"The demo in a controlled environment wowed the executive committee, but scaling it on our legacy systems has turned into a financial wall."
The illusion of the "magic demo"
When a customer service AI assistant was launched, the POC was built in 3 weeks on a cleaned dataset. But when it was rolled out at scale on production systems, the project hit a dead end.
The POC "wow" effect. Instant success in a test environment with artificially prepared data.
The wall of reality. The model could not handle real production data: heterogeneous, unstructured and outdated.
Exploding hidden costs. The budget for data cleansing and access security spiraled.
The 4 forgotten pillars of AI industrialization
- Data quality and governance. A powerful model never makes up for fragmented or outdated production databases.
- Architecture & legacy systems. Connecting an AI component to legacy systems creates underestimated integration debt.
- Cybersecurity & compliance. Confidentiality, LLM data leakage and strict compliance with GDPR / the EU AI Act.
- Change management (FinOps). Controlling the cost of queries (API/GPU) and supporting business transformation.
of artificial intelligence projects never reach industrial production (Gartner).
average cost factor between building a POC and its secure industrialization.
"Building an AI POC takes 20% of the budget. The remaining 80% goes to systems integration, data quality and governance."
Over to you: what is the main barrier to industrialization in your organization?
The series "IT & AI: the reality on the ground"
Why 70% of IT projects driftEpisode 2
Generative AI and IT budgets: the "divided by 4" illusionEpisode 3
The "Fake Agile" trap and weak governanceEpisode 4
The POC syndrome: why 80% of AI projects failEpisode 5
The new execution contract: governance, capabilities and P&L
Digital, Data & AI Strategy
Data & AI roadmap, architecture choices, data governance and high-ROI use cases.
Fakhri Essedik
Founder of EDX Advisory
For more than 25 years, Fakhri Essedik has helped executive teams and CIOs steer major Digital, Data & AI programs across Europe, Africa and the Middle East.