Participation of artificial intelligence in economic growth in Romania

Ioan-Franc, Valeriu; Gâf-Deac, Ioan I. Article Participation of artificial intelligence in economic growth in Romania Amfiteatru Economic Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Ioan-Franc, Valeriu; Gâf-Deac, Ioan I. (2024) : Participation of artificial intelligence in economic growth in Romania, Amfiteatru Economic, ISSN 2247-9104, The Bucharest University of Economic Studies, Bucharest, Vol. 26, Iss. 67, pp. 944-956, https://doi.org/10.24818/EA/2024/67/944 This Version is available at: https://hdl.handle.net/10419/306192 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ AE Participation of Artificial Intelligence in Economic Growth in Romania 944 Amfiteatru Economic PARTICIPATION OF ARTIFICIAL INTELLIGENCE IN ECONOMIC GROWTH IN ROMANIA Valeriu Ioan-Franc1 and Ioan I. Gâf-Deac2 1)2)“Costin C. Kirițescu” National Institute for Economic Research - Romanian Academy, Bucharest, Romania Please cite this article as: Ioan-Franc, V. and Gâf-Deac, I.I., 2024. Participation of Artificial Intelligence in Economic Growth in Romania. Amfiteatru Economic, 26(67), pp. 944-956. DOI: https://doi.org/10.24818/EA/2024/67/944 Article History Received: 2 March 2024 Revised: 8 May 2024 Accepted: 15 June 2024 Abstract The purpose of this article is to demonstrate that it is necessary to model the connections of the Romanian economy for growth with the help of Artificial Intelligence (AI). That is why it is useful to align with the trends in the EU economy and on a global level to use innovative technologies, with the domestic economy having the opportunity to become excellent. It is a moment of opportunity for commitment in this regard, considering that Romania already has the IT infrastructure and the human resources with a real predisposition to AI. The article reports on the research carried out, by way of example, on a number of AI companies, and from the answers received and processed, real values emerge that reflect the potential of contributing to economic growth through AI. Our article presents a first-of-its-kind view of how AI investment and participation relate to domestic economic outcomes. It is estimated that, mainly, in Romania in the coming years, the expected economic growth can be registered on account of the activities coming from small and medium enterprises dominated by AI. As such, it is considered that the new AI economy will be able to be built and engaged in Romania to the extent that small and medium enterprises will show “constructive behaviour, with evolutions based on innovation with the help of AI”. Keywords: Artificial Intelligence (AI), economic growth, AI variables, AI growth modelling JEL Classification: C15, E17, O11, O47  Corresponding author, Valeriu Ioan-Franc – e-mail: [email protected] This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2024 The Author(s). Amfiteatru Economic Recommends AE Vol. 26 • No. 67 • August 2024 945 Introduction Currently, the idea of an almost continuous influence on the economy coming from the ranks of Artificial Intelligence (AI), which can be defined as a competitor for authority, is suggested. The promoters of general economic science believe that “the economy cannot be separated from AI” which proves, mainly, useful in identifying alignments to minimise risks, increase productivity and incomes. Romania has an annual economic growth in the last period (“in 15 years, the GDP increased 4 times, and the GDP per inhabitant increased 2.3 times” (Georgescu, n.d.)), but it lags behind the levels reached in the EU by developed countries or most OECD countries. The levels of poverty and non-fulfilment are visible, and the speed of progress towards upper limits is still low (increased budget deficit, high external debt, low productivity, etc.). Added to this is the large emigration outside the country, the lack of feasible and sustainable strategies in the medium and long term in some branches of economy, the lack of competitiveness of industry and agriculture, etc. However, we believe that there is a chance to reconceptualise the economic growth of the country with the consolidated emergence and manifestation of AI in all sectors of activity nationally and, by extension, globally. The purpose of this article is to demonstrate to official decision-makers, developers of strategies, tactics, and programmes that the