Development of innovation projects based on the synergy TRIZ principle and AI technology - Bushuyev, Sergey; Bushuyeva, Natalia; Puziichuk, Andrii; Bushuiev, Denis (Technology audit and production reserves, 2025)
The object of the research is a novel development methodology for innovation projects that leverages the power of the synergy principle of the Theory of Inventive Problem Solving (TRIZ). It integrates artificial intelligence (AI) technology. The problem addressed in this research is the inefficiency and limitations of traditional methods for development innovation projects, which often fail to comprehensively evaluate their potential, risks, and alignment with future technological trends. The research results in the synergistic application of TRIZ principles and AI technology for conducting comprehensive audits of innovation projects. By integrating the structured problem-solving framework of TRIZ with the analytical power of AI, a novel approach is proposed to enhance the evaluation and optimization of innovation initiatives. The paper explores how artificial intelligence algorithms can be used to analyze project data and identify potential obstacles and opportunities based on the principles of TEDx. As well as to create alternative solutions and predict possible outcomes, help identify synergies between different project elements and external factors. And to constantly monitor and adapt the innovation process based on real-time data and AI-driven insights. The difference in the research is the integration of TRIZ principles into auditing innovative projects using AI systems. The presented case showed the effectiveness of the proposed conceptual, mathematical and process models of auditing innovative projects. The master’s program in artificial intelligence implemented at the Kyiv National University of Construction and Architecture (Ukraine) was chosen as an example for the case study. The study demonstrates the potential of this audit-integrated approach to improve the success rate of innovation projects by providing more accurate assessments, identifying hidden opportunities, and facilitating proactive decision-making. This research contributes to more effective and successful innovation projects by providing a data-driven and intelligent approach to project development and improvement. Within the framework of the considered case, an assessment of the acceleration of analysis and decision-making processes was carried out using the example of the innovative development program for training masters in artificial intelligence. It was found that the analysis and decision-making processes are implemented 2.68 times faster without loss of decision quality.