Artificial intelligence as a tool in academic incubators and accelerators Ref.No.SSTCRC2629
1. Introduction
Technological advances, like any other field of science, have also affected higher education, and it is predicted that in the future, it will not be possible to avoid the use of artificial intelligence in various university tasks, including the commercialization of academic achievements, which is known as the mission of the entrepreneurial university. Studies conducted in this field mainly reflect the applications of artificial intelligence in the field of education and, to some extent, in the field of research, and very few studies have paid attention to the issue of using artificial intelligence in the entrepreneurial university and the process of commercializing knowledge, including a study which deals with the use of AI in personalizing education and assessing students' strengths and weaknesses and adjusting course content based on it. A study examined the use of artificial intelligence in teaching, assessment, and management of student learning. A study emphasized the need to integrate artificial intelligence technologies in higher education. In another study, the use of artificial intelligence to complement the teaching process was examined, with the belief that it is a tool that can make education more efficient and personalized. Or a study that considered the use of artificial intelligence to lead to wider access to training courses and greater productivity for administrators and instructors.In addition to these studies, another group of studies has examined the use of artificial intelligence in starting businesses or managing different parts of a business, including two studies which examined the use of artificial intelligence in startups for greater innovation. Or a study which identified the use of artificial intelligence as a factor in enabling startups. A study studied the use of artificial intelligence in risk management. In short, it can be said that existing studies, such as scattered islands, have studied the use of artificial intelligence in different parts of a business, but these small scattered islands have not yet provided universities with the theoretical foundation for the use of artificial intelligence in the commercialization of knowledge.In the long term, this trend could lead to a weakening of the position of the entrepreneurial university that has not utilized the capabilities of artificial intelligence in completing its executive processes and continues to survive with traditional methods, policy-making, and individual decisions of the growth center managers.
2. Research Progress
Application of Artificial Intelligence in Evaluating Incubator Input Plans (Article in Progress)
-Objective: Design an algorithm that ranks input plans based on startup success criteria.
-Method: Collect data on past plans (successful/unsuccessful), define indicators, use machine learning models (e.g. Random Forest or Neural Network)
Application of Artificial Intelligence in Internal Processes of Incubators and Accelerators
-Objective: Optimize resource management, budget forecasting, automate administrative processes.
-Method: Analyze internal data flow (finance, human resources, project scheduling), develop analytical dashboard.
Artificial Intelligence as a tool connecting incubators with other elements of the Entrepreneurial University
-Objective: Create an intelligent network between incubators, faculties, investors, and industries.
-Method: Design a recommendation platform (recommendation system) to connect projects and people based on interests and needs.
Modeling the use of artificial intelligence in incubators
-Objective: To provide a comprehensive framework that integrates the previous three steps.
-Method: Combining the results of steps 1 to 3, validating the model with expert opinion.
3. Cooperation Required
Managers and experts of university incubators
-For access to real data (startup proposals, internal processes, performance statistics).
-To validate the model and help design applied evaluation indicators.
Specialized machine learning and artificial intelligence team
-For design and implementation of algorithms (evaluation of designs, modeling of internal processes, communication network).
-For technical advice, selection of tools and optimization of models.
Experts in policy-making and technology commercialization
-For coordination with intellectual property laws, data security and the possibility of generalizing the results to the national level.
4. Benefits
Academic and research benefits
-Creating a new model for applying artificial intelligence in the management of incubators and accelerators, which has been less discussed in the entrepreneurial university literature.
-Expanding local knowledge in the field of university-industry relations and knowledge commercialization.
Practical and economic benefits
-Increasing the accuracy and speed of evaluating incoming projects; that is, incubators identify high-potential projects faster and more cost-effectively.
-Optimizing resources (financial, human, space) in internal processes, which can reduce operating costs.
-Creating an intelligent communication network between universities, industry, and investors, thereby increasing the chances of attracting capital and commercialization.
Social and national benefits
-Helping to increase the success rate of knowledge-based startups and creating sustainable employment.
-Achieving a model that can be generalized to incubators at the regional and even international levels.
5. Outputs
Publication of scientific research articles
-Publication of at least one article in reputable scientific journals (SCI/SSCI) based on the final results of the project.
-Ready-made article: Application of ChatGPT in evaluating entry plans to university incubators (in progress) as one of the initial achievements.
Development of applied software
-Creation and presentation of an artificial intelligence-based tool for evaluating entry plans, optimizing internal processes, and establishing connections between incubators, accelerators, and other elements of the entrepreneurial university.
-Pilot implementation in several selected incubators/science and technology parks.