Early Integration of Deep Learning and Neural Networks in Startups: Towards Co-Evolutionary Intelligence and Sustainable Competitive Advantage

DOI

10.2991/978-94-6239-711-8_24How to use a DOI?

Keywords

Deep learning; AI; RNN’s; Co-Evolutionary Intelligence; Sustainable Competitive Advantage; Startups

Abstract

This study explores the early integration of deep learning and neural networks within startup environments, focusing on how these technologies can shape organizational intelligence and long-term competitiveness. The research aims to demonstrate the strategic value of embedding advanced AI methods from the inception of a startup, emphasizing the creation of data-driven decision-making processes. By adopting a qualitative and analytical methodology, the study examines how startups can leverage continuous data collection, neural network training, and context-aware intelligence to enhance operational efficiency and foster innovation. The importance of the study lies in highlighting the role of early AI adoption as a driver for adaptive learning, strategic foresight, and sustainable growth in rapidly evolving markets.

The study’s findings reveal several critical outcomes for startups implementing deep learning and neural networks. First, it enables the building of an institutional data memory, capturing and organizing knowledge for long-term use. Second, it enhances collective intelligence, improving collaborative decision-making and problem-solving across the organization. Third, it accelerates learning and adaptation, allowing startups to respond quickly to market shifts and technological changes. Finally, these capabilities contribute to achieving a sustainable competitive advantage, positioning startups to maintain resilience, innovation, and leadership in their respective industries.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial 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 license and indicate if changes were made.

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TY  - CONF
AU  - Yacine Boubakeur
AU  - Yamina Guerfi
PY  - 2026
DA  - 2026/06/24
TI  - Early Integration of Deep Learning and Neural Networks in Startups: Towards Co-Evolutionary Intelligence and Sustainable Competitive Advantage
BT  - Proceedings of the International Conference on Artificial Intelligence Applications in Business Administration in MENA Region (ICAIABA 2026)
PB  - Atlantis Press
SP  - 251
EP  - 263
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-711-8_24
DO  - 10.2991/978-94-6239-711-8_24
ID  - Boubakeur2026
ER  -