economy in Romania will have real growth based on the use of AI. The lack of commitment or firm immersion in the field of AI can lead Romania’s current economy to stagnation, or, when adhering to this flow results in alignment with operational trends in the EU and the global economy, or the autochthonous economy “becoming” an advanced field of excellence, an example worth following by other state entities. In the article, we resort to modelling the links of the Romanian economy to growth with the help of AI. It is a moment of opportunity, an occasion for commitment in this regard, especially since Romania already has the starting IT infrastructure and the human resources with a real predisposition to work in the field. The research is carried out, for example, on 72 AI companies and from the answers received it follows that the variables (activities) are of high resolution, the subjects/themes in which the companies are engaged for processing demonstrate attractiveness for the Romanian area from the large foreign investors in the field and, equally, it reflects the potential to contribute to economic growth. In our present assessment, AI becomes a subdiscipline of general economic science and we consider that the heterogeneity of national interests, with extension in the European one, should occupy a central place in the general economic picture, including the one of Romania. With the help of AI, it is possible to manifest in the new economy rules such as: realism, agenda with content of majority interest, adaptation to circumstances, pronouncement in real time based on transmitted information, influence from multi-principle mediation of economic decisions. Moreover, an inclusive world based on AI is envisioned, and the requirement for a global approach to data in the digital age is emerging, encouraging competition and stability in the digital economy. It is positive that the Industrial Monetary Fund (IMF) has already established an AI Readiness Index that measures readiness in areas related to each country’s digital infrastructure, human capital and labour market policies, innovation and economic integration, regulation, and ethics. So, in the presence of AI there is a shift towards global principles. Our article provides the first systematic view of how AI investment and participation relate to domestic economic outcomes. It is estimated that, mainly, in Romania in the next 15-20 AE Participation of Artificial Intelligence in Economic Growth in Romania 946 Amfiteatru Economic years, the expected economic growth can be registered due to the activities coming from small and medium enterprises dominated by AI. Therefore, it is considered that among the methods of growth, the new economy will be able to be built in Romania to the extent that small and medium enterprises will show “constructive behaviour, with evolutions based on innovation with the help of AI”. 1. Review of the scientific literature Most studies highlight that AI has potential and economic impact; in fact, through AI, a technological revolution is taking place, stimulating economic growth and incomes globally. Innovative AI technologies will lead to an increase in labour productivity (up to 40%), create a virtual “intelligent automation” workforce and diffuse innovation, which will generate new revenue streams. (Accenture, 2022) Global GDP may increase by 14% by 2030 as a result of accelerating AI development and adoption. The new sense of digital revolution already unleashed with the Internet of Things (IoT) the stimulation for standardisation, automation, personalisation of products and services, bringing productivity gains. Automation of routine tasks, expansion of robotics and autonomous vehicle technologies will promote a new workforce according to PricewaterhouseCoopers (2018), and also to other important authors (Agrawal, Gans and Goldfarb, 2019; Acemoglu et al., 2022). Hershbein and Kahn (2018) classify jobs as requiring cognitive skills only if any of them is found in at least one of the following terms: “research”, “analysis”, “decision”, “solving”, “mathematics”, “statistics”, or “thinking”. There are significant investments in software (approx. 70% of companies adopt at least one type of AI technology), and by 2030 the global GDP will increase by approx. 