The Development of a Method for Forecasting the Business Valuation of Public Companies Within the Framework of the Comparative Approach Using Artificial Intelligence

The main purpose of the paper is to evaluate and compare different business valuation models that incorporate artificial intelligence (AI) technologies. The paper seeks to understand the capabilities, advantages, disadvantages, and limitations of these AI-based models in valuing businesses accurately. Additionally, the paper aims to provide insights into how AI can be utilized effectively in the field of business valuation to enhance accuracy and efficiency. We used qualitative research methods which involve reviewing and analyzing existing literature, case studies, and expert opinions on business valuation models and artificial intelligence. The main contribution of the paper is the integration of artificial intelligence (AI) techniques into traditional business valuation models. The authors propose using AI algorithms such as machine learning and natural language processing to improve the accuracy and efficiency of valuing businesses. By leveraging AI technology, the paper aims to provide more reliable and data-driven valuations, ultimately enhancing decision-making processes for investors, managers, and other stakeholders. The initial segment of the analysis outlines conventional business valuation approaches, such as discounted cash flow (DCF), comparable company analysis (CCA), and asset-based valuation. These methods utilize historical financial data, market comparisons, and asset valuations to estimate a company’s value. Although they are effective, these traditional models have limitations in terms of capturing intricate market dynamics and accurately forecasting future performance. The following section of the analysis delves into specific AI-driven valuation strategies, such as sentiment analysis, predictive analytics, and algorithmic trading techniques. It also explores how AI technologies, like machine learning algorithms, natural language processing (NLP), and deep learning, are revolutionizing business valuation practices. AI enables the analysis of vast datasets, including unstructured data from platforms like social media, news articles, and industry reports, to extract valuable insights. Machine learning models can detect patterns, correlations, and predictive indicators that traditional models may miss, leading to more accurate and agile valuations. The analysis then addresses the benefits, obstacles, and considerations associated with integrating AI into business valuation. This includes data quality and accessibility, model interpretability and transparency, regulatory compliance, and ethical concerns related to AI bias and fairness. In addition, a comparative evaluation of AI-based models is presented. In conclusion, integrating AI into business valuation models presents significant potential to enhance the accuracy, efficiency, and dependability of valuation assessments. Using AI-driven methodologies, investors and analysts can gain deeper insights into the intrinsic value of businesses, enabling them to make more informed investment decisions in dynamic and competitive markets. However, it is crucial to pay careful attention to data integrity, model transparency, and ethical implications to ensure the responsible and effective use of AI in business valuation. Finally, future directions and recommendations are provided.

