Artificial Intelligence and Innovation Management
Conference Name:
International Conference on Artificial Intelligence, Digital Innovation, and Applied Research AIDIAR 2026
Author
Ahmed Youssef
ORCID:
Affiliation
Swiss International University (SIU)
Keywords
Artificial Intelligence, Innovation Management, Digital Transformation, Strategy, Creativity, R&D, Organizational Learning, Responsible AI
Received: 30 March 2026; Revised: 9 April 2026; Accepted: 29 April 2026; Presented at the conference: 2–3 May 2026; Available online: 6 May 2026; Version of Record: 6 May 2026.

Published by:
U7Y Journal – The Seven Continents Yearbook of Research (ISSN 3042-4399)
Abstract and Poster Explanation
This research explores the role of Artificial Intelligence (AI) within systematized innovation, meaning structured and process-driven improvement within enterprises. AI can support various areas of innovation, including idea and process generation, identification of trends and insights, design, research and improvement of goods and services, management of organizational knowledge, and the measurement and analysis of innovation.
The poster shows that AI is an enabler, meaning a system that supports an enterprise, as it offers organizations the ability to generate and evaluate new insights for innovation, practice, and idea generation within the context of improved flexibility, responsiveness to disruptive innovation, and support for emerging creativity. AI can improve the quality of knowledge, evaluation, and creative practice within the organization.
In the context of the above, it can be acknowledged that innovation management is a human-centered process and that creativity, judgment, ethical awareness, and the ability to respond to changing situations and understand context are of utmost importance. A key focus of this research is that AI should support and improve the work of innovation management and teams, and should neither replace nor substitute for these roles.
The poster identifies potential risk areas, including insufficient AI training data, limited explainability, bias within AI systems, and user inexperience, as possible barriers to effective use. When employed with transparency, quality control, and human decision-making, AI can reasonably be expected to assist in the areas outlined above. AI, when used through controlled and quality-guided efforts, can improve the process of innovation, understood here as systematized creativity, and the overall balance of the enterprise. Improved creativity, flexibility, and innovation within the enterprise can be achieved, provided that these computing-guided innovation efforts remain aligned with ethics and sustainable value creation.
U7Y ID:
5aed0f68-3d53-410f-91b0-d5ea71f854e8

