TL;DR
AI proposals usually get compared against doing nothing. Compare them against the real options instead: automate it, build it, buy it, hire for it, or wait.
What the paper develops
AI proposals are often weighed against doing nothing, rather than against everything else you could do instead. This paper puts all five options on the same page: automate, build, buy, hire, or wait. Each is compared on how it creates value, what it costs to run, how long it takes to produce evidence, how easily it can be undone, what it depends on, and what it risks. The aim is to pick the smallest credible move without mistaking novelty for fit.
What to do next
Judge automation, building, buying, hiring, and waiting against the same questions: what it is worth, what it risks, what capacity it needs, and how easily you could undo it. Do that before treating AI as the default answer.
Inside the white paper
- Why AI proposals get compared against doing nothing instead of the real alternatives
- One way to compare automating, building, buying, hiring, and waiting side by side
- What each answer commits you to after approval, and what would reverse it
Sources and notes
- Alex Singla, Alexander Sukharevsky, Bryce Hall, Lareina Yee, Michael Chui, and Tara Balakrishnan, "The state of AI in 2025: Agents, innovation, and transformation," McKinsey & Company, November 5, 2025. Verified July 7, 2026. mckinsey.com
- James Ryseff, "The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed: Avoiding the Anti-Patterns of AI," RAND Corporation, 2024. Verified July 7, 2026. rand.org
- Arun Chandrasekaran, "Why 50% of GenAI Projects Fail - And How to Beat the Odds," Gartner, January 26, 2026. Verified July 7, 2026. gartner.com
- NIST, "AI Risk Management Framework Core," excerpt from AI RMF 1.0, 2023. Verified July 7, 2026. airc.nist.gov
- Johannes-Tobias Lorenz, Joshan Cherian Abraham, Robert Levin, and Douglas Ziman, "From promise to impact: How companies can measure and realize the full value of AI," McKinsey & Company, April 24, 2026. Verified July 7, 2026. mckinsey.com