Penelitian ini bertujuan untuk mengetahui serta memahami urgensi pengaturan AI dalam UU Hak Cipta di Indonesia serta potensi AI sebagai subjek hukum dalam sistem hukum di Indonesia, Penelitian ini menggunakan metode penelitian normative serta menggunakan pendekatan perundang-undangan atau statue approach serta pendekatan perbandingan atau comparative approach. Adapun rumusan masalah dalam penelitian ini adalah Apa urgensi pengaturan artificial intelligence dalam rezim hukum hak cipta di Indonesia? Dan Bagaimanakah potensi artificial intelligence sebagai subjek hukum dalam sistem hukum di Indonesia ? Dalam penelitian ini menemukan bahwa dalam UUHC Indonesia tidak mengenal AI sebagai subjek hukum, sehingga AI berdasarkan pada UUHC Indonesia tidak dapat digolongkan sebagai pencipta serta potensi AI untuk diakui sebagai entitas baru berkaitan dengan subjek hukum selain manusia dan badan hukum yang sebelumnya telah diakui sebagai subjek hukum di Indonesia sangat terbuka, mengingat AI dapat dipersamakan dengan badan hukum sesuai dengan teori-teori badan hukum serta adanya konsep Work Made For Hire yang terdapat dalam UUHC Amerika Serikat yang dapat diadopsi oleh Indonesia untuk mengakomodir AI sebagai suatu entitas baru berkaitan dengan subjek hukum yang diakui di Indonesia. Kata Kunci: Kecerdasan Buatan, Hak Cipta, Subjek Hukum This study aims to determine and understand the urgency of AI regulation in the Copyright Law in Indonesia as well as the potential of AI as a legal subject in the legal system in Indonesia, This study uses normative research methods and uses a statutory approach or statue approach and a comparative approach. This study found that the Indonesian Copyrights Law does not recognize AI as a legal subject, so AI based on the Indonesian Copyrights Law cannot be classified as a creator and the potential for AI to be recognized as a new entity related to legal subjects other than humans and legal entities that have previously been recognized as legal subjects in Indonesia is so open, considering that AI can be equated with legal entities in accordance with theories of legal entities and the concept of Work Made For Hire contained in the United States Copyrights Law which can be adopted by Indonesia to accommodate AI as a new entity related to legal subjects recognized in Indonesia. Keywords: Artificial Intelligence, Copyright, Legal Subject REFERENCES ABC. “Ada Sejumlah Kekhawatiran di Balik Tren Avatar Buatan Lensa.” TEMPO.CO. Last modified December 13, 2022. Accessed November 6, 2023. https://www.tempo.co/abc/8118/ada-sejumlah-kekhawatiran-di-balik-tren-avatar-buatan-lensa. Amboro, F. L. 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Objective: To critically assess the impact of Artificial Intelligence (AI) on the recruitment process within the Human Resources (HR) sector, pinpointing its potentialities and challenges. Method: A comparative approach was employed to contrast traditional recruitment strategies with AI-enhanced techniques. The analysis centered on the inherent advantages and challenges of AI adoption in recruitment. Results: The benefits of AI in recruitment significantly outweigh its limitations. The research indicates a trend of broad endorsement of AI in the corporate realm, with AI systems adeptly: a) cataloging behavioral patterns, b) determining job fit based on disposition, c) synchronizing these with job specifications, d) interfacing with enterprises, e) facilitating virtual interviews, and f) engendering synergistic outcomes. Conclusions: AI, reflecting its foundational ethos, holds the potential to produce both commendable and adverse effects in recruitment. The self-evolving capability of AI necessitates continuous oversight to circumvent governance challenges. Practical Implications: Responsible adoption of AI in HR can optimize recruitment processes, rendering them more efficient and precise. However, it is imperative to strike a harmonious balance between artificial and human intelligence to ensure ethical and efficacious deployment, minimizing risks and maximizing benefits.

Purpose This study aims to examine the implementation of artificial intelligence (AI) in the Islamic finance industry and to identify legal issues and design an appropriate supervisory model to promote the Islamic finance industry. Design/methodology/approach This type of research is legal research. This legal research uses a statute approach, conceptual approach and comparative approach between Indonesia, Hong Kong, Malaysia and the United Arab Emirates (UAE). Findings The utilization of AI in Islamic finance is becoming increasingly important in various sectors. In the front office, AI simplifies credit evaluation, Takaful (Islamic insurance) and chatbots, improving client interactions and decision-making processes. In the middle office, AI is an integral part of anti-money laundering, counter-terrorist financing (CTF), know your customer protocols and fraud detection. In the back office, AI improves capital management, market impact assessment, risk management and asset and wealth management. In addition, AI substantially enhances regulatory technology (RegTech) and supervisory technology (SupTech), ultimately improving the effectiveness of regulatory compliance and supervision in the Islamic finance industry. These technologies simplify compliance processes, evaluate data quality, detect potential hazards and adapt to complex regulatory frameworks. Nonetheless, the incorporation of AI faces significant obstacles, most notably the absence of a comprehensive legal framework governing the application of AI in the Islamic finance industry. The current regulations, including the Islamic Banking Law and Insurance Law, do not adequately address AI. Moreover, the use of AI raises concerns about Shariah compliance, particularly about transparency and possible algorithmic bias in the decision-making process. The effectiveness of supervision in Islamic finance largely depends on the membership of the Islamic supervisory board, which must have technological expertise to ensure compliance withShariah norms. Therefore, the development of more sophisticated and effective supervisory procedures is essential for the proper implementation of AI in Islamic banking. An efficient supervisory framework should provide transparency, data security, regular auditing of AI systems and integration of RegTech and SupTech technologies within the Islamic finance sector. Research limitations/implications This research examines the use of AI in the Islamic finance industry in Indonesia, Hong Kong, Malaysia and the UAE. Practical implications This research is important to mitigate the risks of using AI in the Islamic finance industry such as AI decision transparency and explanation, AI job transfer bias and AI conflict with Islamic finance principles. This research is also important to formulate a regulatory framework to enhance AI supervision in the Islamic finance industry. Social implications This research improves and encourages the growth of the Islamic finance industry using AI. Originality/value This research identifies the problems and legal issues of using AI in the Islamic finance industry and formulates a supervisory model.

