Data Quality & Lineage Risk
What is Data Quality and Lineage Risk?
Data Quality and Lineage Risk is the danger that an AI system will produce wrong, biased, or unreliable results because the data feeding it is incomplete, inaccurate, inconsistent, or poorly tracked.
Two things drive this risk:
1. Data Quality
If the data is wrong, messy, biased, outdated, or mislabeled, then the AI model will make bad decisions.
Gartner notes that poor data quality causes 80% of AI project failures and costs organizations millions annually.
2. Data Lineage
If you can't trace where data came from, how it changed, or who touched it, then you can't trust the model's output.
Elevate Consulting emphasizes that teams without clear lineage face AI systems that "simply don't work" thereby destroying trust.
Forbes adds that traditional lineage systems are no longer enough for AI because they lack the transparency and accountability that regulators now expect.
What does Data Quality & Lineage Risk Do?
Data Quality and Lineage Risk shows up when:
- AI models make decisions based on incorrect or inconsistent data
- You can't explain where training data came from
- Data transformations are undocumented
- Data sources conflict or do not match
- Bias enters the model through flawed datasets
- A model's performance suddenly drops and no one knows why
- Regulators ask for evidence that you cannot produce
Atlan highlights that AI-ready lineage must be complete, granular, and continuously updated to maintain trust and context.
Why it Matters for Executives?
Poor data quality and/or missing lineage can lead to:
- Wrong business decision
- Biased or unfair outcomes
- Regulatory violations, especially under EU AI Act Article 10
- Loss of customer and stakeholder trust
- Operational failures
- Inability to audit or defend AI decisions
- Major financial losses
This is one of the most common and most expensive AI risks.
Transparency Disclosure
All images and videos on this site were AI generated and/or are Getty licensed images that may have been AI generated. AI was also used to edit the content descriptions.
