Decision Making Artificial Intelligence
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Decision Making Artificial Intelligence

An adult makes around 35,000 decisions per day, on average. That is a lot, right? However, these decisions are not taken blandly. We consider several internal as well as external factors. Generally, we are driven by our current situation and environment, desires, emotions, previous experiences, etc. But we as human beings cannot analyze every factor. There comes a limit. We can never imagine a holistic picture of our choices in advance.  That is when decision-making artificial intelligence comes into play. AI (Artificial Intelligence) eliminates emotional behavior and considers all the information available while deciding.  

This blog will help you to understand Decision-Making Artificial Intelligence more clearly.  

 

What is Decision Intelligence?  

In simple words, decision intelligence (DI) is all about taking help from computers while making decisions relating to real-world based scenarios. It helps businesses consider the broader aspects of how a particular decision can impact a company. It helps them to process the available data rather than just storing it.  

For example, Robo-advisors help in bridging the gap between data analytics and decisions.  

 

How does Decision Intelligence work?  

By now, you might be intrigued to know the functioning of decision intelligence. This paragraph will satisfy all your curiosity.  

Decision Intelligence works on a decision-centric approach. It includes machine learning, deep learning, visual decision modeling, complex system modeling, predictive analytics.  

  • Machine Learning (ML):

    This algorithm observes the pattern of information and provides better suggestions for the same search in the future. For example, if any user tries to access the online banking facility from a suspicious IP, the system automatically decides on the necessity of additional user authentication.  

  • Deep Learning:

    In this stage, a decision machine considers past information and decisions to offer better new suggestions. For example, face recognition programs.  

  • Visual Decision Modeling:

    Though decision intelligence serves as a reliable starting point, decisions are still taken by the human resources of a company. Visual Decision Modeling helps humans in identifying the available options and their outcomes.  

  • Complex System Modeling  

  • Predictive Analysis

     The decision intelligence system is based on accurate analysis and prediction.  

 

Intelligence Decision-Making used across various industries  

Banking and Finance:  

  • In the finance sector, decision-making models analyze and suggest some winning strategies to clients, along with managing their online investment portfolio. Also, it helps banks to analyze and predict customers’ behavior and necessities before planning and customizing products and services for them.  

Retail:  

  • In the retail industry, pricing plays a key role. A fairly priced product can change the game for retailers and merchants. Based on several external factors such as consumers’ demand, expectations, trends, etc., decision intelligence helps them predict and set better prices, thereby optimizing the supply chain. 

E-Commerce:  

  • On e-commerce platforms, decision intelligence helps companies suggest better products to customers. They do so by giving insights into customers’ latest purchase patterns, their recent interactions with various brands.  

Real-estate:  

  • Decision Intelligence helps companies gather information relating to the measurement of land in acres, price comparison of neighboring lands, and future planning.  

Transportation:  

  • GPS is a notable example of decision intelligence. It helps its users decide the route by providing information relating to the fastest route available, traffic jams around various roads, etc.  

 

Conclusion  

In this fast-paced world where making better and faster decisions is the need of the hour, decision intelligence solutions not only help companies in unlocking the benefits of data but also help in analyzing the broader aspects of relevant information while taking up the next big step. 

 

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