Skip to content
Open access

Effects of implementing artificial intelligence in transport

Sep 2026 · Post–Soviet Continent · 0 citations · 2 references

TL;DR

The positive and negative effects of the implementation of artificial intelligence technologies in the transportation industry are analyzed, as well as prospects for further development in the context of digitalization and automation of transportation systems.

Abstract

Modern technologies are rapidly advancing, and artificial intelligence is becoming a key driver of transformation in the transportation sector. The implementation of AI leads to increased efficiency, safety, and environmental sustainability of transportation systems, but is also associated with a number of challenges and risks. In recent decades, the world has faced challenges associated with accelerating technological progress and development. Artificial intelligence (AI) has become a key factor in the transformation of various economic sectors, including transportation and logistics. These changes open up new opportunities for improving the efficiency, safety, and sustainability of transportation systems, creating a customer-centric industry, and ensuring individual mobility for all segments of the population, which is particularly important given the growing needs of society and businesses. This article examines the key implications of the implementation of artificial intelligence (AI) technologies in the transportation industry. It analyzes the positive and negative effects, as well as prospects for further development in the context of digitalization and automation of transportation systems.

Read PDF

Similar papers

Preprint Sep 2026

Artificial Intelligence as an Economic, Environmental, Geopolitical, and Social Transformation

The rapid development of artificial intelligence is often discussed primarily as a technological breakthrough. Such an approach is insufficient because AI is also transforming the allocation of capital, energy, natural resources, labour, and political power. Investment in generative AI and computing infrastructure is i...

Marcin Marciniak · 0 citations
Review Sep 2026

The Role of Artificial Intelligence in Enterprises and the Challenges Associated with Its Implementation

Artificial Intelligence has become a key driver of digital transformation and competitiveness in modern enterprises. Despite its growing adoption, many organizations continue to face organizational, financial, technological, and human-related barriers that limit the effective implementation of Artificial Intelligence....

Jakub Dębicki · 0 citations
Aug 2026

ՀՀ-ում արհեստական բանականության տարածվածության մակարդակի վերլուծություն

The research aims to uncover the depth of AI integration across different sectors and assess its potential impact on the country's economic development prospects, as well as identify the current baseline of AI application.

Շողեր Պյոտրի Պողոսյան · 0 citations
Aug 2026

Artificial intelligence as a driver of economic development for mining companies in modern conditions

The purpose of this study is to explore the potential of using Artificial Intelligence (AI) in the production processes of mining enterprises, identify the challenges and limitations that arise, and assess the opportunities for overcoming them. The article examines the benefits of implementing AI in mining operations,...

A. Balashov · 0 citations
Open access Oct 2026

The role of artificial intelligence in the modern Russian economy innovative development

Innovation is now not just one of the possible paths of development, but the main condition for the survival of any enterprise. The key factor that changes the paradigm of the innovation process is the ability to delegate routine operations. Previously, a significant portion of highly qualified employees’ time was spen...

V. Kurchenkov, Roman S. Zaitsev · 0 citations
#federated learning Review Open access Sep 2026

The Role of Artificial Intelligence and Digital Transformation in Smart and Sustainable Infrastructure Systems

Special emphasis is placed on the concept of explainable AI, human in the loop decision making, risk based asset prioritization and ongoing model validation as ways to provide public accountability and reliability in critical infrastructure sectors.

Marjan Sultana Nuha · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.