AUTOMATOR
DECIDER
Recommender
Illuminator
Evaluator
Algorithmic ad displays; personalized marketing offers; dynamic pricing engines
Automator
When AI has plenty of context, but a human touch is needed for execution…AI should decide, and humans should implement.
When there are multiple, repetitive decisions to be made, but AI is missing necessary context… AI should recommend, and humans should decide.
When inherently creative work will benefit from machine learning…
humans should leverage AI-generated insights.
When there’s not enough context, and the stakes are high…humans should generate scenarios for AI to evaluate.
Decider
RecommendeR
Illuminator
Evaluator
EXAMPLES
EXAMPLES
EXAMPLES
EXAMPLES
When AI has all the context and needs to quickly reach a conclusion…
AI should decide and implement.
EXAMPLES
EXAMPLES
EXAMPLES
EXAMPLES
EXAMPLES
EXAMPLES
Call center optimization (what to say and how); predictive maintenance
Promotional calendar creation; sales and operations planning
Product design based on customer usage; analyzing customer complaints for common issues
Store or plant network planning; digital-twin simulations for operations; large, seasonal promotions (holidays, for example)
Automator
When AI has all the context and needs to quickly reach a conclusion…AI should decide and implement.
Algorithmic ad displays; personalized marketing offers; dynamic pricing engines
Decider
When AI has plenty of context, but a human touch is needed for execution…AI should decide, and humans should implement.
Call center optimization (what to say and how); predictive maintenance
Recommender
When there are multiple, repetitive decisions to be made, but AI is missing necessary context…AI should recommend, and humans should decide.
Promotional calendar creation; sales and operations planning
Illuminator
When inherently creative work will benefit from machine learning…humans should leverage AI-generated insights.
Product design based on customer usage; analyzing customer complaints for common issues
Evaluator
When there’s not enough context, and the stakes are high…humans should generate scenarios for AI to evaluate.
Store or plant network planning; digital-twin simulations for operations; large, seasonal promotions (holidays, for example)
Examples
Examples
Examples
Examples
Examples
When AI has all the context and needs to quickly reach a conclusion…
AI should decide and implement.
When AI has plenty of context, but a human touch is needed for execution… AI should decide, and humans should implement.
When there are multiple, repetitive decisions to be made, but AI is missing necessary context… AI should recommend, and humans should decide.
When inherently creative work will
benefit from machine learning…
humans should leverage AI-generated insights.
When there’s not enough context, and the stakes are high…
humans should generate scenarios for AI to evaluate.