Rebalancing the AI Economy: Strategies for Enhancing Latin America’s Competitiveness in the Global AI Era

Purpose This study aims to investigate how artificial intelligence (AI) integration in service delivery influences sustainability and business performance in small- and medium-sized enterprises (SMEs) across diverse sectors. It further examines the moderating roles of stakeholder engagement and adoption barriers and the mediating role of sustainability performance in the AI–business performance relationship. Design/methodology/approach A mixed-methods approach was used, combining survey data from 428 firms across four sectors with qualitative insights from 20 semistructured interviews. Partial least squares structural equation modeling tested the hypothesized relationships, while thematic analysis provided contextual understanding of implementation challenges and success factors. Findings AI integration significantly improves both sustainability and business performance. Stakeholder engagement strengthens the positive effect of AI on sustainability outcomes, while adoption barriers weaken AI’s impact on business performance. Sustainability partially mediates the relationship between AI integration and business outcomes, underscoring its strategic role. Practical implications To maximize AI’s value, SMEs should adopt phased strategies, engage stakeholders proactively and address technological and organizational barriers. These actions enhance AI’s effectiveness in driving sustainable, competitive service delivery. Originality/value This study advances the AI literature by linking AI adoption to dual sustainability and business benefits while also incorporating the moderating effects of engagement and barriers – an area previously underexplored. It offers a sector-sensitive, empirically grounded model of AI-enabled transformation in SMEs.

The adoption of artificial intelligence (AI) among small and medium enterprises (SMEs) is gaining global attention, yet its implementation in developing economies remains underexplored. This study investigates AI adoption in SMEs in Mauritius and Lagos, Nigeria, using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Employing a qualitative approach, semi-structured interviews were conducted with ten SME owners and managers - five from each region - to examine key factors influencing AI adoption. Findings reveal that AI integration has enhanced business operations, particularly in inventory management, customer engagement, and booking systems, leading to notable improvements in efficiency and sales. For example, SMEs in Mauritius reported a 30% increase in online reservations due to AI-enabled booking systems, while Lagos businesses benefit from AI-powered chatbots managing 70% of customer inquiries. However, significant challenges persist. Data privacy and security concerns were prominent, with 80% of Mauritius respondents and 60% in Lagos expressing apprehensions. Regulatory compliance emerged as a critical issue, suggesting that we require clearer guidelines to support AI implementation. Financial constraints and a lack of technical expertise further hinder widespread adoption, limiting SMEs’ ability to maximize AI’s potential. Despite these challenges, many respondents acknowledged AI’s role in driving business innovation, although some remained skeptical, emphasizing the necessity for stronger legal protections and ethical oversight. The study points out that it requires tailored policies, financial incentives, and AI literacy programs to support SMEs in leveraging AI for sustainable growth. Aligning with Sustainable Development Goal (SDG) 9, which promotes innovation and infrastructure, this research highlights AI’s transformative potential in enhancing the competitiveness of SMEs in developing economies. Future studies should explore AI adoption across additional sectors and integrate quantitative analysis for broader generalizability.

Abstract: In emerging economies such as India, small and medium enterprises (SMEs) act as the foundation for economic growth, contributing significantly to employment and the country’s GDP. Yet SMEs face dual challenges: attaining economic efficiency through digital transformation and attaining sustainability targets amidst growing environmental concerns. Artificial Intelligence (AI) has transformative potential, but its adoption in SMEs has been examined mostly from the perspective of cost-cutting and automation with limited consideration for sustainability. The existing research looks at AI adoption for efficiency or sustainability purposes separately, while the integration of AI in delivering sustainability advantage for SMEs receives little attention. Thus, there exists a vital research gap in their integration for a firm’s long-term competitiveness. To close this gap, this research proposes SME-AIGEN, a conceptual framework mapping AI adoption levels (Aware → Piloting → Integrated) against green maturity stages (Ad-hoc → Systematic → Certified). The framework identifies four strategic archetypes—Efficiency Seekers, Eco-Improvers, Digital Optimizers, and Sustainable Innovators—and suggests upgrade trajectories with targeted interventions. An integrative literature review methodology is used in this paper. Academic work and policy documents on application of AI in SMEs (predictive analysis, process optimization, and energy management), green practices, and Industry 4.0-driven sustainability in emerging economies have been studied. The findings emphasize the strategic role that AI plays in helping SMEs not merely to survive but prosper in a market that is competitive and driven by sustainability. This pioneering conceptual framework can form the foundation of future empirical studies and policy actions to encourage AI-enabled green transformation in the SME sector.

