set to double within six months, yet companies report feeling less prepared on infrastructure, data, risk, and talent. deloitte.com
10 Anaconda (2024). State of Data Science Report. Data scientists spend approximately 60% of their time on data cleaning and preparation. Corroborated by CrowdFlower/Appen surveys (2016–2023). anaconda.com