The Potential of Artificial Intelligence in Increasing Business Process Efficiency

Authors

  • Firyal Ayudhiya Hasanah Fakultas Ekonomi dan Bisnis Universitas Muhammadiyah Riau
  • Ririn Afrilia Fakultas Ekonomi dan Bisnis Universitas Muhammadiyah Riau

DOI:

https://doi.org/10.61166/interkoneksi.v2i2.26

Keywords:

Artificial Intelligence (AI), Efficiency and Business.

Abstract

Artificial intelligence (AI) is a simulation of human intelligence which is modeled in machines and programmed to think like humans. This article aims to determine the potential of artificial intelligence in increasing the efficiency of business processes. This article seeks to provide a comprehensive understanding of what the potential of artificial intelligence is in increasing the efficiency of business processes. This research method is literature research (library research) using a qualitative approach. Qualitative research is the focus of attention with a variety of methods, which include interpretive and naturalistic approaches to the subject of study. The result of discussing this article is that artificial intelligence has become one of the most transformative technologies in recent years. AI's ability to learn from data, recognize patterns, and make decisions independently has opened up new opportunities for businesses to increase efficiency and productivity. Artificial intelligence offers enormous potential to increase the efficiency of business processes. By leveraging AI technology, businesses can become more competitive, innovative and responsive to market changes. Artificial intelligence has enormous potential to revolutionize the way we do business. By automating tasks, analyzing data more quickly and accurately, and personalizing the customer experience, AI can help businesses become more efficient, productive, and competitive.

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References

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Published

2025-01-22

How to Cite

Firyal Ayudhiya Hasanah, & Ririn Afrilia. (2025). The Potential of Artificial Intelligence in Increasing Business Process Efficiency. Interkoneksi: Journal of Computer Science and Digital Business, 2(2), 177–184. https://doi.org/10.61166/interkoneksi.v2i2.26

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Articles