Artificial intelligence (AI) has become a popular technology of this era due to its potential to transform businesses. Therefore, various businesses are focused on adopting this technology to enhance their business. However, due to challenges, not all organizations can adopt AI for their business functions. Considering the importance of AI and small and medium-sized enterprises (SMEs) in the economy, this study aimed to examine the challenges and prospects of AI for SMEs. The study performed review-based research to examine past literature to determine the key challenges facing SMEs in AI integration. It was noted in the results that costs and technical requirements of AI remain the topmost challenges for SMEs to implement AI. These challenges remain the major hindrance to the adoption of AI, and thus, this study analyzes these issues deeply to provide organizations with the insight to overcome these problems. The study also noted that the prospects of AI in SMEs are great as the costs of AI are reducing, and with more research and development, AI integration will become more convenient. Therefore, this research provides key details into the problems facing AI adoption contemporarily and how they can be solved in the future.

The integration of Artificial Intelligence (AI) in Small and Medium-sized Enterprises (SMEs) and supply chains has revolutionized operational efficiencies and decision-making processes. This review paper aims to explore the ethical implications of AI adoption in these sectors, identifying current challenges and proposing future directions for ethical AI deployment. Through an extensive review of existing literature, the paper examines key ethical concerns such as data privacy, bias in AI algorithms, transparency, and the socio-economic impact on the workforce. The findings indicate that SMEs face unique ethical challenges due to their limited resources and expertise, which exacerbate issues related to AI implementation. Additionally, supply chains grapple with transparency and accountability, necessitating immediate attention to ensure ethical practices. The review concludes that establishing a robust ethical framework is crucial for guiding AI integration in SMEs and supply chains. It recommends the development of standardized ethical guidelines, enhanced stakeholder engagement, and increased investment in AI literacy and infrastructure. Future research should focus on creating adaptable ethical models that evolve alongside technological advancements and industry needs, ensuring that AI contributes to sustainable and equitable growth. This paper contributes to the ongoing discourse on ethical AI, offering actionable insights for policymakers, business leaders, and researchers dedicated to fostering responsible AI practices in SMEs and supply chains. Keywords: Ethical AI, SMEs (Small and Medium-sized Enterprises), Supply Chains, Algorithmic Bias, Data Privacy, Transparency, Accountability, AI Trust, Regulatory Compliance, Stakeholder Engagement, Job Displacement, Explainable AI (XAI), Workforce Reskilling, Sustainable AI Practices, AI Ethics Frameworks.

The rapid advancement of Artificial Intelligence (AI) has transformed business operations across the globe, with increasing relevance for Small and Medium Enterprises (SMEs) in emerging economies like India. This study investigates the impact of AI implementation on the performance, productivity, and competitiveness of Indian SMEs. By analyzing primary data collected through surveys and interviews with SME owners and managers across various sectors, and secondary data from industry reports, the research identifies key areas where AI technologies—such as machine learning, predictive analytics, and intelligent automation—are being adopted. The study reveals that AI adoption enhances operational efficiency, customer engagement, and decision-making processes in SMEs. However, it also highlights several challenges including high implementation costs, lack of technical expertise, and resistance to change. The findings underscore the critical role of government support, digital infrastructure, and upskilling initiatives in facilitating effective AI integration within SMEs. This research contributes to the understanding of AI's transformative potential for small businesses in developing nations and offers strategic recommendations for stakeholders to foster an inclusive and innovation-driven SME ecosystem in India..

