Decision Intelligence vs. Decision Automation

The spectrum of Decision Intelligence (DI) extends over several levels of autonomy. With Decision Automation (DA), humans set up control tasks for autonomously operating decision processes.


Similar to autonomy levels required for assisted driving, the spectrum of Decision Intelligence (DI) spans several levels. With Decision Automation (DA), humans delegate the entire decision-making process to the machines.

The three levels of DI
  • Decision Support assists human decision-making with analytics and data exploration.
  • Decision Augmentation recommends decisions to be made and predicts future situations using analyzed data.
  • Decision Automation enables the machines to perform both the decision step and the execution step autonomously.

DA is one of many processes that DI can utilize to make daily decisions in the running of companies and organizations. The use of Artificial Intelligence, machine learning and process automation empowers users to make comprehensive and unbiased decisions based on existing data.

For tasks that the user would rather be carried out by using experience or cognitive considerations, support through analyses or data visualizations (Decision Support) is usually sufficient. For recurring processes, on the other hand, supplementary support (Decision Augmentation) is the optimal choice. In this case, the analyzed data is used to generate recommendations and predictions.

In other words, DA requires just minimal human involvement within the decision-making process. The machines perform both the decision step and the execution step independently. Of course humans maintain an overview and monitor for risks and any unusual activities whilst they regularly review the results in order to improve the system.

Finding the right level of automation

Automated systems are the fastest and most profitable solution for routine tasks in business and customer operations as well as in production. Programmed processes can execute schematic tasks and run error-free and without pausing. As such, automated decisions increase productivity while reducing risks and error rates within the decision-making process. They are most useful in situations where solutions to recurring management problems are required.

An efficient DI system will allow all three levels – support, augmentation and automation – to be selected. This gives users the chance to employ different levels of automation according to their skills and confidence in the technology.

Level of automation graph
Source: Lorien Pratt: “Link – How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World”

Another benefit is the ability to switch to a different level during an event of extreme changes in conditions. For example, during the Covid-19 pandemic the previous year’s data became unusable for predictions in most instances.

To get started with DI, it is best to categorize your business decisions by frequency and complexity using a matrix diagram of the three levels mentioned above. For the simplest and most frequent decisions the use of DA is suitable, while the most complex and least frequent decisions fall into the category of Decision Support.


We are the leading AI-based decision intelligence platform for effective, data-driven decision-making processes in companies. No more bad decisions!


We are at the brink of one of the biggest business transformations in history. Stay ahead in the decision-making game!

With your newsletter sign-up you accept our privacy policy.
You can unsubscribe at any time.

Book your demo

Lead, don’t follow! Schedule a free demo today and become an industry champion in the era of AI.

Book demo