1.2% annually, shows Bughin et al. (2018). On the other hand, Farboodi and Veldkamp (2022) outline that AI will have positive direct and indirect effects on places of work (40% of the total), productivity and GDP, will optimise business processes and decisions, thereby increasing knowledge and access to information. There will be implications of AI in the selection of economic policies, effects on processing sectors, on companies, industries, at the level of countries generating impact and redistribution of the labour force. At the same time, Szczepanski (2019) points out that AI will be crucial for labour productivity, income distribution, and especially for economic growth itself, as supported also by Mihet and Philippon (2019) and Farboodi et al. (2019). At the 2023 World Economic Forum (WEF), it was noted that the use of AI for common tasks has seen an increase in recent years, and ChatGPT developed by OpenAI is an example of generative AI used daily by more than 1 billion people. It is recalled that the GEF in October 2020 concluded that, while AI would eliminate 85 million jobs globally, by 2025 it would also generate 97 million new jobs in AI fields, from big data and machine learning to information security and digital marketing. AI technologies have advanced rapidly in the last few years (Chang et al., 2023); currently, general-purpose infrastructures are available (Aghion et al., 2018; Patrick, 2018), and between 2015 and 2021 the number of AI patents increased 30 times (Ganglmair et al., 2021). At the same time, Fizsbein et al. (2020) highlight that AI has led to rapid productivity gains. Technological changes through AI are opportunities for investment and economic growth. (Furman and Seamans, 2019). Amfiteatru Economic Recommends AE Vol. 26 • No. 67 • August 2024 947 Some authors believe that the question whether AI can transform economies and boost economic growth remains open. Brynjolfsson, Rock and Syverson (2021) and Raj and Seamans (2017) point out that there is currently a lack of relevant data on AI coverage at firm level, and Alderucci et al. (2020) believe that it is necessary to focus on companies that invent AI. The AI-trained labour shortage is another constraint to the inclusion of AI in firms (CorrelationOne, 2019). The development of new products with the help of AI eliminates lengthy experimentation (Braguinsky et al., 2021), as AI algorithms generate accelerated learning and reduce the uncertainty of homologation. It turns out that AI is definitely stimulating economic growth, already becoming a technology of general use (Goldfarb, Taska and Teodoridis, 2023). Bughin et al. (2018) estimate that, in industry, 90% of companies’ investments in AI are internal and only 10% come from acquisitions. The percentage of companies investing in AI in just one year is 29.5%, compared to 70.6% for robotics (Humlum, 2019). Globally, consistent with findings made by Caliendo et al. (2020), in practice, product quantities increase to such an extent that lower prices are charged. Some authors consider AI a predictive technology (Agrawal, Gans and Goldfarb, 2019), while for others AI is a general-purpose technology (Goldfarb, Taska and Teodoridis, 2023). It is notable, however, that AI technologies have scale effects that favour large firms, which accumulate large amounts of data as a by-product of their economic activity (Farboodi and Veldkamp, 2022). The benefits of AI largely depend on who owns big data – the key input for AI technologies, according to Fedyk and Hodson (2023) and Babina et al. (2024). However, there is no systematic data on the companies’ AI investments. According to some authors, they amount to approx. 140 billion USD/year globally. We can conclude that economists, in general, do not have a strong potential to predict the future. It is estimated that in 12 developed economies, AI could double annual global economic growth rates by 2035. 