Discover why most AI projects collapse before reaching production and how your organisation can build systems that deliver real ROI, not just hype.
This report explains the structural and strategic reasons why 88% of AI projects fail to reach production and provides a checklist for business leaders to ensure successful implementation.
Most failures are not technical but strategic. Common causes include poor problem definition, lack of cross-functional alignment, and "garbage" data quality rather than the model capabilities themselves.
No. It is written for business leaders (CEOs, Operations Directors, CFOs). It focuses on the investment, governance, and strategy required to make AI work, rather than code.
It is the mistaken belief that AI will instantly fix broken business processes. In reality, AI requires discipline; if you apply it to an inefficient process, you simply scale the inefficiency.
We move beyond the hype to build engineering-led AI solutions. We help you define the business case, integrate with legacy systems, and manage the full lifecycle from PoC to production.
Empower your business to move from hype to engineering reality. Ensure your next AI investment delivers a measurable return.
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