The research examined how the integration of Artificial Intelligence (AI), the Internet of Things (IoT), and e-marketing can enhance the sustainability and competitiveness of Micro, Small, and Medium Enterprises (MSMEs). It addresses the gap in existing literature regarding the synergistic effects of these technologies in overcoming resource constraints often faced by MSMEs during digital transformation. While previous research has focused on the individual benefits of AI or IoT, limited attention has been given to their combined impact on e-marketing and its influence on MSME sustainability. The research applied a quantitative approach to survey 200 MSMEs in Denpasar City through a Likert-scale questionnaire and analyzed with PLS-SEM version 4.0. The findings reveal that AI improves access to e-marketing channels and operational efficiency, while IoT enhances data analytics and automates business processes. Their integrated adoption significantly boosts digital marketing performance, positively affecting MSME sustainability. The challenges identified include the high costs and expertise required for effective implementation. Nonetheless, with appropriate investment and technical support, AI, IoT, and e-marketing synergy can make MSMEs more sustainable. From a managerial perspective, the long-term integration of these technologies into business strategies is critical for sustaining growth in the digital era.

Artificial Intelligence (AI) is increasingly adopted by Small and Medium Enterprises (SMEs) to enhance financial decision-making processes. This study investigates the relationship between AI integration, financial awareness, and decision accuracy among SME managers. A structured questionnaire was administered to 200 SME decision-makers using three 40-item, 5-point Likert scales assessing AI usage, financial awareness, and decision accuracy. Descriptive statistics and Pearson correlation analysis were conducted using EDUSTAT software. The findings reveal moderately high mean scores in all three dimensions but no significant correlations among them. This suggests that while AI tools are being used, their impact on improving financial awareness and decision accuracy remains limited. The study highlights the importance of user training and strategic integration of AI systems to bridge this gap. Implications are drawn for policymakers, AI developers, and SME leaders aiming to optimize financial outcomes through technology-driven approaches.

This study explores the utilization of Artificial Intelligence (AI) in promoting creative economy products in Central Java's tourism areas, with a focus on Jatirejo Village, Semarang, known for its kolang-kaling production. As digital technology advances, AI presents substantial potential for enhancing the effectiveness, efficiency, and personalization of marketing strategies for local products, including batik, handicrafts, and culinary goods. Despite this potential, many small and medium enterprises (SMEs) in Central Java struggle to adopt AI due to limited resources, insufficient understanding of AI applications, and underdeveloped digital infrastructure. Using a qualitative descriptive approach, this research employs a case study method supported by in-depth interviews and direct observation. The findings reveal several challenges, such as a lack of digital literacy, financial constraints, and inadequate access to technology. However, the study also identifies significant opportunities for improvement. These include providing targeted training programs to increase AI literacy, fostering partnerships between SMEs, the government, and private sector actors, and improving supporting infrastructure to facilitate digital transformation. By addressing these barriers and leveraging collaborative efforts, AI can serve as a strategic tool to enhance promotional efforts and market reach for local creative products. This research contributes practical insights for policymakers, tourism authorities, and SME managers in designing inclusive, technology-driven strategies to support the growth of the creative economy in tourist regions. Ultimately, the integration of AI in promotional activities is expected to not only boost local economic development but also strengthen the cultural identity and competitiveness of creative products from Central Java on a broader scale.

