Moment 165. How To Avoid Expensive Tech Project Failures - No Bullsh!t Leadership Recap

Podcast: No Bullsh!t Leadership

Published: 2026-03-22

What Happened

Martin Moore highlights the challenges faced by organizations adopting AI, noting that less than 10% of technology projects meet their original cost and time estimates. Despite the promise of AI, reports from McKinsey and Accenture show that 80% of AI projects fail to scale, with only 4% delivering noticeable productivity gains.

The lack of industry standards in IT projects is a significant hurdle, as the field has low barriers to entry and inconsistent professional standards. This has been a persistent issue over the last 50 years, affecting the outcomes of major technology projects.

Inexperience in handling large-scale tech projects is another problem, as companies often hire external firms that may assign inexperienced personnel to build their capability. This can lead to numerous complications during project execution.

The intangible nature of software makes it difficult to visualize and define the finished product. Many rely on the 'I'll know it when I see it' approach, which can complicate project completion and satisfaction.

Customization is a common pitfall, with companies believing they are unique, leading to excessive customization. This increases both complexity and cost, making it harder to learn from previous projects.

Poor scope control is a frequent issue, as project requirements are often discovered during the design process, resulting in scope creep. Unlike tangible projects, tech projects lack finite delivery parameters.

Accountability is a major problem in tech projects, as business leaders often delegate responsibility to tech teams without sufficient oversight. This results in weak project liaison roles and a lack of attention to project milestones, which can lead to project failure.

Martin Moore recommends listening to episode 363 for 10 strategies to increase the likelihood of tech project success. He emphasizes the importance of understanding these common pitfalls to become a more effective leader.

Key Insights

• Less than 10% of tech projects meet initial cost and time estimates, with only 4% of AI projects achieving noticeable productivity gains according to Accenture.
• The IT industry suffers from a lack of consistent standards and low barriers to entry, which have not been effectively addressed in over 50 years.
• Customization in tech projects increases complexity and costs, as companies often wrongly assume their needs are unique.
• Accountability issues arise when business leaders leave tech projects to IT teams, failing to assign strong liaison roles or monitor project milestones effectively.