2. Research methodology Methodologically, our article presents a novel approach to demonstrate the extent to which AI contributes to economic growth, and more broadly, our method suggests that new technologies such as AI have clear and distinct advantages in the speed of positive change in the national economy. The research in this article is based on the original mathematical formalisation of modelling, systematisation, and interpretation relationships in the field. In general, for the understanding and operationalisation of AI in the Romanian economy, we propose to go through a procedural algorithm to obtain univariate classifications (𝐶0). In fact, the formalisation starts from the multivariate classification (𝐶𝑚) when for this conception there are a number of classes (𝑁𝑐) of knowledge that enter the so-called intelligent creation. A first step is the separation of classes/sub-classes (∆𝑠), followed by transformations of/for linearisation (∆𝑙) to notice the processing in question in a more simplified manner. In the end, it is a matter of metricity/ultrametricity obtained by simplifying calculations for determinations related to the identification and analysis of linear discriminants. The transformations for linearisations (i) can record relative/absolute amplitudes, highlighting the depth of refinements to eliminate reminiscences/redundancies, with reference to reducing spaces/distances between data. In the literature in the field, concerns are highlighted for the search for global classification models or for spatiality/spatialisation, respectively, the AE Participation of Artificial Intelligence in Economic Growth in Romania 948 Amfiteatru Economic localisation of classifications. The most important property for AI, in our opinion, in the process of searching for classifications becomes procedural adaptability, an aspect that does not introduce the obligation to establish immutable methods, procedures, techniques, etc. in the field. As such, it can be written: {(𝐶𝑚) (𝑠) → {𝐶} ∀[𝑀𝑎𝑥(∆𝑠)∗𝑀𝑖𝑛(𝑁𝑐)] (∆𝑙) → (𝐶𝑜) (𝐶𝑜)∈[{𝐶}𝑓(𝑠)⊂(𝐶𝑚)]≈[{𝐶}𝑓(𝑠)∩(𝐶𝑚)] (1) At the same time: {𝐶}:(𝑅,𝑅)−[𝛷{𝐶}+𝛷(𝜀𝑖)+𝛷(𝛥𝐶𝑚)]=(𝐶𝑜)𝑓(𝛥𝑙) (2) {(𝛥𝑠)∗(𝑁𝑐)} → 𝑀𝑎𝑥𝑀𝑖𝑛𝑓(𝛥𝑙) (3) On the other hand: {∑ (𝜀𝑖) 𝑘𝑖=1 =𝑀𝑎𝑥𝛷(𝜀𝑖) ∑∆(𝐶𝑚)𝑖 𝑘𝑖=1 =𝑀𝑎𝑥𝛷(∆𝐶𝑚) (4) and [{𝐶}:(𝑅,𝑅)]−{±∑ (𝜀𝑖) 𝑘𝑖=1 ±∑∆(𝐶𝑚)𝑖 𝑘𝑖=1 }=(𝐶𝑜)|(∆𝑙) (5) Making n observations of the type (𝑎𝑖,𝑏𝑖,𝑐𝑖,…,𝑧𝑖)∈ℝ in the real space (Romanian companies that have AI activities), each variable provides a sub-image (SI) in the set {Mo}⊃ [(SI)ai;(SI)bi;…;(SI)zi], that become correspondents, members of an incipient nonreminiscent and non-redundant classification. The placement of sub-images in variancecovariance matrices depicts the dimensional and qualitative disproportions of observations made on AI in the economic productive field, in everyday life. Eliminating or reducing discrepancies means reducing the virtual weight of events found with AI in supervised/unsupervised database simulations in the real economy/new economy. In the context, the falsely appropriate and non-covariational analog set {Mo} appears, which is nondistanced from the set of initially identified/delimited sub-images. On this basis, AI processings that are considered untrue often appear. Therefore: {𝑀𝑜}∧{𝑀𝑜} (6) Also: {[𝑚𝑎𝑥𝛷(𝜀𝑖)]∧[𝑚𝑎𝑥𝛷(𝜀𝑖)] [𝑚𝑎𝑥𝛷(∆𝐶𝑚)]∧[𝑚𝑎𝑥𝛷(∆𝐶𝑚)] (7) [{∑ (𝜀𝑖) 𝑘𝑖=1 }∗{∑ (∆𝐶𝑚) 𝑘𝑖=1 }] → (𝐶𝑜)−(𝛷{𝑀𝑜})(𝐶𝑚)={𝑀𝑜}(𝐶𝑜) (8) On the final configuration {Mo}(Co), related to AI, infrastructures/machines show learning efforts, equally on the part of humans, understanding and perceiving or assuming the nature Amfiteatru Economic Recommends AE Vol. 26 • No. 67 • August 2024 949 and realism of the sub-images validated to be contained in a consolidated non-reminiscent and non-redundant classification of knowledge. In this framework, we resorted to research through interviewing 72 Romanian companies with AI as a field of activity, and the answers were systematised in accordance with relations (6), (7), and (8), in tables with power allocations (coefficients of importance). In this way, the involvement of AI in the issue of the domestic economy is deduced, emphasising its possible proportional growth with computerisation, digitisation and the general increase of knowledge. 3. Results and discussion As part of the research, responses were received from a number of 72 companies that agree to the existence of 63 “activities” type variables in the field of AI. (Table no. 1) Table no. 1. The variables detected (received as responses) from the entities that have the formalisation and application of AI as field of activity No. crt. Variables Ac Yes Yes/ No No No M As AI to extend/enhance knowledge 1. systems and software on quality platforms; 2 0.70 1.00 1.00 2 0.35 .041 2. customised web applications; 1 0.82 - 0.00 - 0.82 .043 3. customised software and digital innovation; 1 0.60 - 0.00 - 0.60 .008 4. the architecture of the digital transformation approach; 1 0.72 - 0.00 - 0.72 .042 5. software and hardware for understanding the details; 1 0.79 - 0.00 - 0.79 .043 6. web and