AI & Machine Learning Projects: Client Expectations
AI/ML projects have characteristics that differ from standard software development. Understanding these sets realistic expectations.
AI Is Probabilistic, Not Deterministic
Unlike traditional software, ML models produce probabilistic outputs — they are right most of the time, not all of the time. This is inherent to the technology, not a flaw.
Data Quality Is Everything
The quality and quantity of training data determines model quality. The most common reason AI projects underperform is poor data. We conduct a data assessment before any ML project begins. Expect significant effort in data gathering, cleaning, and labelling.
Iteration Is the Process
AI projects are iterative. We build a model, evaluate it, refine the data or approach, and retrain. A first model version is rarely the production version — budget for iteration cycles.
The Right Metrics
We will discuss performance metrics with you in plain language. The right metric depends on your use case: for medical screening, missing a case (low recall) may be worse than false positives. We align on metrics before building.
Ethical AI
We assess every AI project for bias risk, transparency requirements, and fairness across user groups. We will not build AI systems we believe could cause harm or produce discriminatory outcomes.