The development of digital technology requires Micro, Small, and Medium Enterprises (MSMEs) to adapt in utilizing artificial intelligence (AI) as a strategy to improve digital literacy. The problems faced by MSMEs generally lie in limited technological understanding, lack of access to relevant digital information, and low utilization of interactive platforms that can support effective business management. These conditions hamper the ability of MSMEs to face the challenges of an increasingly competitive digital market. The purpose of this study is to examine the integration of AI in interactive websites as a means of transforming MSMEs' digital literacy, while also formulating an implementation model that can improve access to information, digital skills, and operational efficiency. The methods used include literature studies, field observations, and the development of an AI-based interactive website prototype with automatic data analysis features, learning content recommendations, and business digitalization guidelines. The results of the study indicate that the integration of AI in interactive websites can significantly improve MSMEs' digital literacy capabilities. MSMEs that were the subjects of the trial showed an increased understanding in the use of digital technology, optimization of online marketing strategies, and increased business productivity. The main conclusion of this study is that the implementation of AI-based interactive web not only plays a role as a digital education tool, but also as a strategic solution in reducing the digital literacy gap in MSMEs. This finding contributes to the development of knowledge in the field of digital transformation, especially in the use of artificial intelligence to support the empowerment of MSMEs in the digital economy era.

Small and Medium Enterprises (SMEs) are crucial players in the global economy, contributing over 50% of the world’s GDP and accounting for 70% of jobs globally (World Bank, 2021). In developing countries, SMEs make up a staggering 90% of all businesses, highlighting their vital role in driving innovation, local growth, and economic stability. Yet, these enterprises often grapple with significant hurdles, such as limited financial resources, inadequate technological infrastructure, and a shortage of skilled workers. Enter Artificial Intelligence (AI), a game-changing force that can help SMEs break through these barriers by streamlining operations, improving decision-making, and opening up new avenues for investment. McKinsey (2022) suggests that adopting AI could boost productivity by 15-20% and cut operational costs by 30% for SMEs. However, the OECD (2021) points out that only 15% of SMEs have embraced AI in their operations, in stark contrast to 56% of larger companies. Bringing AI into SME investments is more than just a tech upgrade; it represents a fundamental shift in how these businesses plan, allocate resources, and chase growth. This research delves into the strategic integration of AI in SMEs, examining the associated risks, the potential for skill development, and the long-term effects on investment choices. By exploring these aspects, the study aims to create a thorough framework that guides SMEs in making the leap toward AI-driven investments.

Financial inclusion is crucial for the growth and sustainability of small and medium-sized enterprises (SMEs), which are significant contributors to economic development and job creation. However, traditional banking models often fall short in serving the unique needs of SMEs due to perceived high risks and insufficient credit history. Leveraging artificial intelligence (AI) and data analytics, the banking sector can transform its approach to financial inclusion, offering tailored financial products and services that cater specifically to SMEs. AI and data analytics enable banks to analyze vast amounts of data from diverse sources, including transactional histories, social media activity, and market trends. This holistic view of an SME's financial health and business potential allows for more accurate risk assessment and credit scoring. Machine learning algorithms can identify patterns and predict creditworthiness, enabling banks to extend credit to SMEs that may have been overlooked by traditional models. Additionally, AI-driven insights facilitate the development of customized financial products, such as flexible loan terms and dynamic interest rates, that align with the cash flow cycles and operational realities of SMEs. Automated processes and AI-powered chatbots enhance customer service, providing SMEs with timely support and financial advice, thereby improving their banking experience. Data analytics also play a critical role in fraud detection and prevention, ensuring the security of transactions and building trust among SME clients. By continuously monitoring and analyzing transaction data, banks can quickly identify and mitigate fraudulent activities, protecting SMEs from financial losses. Moreover, AI and data analytics support the creation of financial literacy programs tailored to the specific needs of SMEs, empowering business owners with the knowledge and tools to make informed financial decisions. This educational aspect is vital in fostering a sustainable financial ecosystem for SMEs. In conclusion, the integration of AI and data analytics in the banking sector holds significant promise for promoting financial inclusion among SMEs. By providing more accessible, customized, and secure financial services, banks can support the growth and success of SMEs, ultimately contributing to broader economic development and financial stability.