mobile application software, DevOps, machine learning; 1 0.80 - 0.00 - 0.80 .043 7. AI solutions for deep understanding of content; 1 0.56 - 0.00 1 0.56 .009 8. AI for natural language processing (NLP), Text Analytics and Speech to Text; 1 0.53 - 0.00 1 0.53 .009 9. software libraries for neuromorphic computer vision; 1 0.60 - 0.00 - 0.60 .008 10. data intelligence and AI. 1 0.48 - 0.00 1 0.48 .009 AI for technologies 1. continuous presence at the end of the best technologies; 1 0.78 - 0.00 - 0.78 .038 2. work in a complex environment with updated technologies; 1 0.83 - 0.00 - 0.83 .044 3. technical talent in the field; 1 0.81 - 0.00 - 0.81 .043 4. the ability to integrate advanced technologies; 2 0.79 1.00 1.00 1 0.39 .043 5. simplification of complex technical problems in a timely manner; 1 0.84 - 0.00 - 0.84 .044 6. nearshoring and offshoring technologies; 1 0.69 - 0.00 - 0.69 .008 7. deep-tech AI platform with ICT system, infrastructure, code, algorithms, scripts and technical processes; 1 0.69 - 0.00 - 0.69 .008 8. AI template generation technology; 1 0.59 - 0.00 1 0.59 .007 9. integration of AI technologies; 2 0.78 1.00 1.00 - 0.36 .043 10. essential and transformative machine intelligence for enterprises; 1 0.70 - 0.00 1 0.70 .041 11. Eye-Tracking and Brain-Computing Interface technologies, generative and parametric methods in Game Engine environments; 1 0.69 - 0.00 - 0.69 .008 12. software robots using UipAth, Rinkt technologies. 1 0.42 - 0.00 1 0.42 .006 AI for deep/advanced services 1. technological services in the development of customised software and IT outsourcing; 2 0.84 1.00 1.00 1 0.41 .044 AE Participation of Artificial Intelligence in Economic Growth in Romania 950 Amfiteatru Economic No. crt. Variables Ac Yes Yes/ No No No M As 2. virtual assistants for managing repetitive and time-consuming tasks; 1 0.73 - 0.00 - 0.73 .041 3. clean and error-free code service; 1 0.79 - 0.00 - 0.79 .043 4. excellent response time and quality workmanship; 1 0.84 - 0.00 - 0.84 .044 5. independent conversational AI platform with interconnected virtual assistants; 1 0.69 - 0.00 - 0.69 .008 6. Ressi platform of generative AI assistants; 1 0.59 - 0.00 1 0.59 .007 7. automatic extraction, clean design; 1 0.61 - 0.00 - 0.61 .007 8. capabilities solutions based on AI/ machine learning; 1 0.68 - 0.00 - 0.68 .008 9. automation scenarios in environments with common solutions; 1 0.83 - 0.00 - 0.83 .044 10. new applications and supporting their maintenance; 1 0.83 - 0.00 - 0.83 .044 11. Wise Agent support automation platform (website chat, Facebook, e-mail, phone call), CRM integration for conversation escalation (Wisevoice Dialog Builder); 1 0.68 - 0.00 - 0.68 .008 12. advanced solutions for visual, voice natural language search, cloud search query processing and classification; 1 0.49 - 0.00 1 0.49 .006 13. writeGPT as web extension; 1 0.78 - 0.00 - 0.78 .043 14. AI chatbot to be integrated on websites. 1 0.71 - 0.00 - 0.71 .040 AI for management 1. reducing complexity through human-centered innovation; 1 0.80 - 0.00 - 0.80 .043 2. platform for organising the timeline of information flow; 1 0.81 - 0.00 - 0.81 .043 3. on-time delivery and persistent risk management; 2 0.83 1.00 1.00 - 0.42 .044 4. transparency about what can and cannot be done through AI; 1 0.83 - 0.00 - 0.83 .044 5. team oriented towards optimal results; 1 0.80 - 0.00 - 0.80 .043 6. organisational culture with customised software solutions, dedication and selectivity; 1 0.75 - 0.00 - 0.75 .045 7. more for the community, not just for its own employees; 1 0.59 - 0.00 - 0.59 .007 8. innovative, flexible and hardworking; 1 0.76 - 0.00 - 0.76 .047 9. top communication, explicit AI data updates; 3 0.80 2.00 2.00 - 0.27 .043 10. work ethic, quality and real-time delivery; 1 0.79 - 0.00 - 0.79 .043 11. significant skills, high commitment and company culture; 1 0.78 - 0.00 - 0.78 .043 12. the attention and pride the team has in the field of AI; 1 0.69 - 0.00 - 0.69 .008 13. managing the speed of change; 1 0.68 - 0.00 - 0.68 .008 14. quick identification of errors and fixes. 1 0.79 - 0.00 - 0.79 .043 AI for development 1. positive approach to AI development projects; 2 0.82 1.00 1.00 - 0.41 .043 2. essential partners in the development of platforms; 1 0.83 - 0.00 - 0.83 .044 3. chatbot, mobile, web and Ethereum Blockchain Smart contract; 1 0.77 - 0.00 - 0.77 .043 4. the ability to deliver high-quality AI knowledge products; 1 0.78 - 0.00 - 0.78 .043 5. complexes that integrate AI, big data, web or desktop solutions. 