Elvitix warns that poor planning is the primary cause of most enterprise AI projects stalling, often resulting in significant financial losses. The firm unveils a practical three-step readiness framework to reduce risks and accelerate scaling.
LONDON, UK / ACCESS Newswire / November 10, 2025 / Elvitix, a data and AI consultancy, has issued a warning about the high failure rate of enterprise AI initiatives and unveiled a three-step readiness framework designed to prevent common and costly pitfalls.
Industry analyses, including recent figures from Gartner, indicate that nearly 80% of AI projects fail to reach production, resulting in average sunk costs of around €920,000. The financial drain typically comes from cloud expenses, duplicated data pipelines, and re-engineering efforts when pilots fail to transition into operational environments.
"AI projects often stumble because organizations start with the technology instead of the problem it is meant to solve," said Nicholas Perkins, CEO of Elvitix. "Our framework guides companies to ask the right questions first, invest early in data foundations, and ensure governance is in place so pilots can scale reliably."
Key Drivers of Project Failure
Many organizations underestimate the practical challenges of moving AI from pilot projects to production environments. As a result, several recurring factors repeatedly undermine progress and inflate costs.
Unclear Problem Definition: Many initiatives launch models, such as churn predictors or fraud detectors, without articulating the measurable business outcome they intend to achieve.
Weak Data Foundations: Inconsistent definitions, missing or duplicated records, and poorly integrated pipelines frequently derail promising pilots once they are deployed in real-world systems.
Gaps in Governance and Ownership: Without clear accountability for model retraining, data approval, and compliance oversight, teams face delays, increased costs, and operational bottlenecks.
Elvitix's Three-Step Readiness Framework
The framework, released as part of Elvitix's advisory offerings, focuses on three essential checks before scaling AI solutions:
Business Clarity: Defining a single, measurable business objective that the AI model must address.
Data Reality: Ensuring the necessary data sources are reliable, integrated, and production-ready.
Operational Maturity: Confirming that teams, processes, and governance structures are in place to keep models functioning effectively in production.
Elvitix reports that organizations applying this readiness lens reduce overspending and achieve faster time-to-value for their AI investments.
"The discipline of preparation not only prevents budget leaks but also accelerates progress," added Perkins. "By addressing the fundamentals first, companies move more confidently from pilot to production."
About Elvitix
Founded in 2019, Elvitix is a London-based consultancy specializing in helping enterprises adopt AI responsibly and efficiently by focusing on strong data foundations, clear governance, and practical scaling strategies.
Media Contact
Contact Name: Nicholas Perkins
Email: support@elvitix.io
Website: https://elvitix.io/
SOURCE: Elvitix
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