Introduction. The problematic of artificial intelligence (AI) is one of the central issues for modern scientific and business communities. Despite the relevance and particular demand for AI professions, there is currently an acute need in the labor market for both highly qualified and young specialists in this area. According to analysts, the shortage is due to shortcomings in the system for training AI specialists. The reasons that determined the crisis of educational programs in the field of IT are considered. The main emphasis is focused on the new approaches of gaining knowledge in the training of IT specialists, appropriate to the specifics of the new realities.Methodology and sources. The methodology of comparative analysis, interdisciplinary and philosophical approaches to the consideration of AI as an information and communication phenomenon of the new reality is used. Sources are based on the special literature of foreign (K. Schwab, N. Davis, P. Dougherty, J. Wilson and etc.) and Russian (E.M. Proydakov, V.B. Tarasov, P.M. Gotovtsev and others) authors, scientific researches (collective research of Russian scientists “Strong Artificial Intelligence”, 2021; and others), publications and websites devoted to the problems of AI, including the educational sphere (O.E. Baksansky, U. Pakhomov, etc.; www.trends.rbc.ru/trends/education and others).Results and discussion. Main tendencies of artificial intelligence development are determined. AI is opening out both as a special field of scientific knowledge and as a huge AI-industry. The specifics of educational track in training young AI specialists are revealed; the question of the necessity of developing new educational model, implementing the needs of digital economy in terms of training highly qualified personnel in the field of IT is raised.Conclusion. In the present conditions, when the volume of information is constantly increasing and the practice of AI development is ahead of the theory, the training of AI specialists has still a narrow profile. In this connection, we consider the latest modification of STEM education – i-STEAM, which, like STEM, is aimed at ensuring end-to-end interaction between applied tasks, fundamental research and educational system, but, unlike STEM, includes humanitarian and innovative components, which is especially relevant for training young AI specialists. However, as applied to the AI direction, the humanitarian component must be necessarily supplemented by the subject field of digital humanistic with the main emphasis on digital applied ethics as a prerequisite for progressive development of AI. It is focused that this approach of the training of AI profile meets the requirements of the human-centered digital era.

Artificial Intelligence (AI) is reshaping strategic management in Chinese enterprises, offering powerful tools for data-driven decision-making and competitive advantage in a dynamic business environment. This study examines how AI adoption influences strategic management practices in China. Background: Chinese firms are integrating AI across strategy formulation and execution amidst strong state support and a booming AI industry. However, traditional strategic methods reliant on managerial intuition and static analysis face limitations handling big data and rapid market changes. We adopt a conceptual analysis of recent literature and industry reports (2019-2024) to outline frameworks, comparative approaches, and case insights on AI-driven strategy. Findings indicate that AI-enhanced practices improve market forecasting, real-time environmental scanning, and operational efficiency. Chinese enterprises lead in AI adoption e.g. 83% of surveyed Chinese firms report using generative AI vs 65% in the US leveraging AI for automation, customer analytics, and innovation. We propose a conceptual model of AI-integrated strategic management linking AI capabilities with enhanced agility and competitiveness. Comparative analysis shows AI-augmented approaches enable faster decisions and personalized strategies relative to traditional methods. Nonetheless, challenges arise in workforce adaptation, data governance, and alignment with strategic goals. AI is a catalyst for strategic transformation in China, elevating analytical rigor and responsiveness of enterprises. To realize its full potential, firms must develop AI maturity, address ethical and talent gaps, and align AI initiatives with long-term strategy. This work contributes a structured overview of AI strategic impacts, offering frameworks (PESTLE, SWOT) and guidance for Chinese enterprises and policymakers to harness AI for sustainable competitive advantage.

