By Laura Cattaneo for Data Language only

Artwork by Laura Cattaneo for Data Language only

Artificial Intelligence Engineering Maturity Model

Stage 2: 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.

Capabilities required for this maturity stage

Media assets include structured, descriptive metadata

A working environment that fosters innovation

A safe environment to prototype new ideas using real data

Businesses may experience these problems at this stage

Innovation is slow and expensive

Suggested Interventions

Deliver a Linked Media Content Graph Platform

Create a Proof of Value prototype to test for value

Create a Proof of Value prototype to test for value

Data Scientist resource wasted on non-differentiating features

Suggested Interventions

Use SaaS to lower the Total Cost of Ownership (TCO)

Distraction caused by technology fads

Early Interest: Consideration of AI potential - Maturity Stage

At this maturity stage, a business is potentially in a mixture of states of mind. Some teams may be overly excited, and others cautious.

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.