About Gary Segal
Helping organisations understand the structural risks hidden inside their data before those risks are amplified by AI, analytics and automation.
Experience across finance, data, systems and executive decision-making
Gary Segal works at the intersection of data engineering, business intelligence, inventory intelligence, governance and AI readiness.
A lifetime across data evolution
Gary’s experience covers the journey from manual accounting structures, spreadsheets, business intelligence and data warehousing through to modern AI-driven platforms.
This long-view perspective helps identify where systems process information correctly but fail to structure it for better decisions.
The Dirty Data perspective
Gary challenges the assumption that clean data is enough. His central argument is that without proper segmentation, governance and structural integrity, even clean-looking data can lead to poor decisions.
His work is aimed at executives who need clearer thinking, better questions and stronger foundations before investing further in AI.
Executive advisory focus
- AI risk assessment
- Dirty data exposure
- Data governance and ownership
- Segmentation and inventory intelligence
- Executive decision integrity