Application of Artificial Intelligence in Pricing

Authors

  • Pál Danyi Budapest University of Technology and Economics

Keywords:

intelligent pricing, artificial intelligence, dynamic pricing, machine learning, deep learning

Abstract

THE AIMS OF THE PAPER

For the experts of commercial pricing, the re-discovery of Artificial Intelligence (AI) a couple of years ago raises the question of what this will bring in the next decade. Pricing robots have emerged recently. Media has increasing coverage on AI in pricing, whether it is in tourism, car sharing, apartment renting or commerce. The study summarizes the world’s current state, and what to expect regarding usage of intelligent algorithms in pricing in the next 5-10 years.

METHODOLOGY

In addition to a secondary research, an analysis was made to discover the opportunities of applying AI methods.

MOST IMPORTANT RESULTS

Based on the research we argue that significant changes can be expected in pricing. Data driven pricing extended with AI elements will spread not only among large companies, but also in SME sector. Primarily dynamic pricing, continuous tuning of prices, and even personalized pricing will be typical. Business process of pricing will also be automated, and we will bargain for the price of a product as part of a robotic process. AI will become the new norm in pricing soon, it cannot be neglected. Humans should not be ignored in the process, but win-win situation will be found with the use of AI.

RECOMMENDATIONS

It is worth starting to experiment with prices by applying AI, especially deep learning, because this will result in competitive advantage.

Author Biography

Pál Danyi, Budapest University of Technology and Economics

Associate Professor

Downloads

Published

2018-09-01

How to Cite

Danyi, P. (2018) “Application of Artificial Intelligence in Pricing”, The Hungarian Journal of Marketing and Management, 52(3-4), pp. 5–18. Available at: https://journals-test.lib.pte.hu/index.php/mm/article/view/1056 (Accessed: 25 November 2024).

Issue

Section

Papers

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