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AI Integration in Unmanned Aerial Vehicles: Key Challenges, Enabling Technologies, and Practical Solutions
Review Article  ·  Published: 20 April 2026
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ICCK Transactions on Applied Intelligence and Cybernetics
Volume 1, Issue 1, 2026: 67-95
Review Article Open Access

AI Integration in Unmanned Aerial Vehicles: Key Challenges, Enabling Technologies, and Practical Solutions

by
Waqas Haider Waqas Haider 1 ORCID
Yar Muhammad Yar Muhammad 2 * ORCID
Adnan Khan Adnan Khan 1 ORCID
Gul Zaman Khan Gul Zaman Khan 3 ORCID
Samreen Ihsan Samreen Ihsan 3 ORCID
1 Software Engineering Research Group (SERG-UOM), Department of Computer Science and IT, University of Malakand, Chakdara 18800, KPK, Pakistan
2 School of Computer Science and Engineering, Beihang University, Beijing 100191, China
3 School of Software Technology, Dalian University of Technology, Dalian 116000, China
* Corresponding Author: Yar Muhammad, [email protected]
Volume 1, Issue 1
Volume 1, Issue 1 2026
Received: 08 January 2026 Accepted: 23 March 2026 Published: 20 April 2026 CrossMark
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DOI: 10.62762/TAIC.2026.456667
ARK: ark:/57805/taic.2026.456667

Article Information

Published in ICCK Transactions on Applied Intelligence and Cybernetics
Volume/Issue Volume 1, Issue 1, 2026
Pages 67-95

Abstract

Over the last decade, Unmanned Aerial Vehicle (UAV) technology has rapidly developed by integrating AI tools and methodologies. UAVs are used across many fields, including wireless communication, logistics, agriculture, construction, security, and exploration. UAV systems are inherently complex and present numerous challenges. This study conducted a systematic literature review to identify the main challenges and the solutions researchers have proposed. A total of 141 research papers were collected and analyzed, with no restriction on publication year. The review identified 10 main challenges affecting AI in UAVs. These include problems with autonomous navigation, real-time decision-making, network and sensor limits, limited computational power, poor communication and coordination, high energy consumption, hardware and payload restrictions, security and privacy issues, path planning and collision avoidance, and limited battery life. In addition, the review identified over 100 solutions/practices, including lightweight AI models, improved communication systems, energy-efficient methods, and enhanced security measures. This review is useful for both researchers and practitioners. It clearly organizes the challenges and solutions, identifies gaps for future research, and offers practical ideas for building better UAV systems. Solving these challenges will make UAVs more reliable and effective in many sectors, leading to improvements in safety, productivity, and economic growth.

Graphical Abstract

AI Integration in Unmanned Aerial Vehicles: Key Challenges, Enabling Technologies, and Practical Solutions

Keywords

artificial intelligence unmanned aerial vehicles AI integration in UAVs systematic literature review challenges of AI in UAVs

Data Availability Statement

Not applicable.

Funding

This work was supported without any funding.

Conflicts of Interest

The authors declare no conflicts of interest.

AI Use Statement

The authors declare that no generative AI was used in the preparation of this manuscript.

Ethical Approval and Consent to Participate

Not applicable.

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Cite This Article

APA Style
Haider, W., Muhammad, Y., Khan, A., Khan, G. Z., & Ihsan, S. (2026). AI Integration in Unmanned Aerial Vehicles: Key Challenges, Enabling Technologies, and Practical Solutions. ICCK Transactions on Applied Intelligence and Cybernetics, 1(1), 67–95. https://doi.org/10.62762/TAIC.2026.456667
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TY  - JOUR
AU  - Haider, Waqas
AU  - Muhammad, Yar
AU  - Khan, Adnan
AU  - Khan, Gul Zaman
AU  - Ihsan, Samreen
PY  - 2026
DA  - 2026/04/20
TI  - AI Integration in Unmanned Aerial Vehicles: Key Challenges, Enabling Technologies, and Practical Solutions
JO  - ICCK Transactions on Applied Intelligence and Cybernetics
T2  - ICCK Transactions on Applied Intelligence and Cybernetics
JF  - ICCK Transactions on Applied Intelligence and Cybernetics
VL  - 1
IS  - 1
SP  - 67
EP  - 95
DO  - 10.62762/TAIC.2026.456667
UR  - https://www.icck.org/article/abs/TAIC.2026.456667
KW  - artificial intelligence
KW  - unmanned aerial vehicles
KW  - AI integration in UAVs
KW  - systematic literature review
KW  - challenges of AI in UAVs
AB  - Over the last decade, Unmanned Aerial Vehicle (UAV) technology has rapidly developed by integrating AI tools and methodologies. UAVs are used across many fields, including wireless communication, logistics, agriculture, construction, security, and exploration. UAV systems are inherently complex and present numerous challenges. This study conducted a systematic literature review to identify the main challenges and the solutions researchers have proposed. A total of 141 research papers were collected and analyzed, with no restriction on publication year. The review identified 10 main challenges affecting AI in UAVs. These include problems with autonomous navigation, real-time decision-making, network and sensor limits, limited computational power, poor communication and coordination, high energy consumption, hardware and payload restrictions, security and privacy issues, path planning and collision avoidance, and limited battery life. In addition, the review identified over 100 solutions/practices, including lightweight AI models, improved communication systems, energy-efficient methods, and enhanced security measures. This review is useful for both researchers and practitioners. It clearly organizes the challenges and solutions, identifies gaps for future research, and offers practical ideas for building better UAV systems. Solving these challenges will make UAVs more reliable and effective in many sectors, leading to improvements in safety, productivity, and economic growth.
SN  - 3143-0309
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -
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@article{Haider2026AI,
  author = {Waqas Haider and Yar Muhammad and Adnan Khan and Gul Zaman Khan and Samreen Ihsan},
  title = {AI Integration in Unmanned Aerial Vehicles: Key Challenges, Enabling Technologies, and Practical Solutions},
  journal = {ICCK Transactions on Applied Intelligence and Cybernetics},
  year = {2026},
  volume = {1},
  number = {1},
  pages = {67-95},
  doi = {10.62762/TAIC.2026.456667},
  url = {https://www.icck.org/article/abs/TAIC.2026.456667},
  abstract = {Over the last decade, Unmanned Aerial Vehicle (UAV) technology has rapidly developed by integrating AI tools and methodologies. UAVs are used across many fields, including wireless communication, logistics, agriculture, construction, security, and exploration. UAV systems are inherently complex and present numerous challenges. This study conducted a systematic literature review to identify the main challenges and the solutions researchers have proposed. A total of 141 research papers were collected and analyzed, with no restriction on publication year. The review identified 10 main challenges affecting AI in UAVs. These include problems with autonomous navigation, real-time decision-making, network and sensor limits, limited computational power, poor communication and coordination, high energy consumption, hardware and payload restrictions, security and privacy issues, path planning and collision avoidance, and limited battery life. In addition, the review identified over 100 solutions/practices, including lightweight AI models, improved communication systems, energy-efficient methods, and enhanced security measures. This review is useful for both researchers and practitioners. It clearly organizes the challenges and solutions, identifies gaps for future research, and offers practical ideas for building better UAV systems. Solving these challenges will make UAVs more reliable and effective in many sectors, leading to improvements in safety, productivity, and economic growth.},
  keywords = {artificial intelligence, unmanned aerial vehicles, AI integration in UAVs, systematic literature review, challenges of AI in UAVs},
  issn = {3143-0309},
  publisher = {Institute of Central Computation and Knowledge}
}

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CC BY Copyright © 2026 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
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