Penggunaan Artificial Intelligence (AI) sudah sangat lazim dan hampir digunakan dalam semua aspek kehidupan. Keberadaan AI merupakan hal yang tidak dapat dihindari. AI sangat memudahkan dalam berbagai aspek kehidupan termasuk dalam pengelolaan Sumber Daya Manusia. Salah satu manfaat dalam menggunakan AI untuk pengelolaan Sumber Daya Manusia adalah dalam menilai kinerja atau prestasi pekerja. AI dapat juga digunakan dalam memberikan keputusan penting dalam hubungan industrial yaitu melakukan pemutusan hubungan kerja. Penelitian ini membahas tentang peraturan-peraturan terkait penggunaan AI untuk melakukan pemutusan hubungan kerja. Penelitian ini merupakan penelitan hukum normative dengan pendekatan peraturan perundang-undangan (statute approach), pendekatan konseptual (conceptual approach), dan pendekatan perbandingan negara (comparative approach). Kesimpulan dari penelitian ini adalah adanya pengaturan yang berbeda di beberapa negara, Indonesia menempatkan AI bukan sebagai subyek hukum, regulasi AI di berbagai negara menunjukkan perbedaan paradigma yang terbagi menjadi dua, yakni mengutamakan pengembangan AI atau proteksi terhadap dampak dari AI dan pendekatan berbasis risiko untuk memastikan pengawasan ketat terhadap penggunaan AI, terutama yang berisiko tinggi bagi pekerja, seperti PHK yang dilakukan oleh AI

Artificial intelligence, or better known as AI, is experiencing very rapid development in today's technological era. Artificial Intelligence (AI) is an innovation that has changed many aspects of life in the world. The presence of machines with AI capabilities certainly has a disruptive impact on various social structures of society. One of the significant changes with the presence of AI is the legal science course, especially criminal law. The existence of a legal vacuum in the regulation of criminal law enforcement regarding AI or artificial intelligence initiated the author to conduct research related to law enforcement efforts against AI as a criminal law subject. This research aims to find out law enforcement against AI which can be the subject of criminal law. This study uses a type of juridical-normative research with a conceptual approach, a statute approach, and a comparative approach. Legal studies on artificial intelligence as perpetrators of criminal acts are quite minimal because they are not accompanied by regulations that regulate them. Artificial intelligence such as AI cannot perform illegal acts independently, because in its operation, AI requires help from humans. In Indonesia's positive law, artificial intelligence (AI) is not recognized as a legal subject as is a human or legal entity that is juridically recognized as a legal subject. Only legal subjects, both individuals and legal entities, can be held criminally liable. The right conclusion in this article is that the government should prepare regulations on AI as a subject of criminal acts and law enforcement against artificial intelligence. This arrangement is along with the identification of legal subjects, both individuals and legal entities, as well as appropriate laws to carry out law enforcement efforts against AI.

Objective: The main objective of the paper is to study the need for Special Regulatory legislation for Technology especially Artificial intelligence (AI) as well as examine how AI and law work together. The paper evaluates the liability of AI when it violates Human Rights and Data Privacy. The paper evaluates how AI has created new possibilities and had posed challenges by interfering Human Rights and challenging Sustainable Development comparing the developments happening in European Union (EU) with countries like India. The paper also attempts to make the complex debate more comprehensible for those with no expertise in this area. Method: The Comparative research approach was administered by highlighting the EU methods to tackle and address the AI liabilities. Analogy and review of the Product Liability Directive (PLD) which is proposed and published by European Union (EU) for an AI system liability and suggestions of National Institution for Transforming India (NITI) Aayog of India to attain Sustainable National Economic Development. The paper analyses from financial and lucrative perspective, what liability rules would curtail the financial damages and other harms caused by AI systems which affect Sustainable Development. Results: The paper findings suggest that influence factor of AI applications should be included in existing Liability framework and must be consistently updated as AIs are characterised by unpredictability and independence. Both the EU and India NITI Aayog states that regulatory insight must be an ethical reinforcement for AI practice and hence ensure the sustainability of AI technologies. Originality/Value: The recent government initiatives in EU and India are discussed with respect to the AI liability. The study provides positive insights of Artificial Intelligence (AI) technology and its liabilities to achieve Economic Sustainable Development. The key findings of the paper highlight the importance of Salmond’s defined Tortious liability during British Era for AI technologies for protecting Human Rights and also achieve Sustain Development.

