The AI Blindspot Framework
9 categories. 54 blindspots.
The AI Blindspot Framework is the backbone of how AIBlindspot classifies real-world AI failures. Click any category to see its blindspots and recent incidents.
Business & Strategic
Blindspots in business strategy, ROI, market positioning, customer value, and investment prioritisation.
Explore BUS →
Operational Management
Blindspots in monitoring, incident response, performance, scalability, integration, and business continuity.
Explore OPS →
Human Factors
Blindspots in change management, skills, human-AI collaboration, trust, workforce, and culture.
Explore HUM →
Governance & Compliance
Blindspots in accountability, regulatory compliance, ethics, risk management, data governance, and audit.
Explore GOV →
Technical Implementation
Blindspots in integration architecture, deployment, performance, data pipelines, security architecture, and maintenance.
Explore TEC →
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Explore DAT →
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Explore SEC →
Environmental Factors
Blindspots in organisational culture, stakeholder expectations, resource allocation, market pressure, regulatory environment, and external partnerships.
Explore ENV →
Agentic & GenAI-Native
Blindspots in autonomous agent authority, delegated permissions, human interrupt, generative output accuracy, and prompt injection.
Explore AGT →