By Laura Cattaneo for Data Language only

Artwork by Laura Cattaneo for Data Language only

Artificial Intelligence Engineering Maturity Model

Stage 3: Operational: AI in Production with successes and challenges - Maturity Stage

A business has successfully moved an important AI capability into production at this maturity stage. The service is working, but might be more expensive than planned, and there are unforeseen challenges.

Businesses may experience these problems at this stage

Lack of engineering best practices for AI

Lack of automation for testing and deploying AI

Lack of governance and change management for AI

Struggling to run AI in Production

Experimentation: Hopeful in AI and its promise - Maturity Stage

At the AI Experimentation maturity stage, a business is "learning through doing" and trying new approaches. At this stage a business must work hard to avoid distractions and fads.

Emerging: AI Data Science and Ops Capabilities - Maturity Stage

At this maturity stage, AI is pervasively used for some business models, and there is an emerging data science and AI ops capability. There are still likely to be pain points around ML training overheads process inefficiencies.