Research · Tech Industry & Practitioner
Back to sweepResearch sweep · deep · 2016 – 2026
Software Project Outcomes Over Time, and Is AI Improving Them
Software and IT project outcomes over time from July 2016 to July 2026 (biased to the latest year): baseline success/challenged/failure ranges across trusted longitudinal datasets (Standish CHAOS, Oxford Global Projects and Flyvbjerg, McKinsey, PMI Pulse), the drivers of outcomes (complexity, budget, domain, delivery methodology, sourcing), build-vs-buy and low-code/no-code commissioning choices (OutSystems, Mendix, Power Platform, Retool), and whether AI-assisted development (Copilot, Cursor, Claude Code, DORA and METR evidence) is yet improving delivery outcomes on traditional software projects that build ordinary systems rather than AI products.
- Claude Fable 5
- financial
- frontier
- academic
- vc
- blogs
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Synthesised 2026-07-24
Narrative
Longitudinal project-outcome datasets tell partly convergent, partly incompatible stories. Standish Group's CHAOS series, running since 1994, is still the most-cited baseline: the original 1994 sample found the overall success rate was only 16.2%, while challenged projects accounted for 52.7%, and impaired (cancelled) for 31.1%