No Bullsh!t Leadership Moment 165. How To Avoid Expensive Tech Project Failures
Mar 22, 2026
A clear look at why AI and tech projects so often miss cost, time and functionality targets. Discussion covers industry low standards, inexperienced project staffing, and the intangibility of software. Problems like excessive customization, scope creep and weak accountability get called out. Practical signposts point listeners toward how to secure ROI on tech investments.
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AI Projects Rarely Deliver Promised Results
- Most AI and tech projects fail to meet cost, time, and functional expectations despite huge spending.
- Martin G Moore cites Gartner, McKinsey, and Accenture stats showing low delivery rates and poor productivity gains for AI investments.
No Standards Have Left IT Fragile
- The IT industry suffers from a lack of consistent professional standards and low barriers to entry.
- Martin G Moore argues this problem has persisted for 50 years and undermines large commercial tech projects.
Inexperience Is Built Into Outsourced Projects
- Organisations lack in-house experience because they seldom run large-scale tech projects and outsource them.
- External firms often staff projects with young, inexperienced people who are still building capability.