Use of Machine Learning in Economic Research

Does your company feel the need to be more organised and productive? Do you wonder how you could implement and use information technology in business? Then article is for you – it will discuss some relevant IT topics and even share with you how to stay focused. 

Today, we use information technology regularly in our daily life, work, and school, but there is more to it than that. Artificial intelligence has been on the rise for some time now. It is revolutionising the way we do business. As of 2021, 86% of CEOs note that AI is the chief support in their offices. The usage varies from predicting customer behavior to reducing data entry to even doing economic research. It is becoming fundamental in remarkable ways.

Current uses of ML in business

Artificial intelligence and machine learning are part of computer science that are correlated with each other. Companies are using them for creating intelligent systems. Both are different terms. AI creates intelligent machines that can stimulate human behavior, but machine learning gets machines to learn from data, without being programmed. AI is in charge in multiple places such as Siri, Google’s AlphaGo, AI in Chess playing, etc. Based on the capabilities we currently have, its weak, but the future is for the strong – AI will be more intelligent than humans. 

Thus, artificial intelligence will allow machines to replace workers, and achieve higher economic growth. The new research technologies may make computers and robots replace labour and dramatically impact production. 

Economic research

Economic research is now interested in the science of machine learning and artificial intelligence. We can identify four main areas here: forecasting and predictions such as ADAM algorithms used for deep learning, sentiment analysis and Natural Language Processing (NLP) which might help to improve the accuracy of standard statistical methods, image processing, and computer vision, and process automation and optimization. In literature, we can find papers dating back to 1991 stating that an algorithm is designed to reproduce human behavior and that we can make artificial learning agents and use their rationality to replicate human behavior. In the following, we will see many other areas where machine learning is used to improve economic growth. 

  • Sales

Automation AI is affecting sales today and it will continue to do so in the future. A study done by Harvard Business Review shows that companies using AI for sales can increase their leads by more than 50%, reduce call time by 60-70%, and have cost reductions of 40-60%. Given all these numbers, it is relevant for businesses – they should look into AI.

  • Marketing

Aiming to improve efficiency and increase customer experience, marketing teams are quickly adopting intelligent technology solutions. There are quite some areas where ML methods are used successfully in marketing: more customised website experiences, push notifications, image recognition and SEO optimisation. Intelligent algorithms help in the personalisation of all of these mentioned above. 

  • Customer Support

Teams work hard to guarantee that consumers get a great experience with a company or service and even to tell others about it. The key element here is to quickly resolve issues – this makes customers happy. For bigger businesses, this may be challenging since more and more requests come in. Because of this, businesses are introducing AI into customer service teams to enhance the customer service experience. The few current uses of modern technology here are chatbots as front-line customer service agents, voice bots – listening to the caller, interpreting their mood, and detecting the problem. 

  • Accounting

Machine learning can improve accuracy and efficiency. Its activities include: uploading files, reading them, and classifying them in the correct accounting codes. This modern way of handling issues never sleeps, tires, or makes human errors! Some of the uses in the field of accounting: performing repetitive tasks like recording data, categorising transactions, reconciling accounts, entering and correlating data from scanned receipts and invoices to transactions, evaluating employee expense reports, and tracking pricing changes are just a few things that take up a lot of an accountant’s time. Companies are saved from mental overload and can focus their work on other tasks.

  • Human Resources

All of us have been affected by the COVID-19 pandemic. HR is in a different environment than they were before the virus. Remote workforces and virtual recruiting continue to expand in number. New platforms and technologies are here to stay competitive. Machine learning gives excellent advantage in human resources: to analyse candidate profiles, since many companies invested in this to help with the hiring process. HR managers can use this way to get potential candidates by past work experiences and interests and match them with the best roles.


Machine learning and artificial intelligence are revolutionising the future of doing business. Companies invest in intelligent technologies in all different areas of their companies: sales, marketing, customer support, accounting and human resources. Human efforts and errors are reduced and efficiency and productivity are increasing. We believe that companies at the forefront of AI will dominate the competition in the future. 

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