Purpose: This article examines the impact of artificial intelligence (AI) on the evolution of business models in the video game industry. The main objective is to fill the research gap concerning how AI integration not only generates new business models but also modifies existing ones, influencing companies’ strategies and players’ experiences. The study addresses the tension between innovation and risk, showing how AI adoption reshapes value creation, delivery, and capture within this creative sector. Design/methodology/approach: The research combines a systematic literature review (SLR) of 56 Scopus-indexed publications with qualitative empirical analysis. A comparative case study approach was adopted, focusing on Ubisoft, which actively experiments with generative AI, and CD Projekt, which deliberately limits AI use. The criteria of analysis included strategic goals, the degree of creative control retained by developers, and the legal and ethical challenges of AI-driven innovation. Findings: The results reveal that AI enables cost optimization, higher player retention through personalization, and novel monetization models such as NFTs and dynamic pricing. Ubisoft uses AI tools like Ghostwriter and NEO NPC to automate NPC dialogues and create dynamic interactions, enhancing immersion while maintaining authorial oversight. In contrast, CD Projekt refrains from integrating generative AI into flagship projects like The Witcher 4, citing copyright and quality concerns, and applies AI only in supportive functions such as testing or voice reconstruction. These contrasting strategies show that AI’s impact on business models depends on technological choices and risk tolerance. Research limitations/implications: The study is limited to global trends and two cases; future research should include regional and ethical perspectives. Practical implications: Game developers can leverage AI to optimize processes and retention, but must apply legal audits and ethical safeguards. Social implications: AI expands gaming as a social and cultural space but raises concerns about manipulation, copyright, and creativity. Originality/value: The study integrates theory and practice, showing how contrasting AI strategies transform business models and offering a framework for future industry adoption.

Analytics and AI innovations have the potential to help the decision-making processes and to bring more business opportunities for stakeholders. This study explored how analytics and AI support decision-making in EdTech platforms. The interest in research on how artificial intelligence (AI) can be applied in the Education sector has grown significantly in the past decade. Using a comprehensive literature review, document analysis, and search analysis, the study emphasized the growing attention to analytics and AI-related topics in public companies’ annual fillings. Also, the study explored the types of decisions in EdTech platforms that can benefit from analytics and AI implementations. There is a broad range of decisions that can benefit from analytics and AI: personalized learning paths, early notifications or student dropout prediction are only a few of the possibilities that analytics and AI implementations can provide to EdTech platforms. The originality of this article consists of a review of the unique combination of stakeholders and decision types that can benefit from analytics and AI along with the general trend of the analytics and AI-related concepts in the official communications of the US public companies. This research contributes to a better understanding of how analytics and AI technologies can help the EdTech platforms provide better learning experiences to the students and better insights to decision-makers on educational offerings.

Artificial Intelligence influences democratic norms and principles. It affects the quality of democracy since it triggers hoaxes, irresponsible political campaign, and data privacy violations. The study discusses the legal framework and debate in the regulation of Artificial Intelligence in the European Union legal system. The study is a doctrinal legal study with conceptual and comparative approach. It aims to criticize the current doctrine of democracy. The analysis explored the law on election and political party in Indonesia to argue that the democratic concept is outdated. On the other hand, the European Union has prepared future legal framework to harmonize Artificial Intelligence and democracy. The result of the study indicates that the absence of law on Artificial Intelligence might be the fundamental reason of the setback of democracy in Indonesia. Therefore, the Indonesian legal system must regulate a prospective Artificial Intelligence regulation and a new democratic concept by determining the new principles of responsible Artificial Intelligence into drafts of laws on Artificial Intelligence, election, and political party. Finally, the new laws shall control programmers, politicians, governments, and voters who create and use Artificial Intelligence technology. In addition, these legal principles shall be the guideline to prevent the harms and to mitigate the risks of Artificial Intelligence technology as well as the effort to strengthen democracy.

Day in and day out, the Workforce Department faces new problems and operational demands. It is very important for the department to respond quickly and understand the best possible action to be taken in each single case. It is unknown in a compromised setting of near-constant shifts in forecast and scheduling, increased customer demands, and changing recruitment and retention of employees. Workforce management around the world has begun to use artificial intelligence (AI)-based workforce management (WFM) software to solve the above problems and reach goals. These tools transform workforce management by helping to anticipate and plan short- and long-term planning. These tools improve Workforce Management by helping to predict short- and long-term scheduling and recruiting requirements, communicate with staff, and at the right time bring customers in contact with the right agent. This chapter addresses AI workforce management intervention and WFM instruments with industry-specific case studies and its experience with the product Workforce Dimensions. Present status and future expectations are also critically reviewed. Techniques of AI and machine learning (ML) are transforming industries, as are goods from thermostats to cars. The global enterprise value generated from AI continues to grow, according to Gartner, and is projected to reach up to $ 3.9 trillion by 2022. But what do these approaches mean for workforce management in the field? The current chapter examines the growing use of artificial intelligence (AI) in various HRM functions, as well as the ongoing debate about the expected decline in the usability of human resources in organizations. In the presence of AI in the workplace, HR practitioners are constantly afraid of being replaced by computers/robots/smart business machines. The study aims to recognize AI’s important contribution to enhancing organizational decision-making processes, as well as to enhance awareness of AI’s acceptability and inclusion in the HRM department. Despite the fact that the combination of AI and HRM is attracting a large number of researchers, many aspects of the field remain unexplored. The current research proposes a collaborative approach by stressing the complementary role of HRM in the successful use of AI, and it contributes to the existing literature. Since AI and HR are so intertwined, organizations should concentrate on incorporating AI as a supporting tool for HR rather than attempting to take over HR’s function. Business systems and smart business machines should be designed in such a way that they cannot produce results without the help of HR.

