how artificial intelligence helps in decision making

How does Artificial Intelligence help In Decision Making?

Data-driven workflows must give way to AI-based workflows. Humans and artificial intelligence are processors with very different capabilities.

Advances in deep learning and machine learning have enabled machines to process and analyze information in ways we could never have imagined. Many companies have adapted to a "data-driven" approach for the decision-making process. Data can improve decisions, but it requires the right processor to get the most out of it. Many people assume the processor is human. The term "data-driven" also implies that data is selected and summarized for people to process. But to take full advantage of the value contained in data, companies need to merge artificial intelligence (AI) into their workflows. We need to evolve from data-driven workflows to AI-based workflows. Humans and artificial intelligence are processors with very different abilities.

AI makes it a powerful tool, which, when used in the right way, can radicalize decision-making and completely change the way we do business. This article examines how AI does it.

Bringing artificial intelligence to the workflow

We need to merge AI into the workflow as the primary data controller. For routine decisions that rely only on structured data, it's best to delegate decisions to AI. AI is less prone to human cognitive biases. Artificial intelligence has no problem managing thousands or even millions of clusters. And it is more comfortable working with nonlinear relationships, be they exponential, power laws, geometric series, binomial distributions, or others. This makes better use of the information contained in the data and is more consistent in its decisions. Python is considered the most widely used programming language for creating a chatbot, and with this, the person can be easily regarded as a certified chatbot developer.

Although humans are removed from this workflow, it is essential to note that mere automation is not the goal of an AI-based workflow. Sure, you can cut costs, but that's just an incremental benefit. The value of AI is making better decisions than humans can make on their own. This creates a radical improvement in efficiency and enables new capabilities. Sometimes, AI is the first to decrease the workload of humans. In other cases, human judgment can be used as advice for AI processing.

Artificial intelligence techniques expand and enrich decision support more and more through means such as coordinating data delivery, analyzing data trends, providing forecasts, developing data consistency.

Artificial intelligence in decision-making

Applying artificial intelligence to decision-making is undoubtedly not new. Recent advances have made artificial intelligence techniques accessible to the public, seen by the increase in the number of applications in intelligent decision support systems. Artificial intelligence is used in decision support for activities such as helping the decision-maker select actions in real-time and stressful decision problems; cut information overload, enable updated information and give a dynamic response with intelligent agents; allow the communication necessary for collaborative decisions and addressing uncertainty in decision-making problems.

Advances in artificial intelligence have made this goal a reality in many applications. These AI-integrated decision support systems, or for short IDSS (Intelligent Decision Support Systems), are increasingly used to aid decision-making in areas such as finance, healthcare, marketing, commerce, command and control, and cybersecurity. These systems use artificial intelligence tools to reason, learn, remember, plan and analyze. Artificial intelligence tools can extend human capabilities by detecting and selecting relevant information from extremely large and distributed data.

The goal of the following points is to highlight how AI is different in business and, in turn, could speed up decision-making.

Marketing decision-making 

In today's customer-driven market, the complexities involved in decision-making are increasing day by day. This includes understanding the customer's needs and wants and aligning products with those needs and desires. Controlling customer behavior change is critical to making the best marketing decisions. 

AI modeling and simulation techniques provide reliable insights into consumer personalities. This will help predict consumer behavior. By collecting real-time data, trend analysis, and forecasts, an AI system can help companies make effective marketing decisions.

Customer Relationship Management (CRM) 

Organizations can find the value of a consumer's life with the help of the AI ​​shopper personality model. It can help organizations manage multiple items. During a complex decision-making process, AI can efficiently manage and control several factors at the same time. Large amounts of data can be collected and processed in minutes while providing valuable business information. While humans face decision exhaustion, algorithms have no such boundaries, making AI-based decisions faster and better.


An expert system is a kind of problem-solving software that attempts to imitate the knowledge and reasoning methods of experts. This system uses expert thought processes to give data, including assessments and recommendations for your problem. This makes it easier to make the right decision and respond quickly when faced with issues and concerns.

Opinion Mining

Artificial intelligence was able to deliver reliable information to decision-makers. For example, in marketing, AI has provided businesses with valuable consumer information, improving their communication with consumers. It also helps retailers predict and respond to product demand quickly. To that end, opinion mining helps companies understand why people feel this way. When enough opinions are gathered and analyzed correctly, the information collected will allow organizations access and predict the concerns of the silent majority. Artificial intelligence has improved this process through automation, which is faster and more consistent, helping organizations make significant business decisions.

Social Computing

Social computing helps marketers understand the social dynamics and behaviors of a target market. Through artificial intelligence, they can simulate, analyze and ultimately predict consumer behavior. These artificial intelligence applications are used to understand and extract data from online social media.

 Moving from data-driven facts to artificial intelligence is the next stage in our evolution. Adopting AI in our workflows enables better-structured data processing and allows an individual to contribute in complementary ways. This evolution is unlikely to occur within the individual organization, just as evolution by natural selection does not occur within people. We will soon see the emergence of new companies that embrace both artificial intelligence and human contributions and merge them natively into their workflows. It is better to use the AI while taking major decisions for the company as it's possible to achieve business goals through this.
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