An article published on IBM’s Think website on October 20, 2026, looks at a type of artificial intelligence called decision models. The piece, written by Hannah Press, opens with a simple question: how many of the decisions you made today actually needed you?
The article says many choices at work are small and routine. Examples include which email to answer first and which request can wait.
Press adds a light personal example. She writes that choosing when to open her second Coke Zero of the day is, in her words, “a very important work decision.”
According to the article, AI is starting to take these kinds of routine decisions off workers’ plates.
How Decision Models Differ From Reasoning Models
For the past two years, AI companies have competed to build models that reason for longer. The goal of that work has been to solve harder problems.
The article says decision models do the opposite. Instead of working through a problem at length, they are built to answer quickly.
A decision model is given a question with a fixed set of possible answers. It then picks one of those answers.
The answer can take a few forms. It might be one option from a list, a point on a scale, or a simple yes or no.
The article is titled “The new-hire test for AI decision models.” It is divided into three sections covering where decision models came from, the stakes of small decisions, and when a model’s confidence can be trusted.
Confidence Scores and Human Review
Along with its answer, a decision model attaches a confidence score. This number shows how likely the answer is to be right.
Developers who use these models set a threshold for that score. The threshold works as a cutoff point.
When the confidence score falls below the threshold, the decision can be routed to a human. This gives a person the chance to review choices the model is less sure about.
The setup splits decisions between the AI and people based on how certain the model is. Choices the model is confident about do not need to go to a person.
One section of the article focuses on when a model’s confidence can be trusted. The routing system depends on that score to decide which choices go to a human.
As described in the IBM article, the final check comes down to the developer’s threshold. Any answer that scores below it can be passed to a person for review.