Introduction. One of the trends of global importance is the artificial intelligence (AI) and its innovations. One of such innovations has become emotional artificial intelligence (emotional AI/AI), it is called a revolutionary technology that can identify human emotions, process them in a timely manner and react “properly”. Experts consider emotional AI as an instrument that provides emotionally-oriented human–machine communication. The article discusses the specifics of emotional AI, achievements, potential opportunities, development prospects.Methodology and sources. The methodology of philosophical, socio-psychological, comparative and interdisciplinary approaches is used. The sources used in the article are: special literature of domestic and foreign authors (B. Goertzel, D. Goleman, R. Picard,D.I. Dubrovsky, E.M. Proidakov) scientific research, publications and websites devoted to emotional artificial intelligence, and its features (Aliya Green Emotional artificial intelligence: changing the human world for the better).Results and discussion. The relevance of the topic of emotional AI determined the need to refer to the concept of ”emotional intelligence” (EI) as the basic basis of emotional artificial intelligence, which allowed us to show the essential characteristics of human emotional intelligence, its difference from AI. Emotional artificial intelligence is an innovation of modern AI, its main actors are anthropomorphic robots, text, voice chatbots and video bots, which are already actively demonstrating to the public their knowledge and skills in the field of psychology of emotions, which are being improved within the framework of the current AI.Conclusion. Currently, there is a gradual process of teaching emotional AI to interact with a person, and although these achievements are not great yet, EII is gradually developing in accordance with the challenges of new realities within the specifics of modern applied AI. However, in the digital age, human–machine and machine-to-human communication is an interconnected process that should be aimed at building both utilitarian–useful and partnership relations in the practices of their interaction, which meets the requirements of the era and leads to further progress of AI – to the creation of a new, common AI – “human AI the level” which is supposed to greatly expand the capabilities of a person and society as a whole.

Artificial intelligence companies are different from traditional labor-intensive and capital-intensive companies in that their core competitiveness lies in technology, knowledge, and manpower. Enterprises show the characteristics of a high proportion of intangible assets, strong profitability, and rapid growth. At the same time, there are also the characteristics of high risk and high uncertainty. In addition to the existing value brought by existing profitability, corporate value should also consider the potential value brought by potential profitability. Enterprise value is affected by many factors such as profitability, growth ability, innovation ability, and external environment. Traditional valuation techniques are often utilised to value artificial intelligence businesses in the present market. Traditional valuation methods ignore the dynamics and uncertainties of artificial intelligence enterprise value evaluation, make static and single predictions of future earnings, ignore the value of enterprise management flexibility, and are unable to assess the intrinsic value of artificial intelligence businesses. Based on the projection pursuit method, this paper constructs a modern high-quality development enterprise high-quality development evaluation model, uses real-code accelerated genetic algorithm to optimize the projection objective function, and calculates the best projection direction vector and projection value. The collected sample data can be imported into the evaluation model to calculate the comprehensive evaluation value of the high-quality development of modern high-quality development enterprises and the weights of various indicators included. By comparing the size of the comprehensive evaluation value, each sample can be calculated Evaluation of the level of high-quality development. The results show that the high-quality development level of China's overall economy is on the rise, but the level of development is still low, and there is a large gap between the development level of the eastern region and the central and western regions. Using the systematic generalized moment estimation method, empirically, we analyse the impact of artificial intelligence on the high-quality economic development. The results show that artificial intelligence at the national level and in the central and western regions will significantly promote high-quality economic development, while artificial intelligence in the eastern region has a significant inhibitory effect on high-quality economic development.