1 0.69 - 0.00 - 0.69 .008 AI for economics / business 1. redefining the tables of business operations through AI solutions; 1 0.82 - 0.00 - 0.82 .043 2. AI platform for identifying payment errors; 2 0.83 1.00 1.00 - 0.42 .044 3. alternative realities through VR, AR and AI technologies using advanced computing methods; 1 0.72 - 0.00 - 0.72 .042 4. codeless flows, AI models with custom datasets; 1 0.78 - 0.00 - 0.78 .043 5. large language models, Big Data Analytics, with the power of AI; 1 0.67 - 0.00 1 0.67 .008 6. reliable and distributed nano-tasks for AI augmentation; 1 0.58 - 0.00 1 0.58 .007 7. Hawking with intelligent AI solutions; 1 0.69 - 0.00 1 0.69 .008 8. platform for personalised, targeted and automated experiences using data and AI. 1 0.81 - 0.00 - 0,81 .043 Notes: Ac = IA activities/company; [0.00 – 1.00] = weighting coefficients (importance). It is stated that the companies did not fully answer all the questions in the interviews; however, the receipt of those incentives is considered representative and with the potential Amfiteatru Economic Recommends AE Vol. 26 • No. 67 • August 2024 951 for extrapolation at the macroeconomic level, demonstrating the meaning, the recommended direction to follow, namely the intensive use of AI in the current domestic economy to generate its real growth in the future stages. The activities (received through the written interviews) were systematised according to the number of entities (Ac), their confirmation in the fields of activity of the AI enterprises (Yes with a weight of 10, Yes/No/ with a weight of 5, No with a weight of 1), the number of observations (N0), mean (M) and calculation of standard deviations (N0). The main goal pursued in this article refers to the elucidation of the participation of AI in the economic growth of Romania in the coming years, how AI contributes to the emergence and functioning of the new domestic economy, and through its national contribution to participate in the EU’s economic security. In summary, after receiving the answers and assigning weights (importance coefficients in the survey), after examining the limits of variation of the average and standard deviations, the numerical table of the situations is outlined below. (Table no. 2) Table no. 2. Synthesis of measured incentive values at AI companies Total no. of AI variables/activities 63 Total no. of AI companies researched/interviewed 72 Total no. of observations (utterances) recorded about the AI 81 No. of AI companies with multiple fields of activity 8 Variable confirmation weight AI activities (integrated average) [0.42-0.84] Share of unrelated options on AI activity variables (integrated mean) 9 activity [0.00-2.00] Reject variables / AI or non-AI activities 15 Standard deviations [0.08-0.47] The main interpretations refer to the following:  in the researched companies, there is a number of AI activities (63) which are practical, applied topics/themes of significant resolution, a fact that can attract the attention of foreign investors relying on the actuality of commitments and challenges determined by Romanian entities in the field;  almost all the researched companies have distinct, singular fields of activity in AI; there is no dissipation on multiple alignments, which shows increased specialisation in AI on distinctly addressed subject solutions (out of the total of 72 companies, only 8 have double or triple fields of activity);  the integrated average of the weights of confirmed AI activities (successful, with achievements) is contained in the interval [0.42 - 0.84], which shows that more than 80% of the entities have business capability in the field;  the integrated average of the weights of unrelated activities (unsuccessful, with failures) is included in the range that emphasises that only 9 activities (in proportion to only 13.30% of the entities) do not have business capability on some AI alignments; in the answers, 15 variables/types of activities were rejected as not being addressed by the studied entities;  the statistical standard deviations are included in the interval [0.08 - 0.47], values that show the reduced distance (scattering) from the positive solutions given by the variables/activities; lacking large distancing, they are close to the pursued ideal alternatives.