5 Applications of Artificial Intelligence in Decision Making | Comidor

5 Applications of Artificial Intelligence in Decision Making

5 Applications of Artificial Intelligence in Decision Making 789 526 Comidor Low-code Automation Platform

The uncompromising competition of the business world forces 83% of companies to rely on the power of Artificial Intelligence solutions. Artificial Intelligence (AI) includes not only the automation of many recurring processes but goes further – it influences decision making. 

By eliminating human errors and analyzing vast amounts of various data quickly and constantly, AI equips businesses with a full range of information and provides structured solutions to arising issues. 

Let’s find out more about AI-driven decisions and 5 robust applications of Artificial Intelligence in decision making practice. 

What are Artificial Intelligence decisions? 

Businesses tend to choose solutions empowered with big data, Artificial Intelligence, or Machine Learning more and more often. 

Such solutions can aggregate data from various areas of the company’s operations, such as finance, accounting, customer service, and more.  

Professionals use this data to save costs, build growth strategies, streamline inner business processes, and enhance decision making initiatives. Combined with the flexibility of cloud computing, AI facilitates management, problem-solving, and strategic development.  

So, when is it worth implementing technologies based on Artificial Intelligence? The answer is simple: when you want specific processes in the company to be faster and more efficient and let qualified employees engage in more creative tasksRobotic Process Automation vs Artificial Intelligence | Comidor Platform

To leverage decision making with the help of AI and ML, you need to understand how it works in a simple manner:   

  1. Configure a required set of tools for data collection, synchronization, transformation, and analysis. 
  2. Tailor a rule or framework for data processing. 
  3. Receive an output, which you can use to decide on a particular case or solve an existing challenge.  

You can follow the system’s suggestions, or you can use the output within a decision making framework. Be it SPADE, Eisenhower matrix, integrative thinking, BRIDGeS framework, or any other, the process is empowered by data, which allows you to make more precise and valuable decisions. 

In this way, AI in decision making applies to anything from minor improvements in routine processes to complex problem-solving. 

5 applications of AI in decision making 

Here is a list of practical examples that can help you quickly take your business to the next level involving AI: 

1. Decisions in business operations  

Machine Learning algorithms come to the rescue in areas built on a constant flow of heterogeneous data, whether it is several financial reports, payrolls, procurement, the analysis of employee productivity, or predicting further churn rates.  

In short, AI takes over routine administrative tasks and changes the whole way of working. It gives employees and executives more space for making faster and relevant decisions. 

Also, the capabilities of AI go further and can interact with clearly figured data requiring a single set of indicators and ephemeral parameters that have not yet been formalized.  

According to Forbes, 95% of businesses still need to process the unstructured data somehow. This approach is appreciated in many operational processes.  Decisions in business operations | Comidor

Let’s view human resources as an example of decisions in business operations. In HR, the entry, categorization, evaluation of employees’ and applicants’ data is essential yet monotonous. The first stages of recruitment are usually challenging: defining a position needed for a department, figuring out all the candidate criteria and areas to cover, sourcing, selecting the first CVs, and so on. Here AI comes in hand. 

AI-empowered solutions help to facilitate the recruitment process, source better candidates, analyzes their interviews. Eventually, an HR team can make a robust decision of hiring a suitable candidate. 

Overall, AI, in terms of inner business processes, is able to leverage business intelligence and make a company data-driven in many aspects, including decision making. 

2. Complex problem-solving

The potential of AI in decision making is robust, but you can solve multilayer and complex problems, too. For this, you must remember that AI solutions depend on the data you have and the step-by-step process orchestration.  Complex problem-solving | Comidor

As an illustration, a company considers launching a new product and targeting it in a new market. Pretty complex, right? To walk from a concept to the first marketing campaign, a company needs to take dozens of decisions, prioritize, optimize, investigate, forecast, and experiment.

Artificial Intelligence here gathers tons of different data and conducts an interdisciplinary study. Eventually, there’s a way to leverage anything from product development stages to digital marketing approaches of product promotion. 

Also, it’s a way to optimize various types of predictions and risk management. For example, you can predict and optimize pricing with the help of AI tools.

3. Strategic changes 

AI allows better planning of production, managing all restrictions, reducing shortcomings in operations, and improving manufacturing. 

It also helps to anticipate and adequately plan product customization, enhance postponement processes, and maintain efficiency with high levels of customer satisfaction. Strategic changes | ComidorBesides, go-to-market and marketing strategies must be flexible due to the current competitive environment and market dynamics. AI can make those changes in strategy quicker and less harmful. 

Throughout the production chain, countless risks can impact the continuity of operations. Continuous improvement is a key aspect of AI software systems: having the capability to learn from the environment and prepare a new solution to the same problem is one of the primary advantages that AI offers to us.  

At the same time, you need to understand that the implementation of any advanced system must-have steps and a clear plan, and AI is no exception.  

4. Customer-related decisions 

AI can be valuable for customer service management, personalized customer communication, evaluation of customer behavior, predicting consumer trends and patterns.  

Today’s speech recognition equipment helps, in a significant way, to improve the customer experience. These systems provide customers with information about the status of their shipments, as well as establish conversations with them to manage unforeseen events, changes in last-minute deliveries, or incident management and feedback from them. Customer-related decisions | Comidor

Artificial intelligence enables automatic recognition and profiling of potential customers. For example, new customers can be identified and characterized based on predetermined profiles. Based on the analysis of this data, it is possible to predict the behavior of new customers and ways of attracting them. Also, advertisers use neuromarketing to influence the thinking and behavior of consumers.  

This can do wonders for your marketing department as it helps them understand the best ways to connect with your potential clients.   

For example, if you’re a SaaS company, it may give you insight into the fact that hosting educational webinars is a great way to attract and retain customers as opposed to social media advertising based on how the customers react.  

Using AI, you can decide on how to improve customer experience. All in all, Artificial Intelligence allows you to understand customers better and decide on which tactics to try. 

5. Performance assessment 

Firstly, it relates to people’s performance evaluation and afterward decisions. The employee performance review process is moving from every 6 or 12 months to ongoing. Despite this, the integrity of the employee evaluation process can be undermined by human error and potential biases. AI is capable of minimizing human errors and making employee performance data more transparent. 

AI can also recommend online courses, training, and development programs to employees based on their performance history.  Many People Management software vendors have added Artificial Intelligence capabilities to their performance monitoring softwarePerformance assessment | ComidorAnother point of performance assessment relates to marketing. With AI solutions, you can precisely evaluate which tactics work, which don’t. And then decide how to adjust them, what approaches to experiment with. 

Ultimately, assessing the performance of some aspects in business is a way to understand the entire company performance, its potential to grow, and which decisions should be made to leverage that. 

Sum up 

Artificial Intelligence adds to decision making a lot. It makes the process clearer, faster, and more data-driven. 

Empowered with AI, you can make small decisions on the go, solve complex problems, initiate strategic changes, evaluate risks, and assess your entire business performance. 

About author
Dmytro Zaichenko is a Digital Marketing Specialist at Railsware, a product studio helping people build great products. Apart from writing and networking, he’s a huge NBA fan.  

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