This study examines the integration of Artificial Intelligence (AI) in the decision-making processes of Small and Medium Enterprises (SMEs) in Nigeria’s retail sector, focusing on its applications, benefits, challenges, and future prospects. Using a descriptive research design, data was collected through a Google Forms survey from 100 SME decision-makers. The findings reveal that while 70% of SMEs have adopted AI to some extent, only 20% have fully integrated it into their operations, with customer behavior analysis (60%) and inventory management (50%) being the most common applications. AI adoption has led to improved decision-making (65%) and enhanced operational efficiency (60%), yet significant barriers such as high implementation costs (70%) and a lack of technical expertise (65%) hinder wider adoption. Despite these challenges, 80% of respondents expressed interest in expanding AI usage in areas such as advanced customer analytics and supply chain optimization. The study concludes that while AI presents immense opportunities for SMEs to enhance competitiveness against larger e-commerce platforms, addressing financial, technical, and infrastructural barriers is crucial for wider adoption. It recommends affordable AI solutions, targeted training programs, improved financing options, policy support, and strategic partnerships to facilitate AI integration and long-term sustainability in Nigeria’s retail industry. Keywords: AI Optimization, Decision-Making, Small and Medium Enterprises (SMEs), Retail Industry, Business Intelligence, Nigeria JEL: O30, L81, M15, L25, M21, D81

Purpose: The paper shows the Artificial Intelligence (AI) company implementation process aimed at improving customer care, which is treated as an exemplification of crafting dynamic marketing capabilities. Design/methodology/approach: The study employs case study analysis, focusing on Philips in the health and well-being market. Findings: The paper provides Philips' AI integration process in customer care, emphasizing the use of GPT models and Retrieval Augmented Generation (RAG) to customize AI responses with company-specific data. Research limitations/implications: Future research should explore AI’s impact on other industries, incorporating quantitative financial and operational outcomes analysis. Longitudinal studies should assess how AI strategies evolve. Key areas for further investigation include ethical and privacy issues, AI implementation in small and medium enterprises (SMEs), and cross-cultural contexts. The research’s limitations include its single case study focus, lack of quantitative data, and short-term AI adoption analysis. Practical implications: AI tools, such as chatbots, can improve customer care efficiency, accuracy, and speed, reducing agent workload and enhancing consumer experiences. For Philips, AI integration in customer care leads to increased consumer satisfaction and loyalty. AI streamlines customer service, reduces operational costs, and allows businesses to scale support without proportional staffing increases, driving profitability and strengthening market positioning. However, human supervision remains critical to ensure accuracy and prevent AI-generated errors, while privacy safeguards must be in place to protect data. Originality/value: The study highlights AI's transformative role in helping businesses navigate market complexities and the use of new technology in improving customer care processes. Keywords: artificial intelligence, customer care, dynamic marketing capability, the health and well-being market. Category of the paper: case study.

Artificial Intelligence (AI) has emerged as a disruptive and transformative force in education as it offers potential benefits such as personalized learning, effective assessment methodologies, and automated administrative processes. This study examines the teachers' perspectives on AI integration in education, reflecting on their perceptions, prevalent challenges, and professional development practices required to empower the teachers with technical skills to ensure effective implementation of AI. A questionnaire was prepared, validated, and used to collect data from the teachers about their awareness and readiness to adopt emerging technologies such as AI, AR, and VR. Some open-ended questions were added to collect information regarding the challenges faced and supportive measures required for AI integration in Education.The research reveals that the majority of teachers reflected a positive attitude toward AI integration. Many educators realize that AI can fill quality gaps in education by making learning experiences more enriching, and student-centered, and enhancing assessment practice. Teachers also appreciate AI in terms of alleviating their burden and making the teaching-learning process student-centric. However, the report highlights major challenges faced by teachers in integrating AI in Education, including limited accessibility to AI-based resources, lack of training, ethical concerns, and data privacy. Concerns regarding resistance to change and infrastructure constraints complicate AI integration further. The study underscores the need for effective and professional training programs to equip and apprise teachers with the skills and confidence to integrate AI into teaching practices. Workshops, online courses, and hands-on training are preferred modes of professional development identified through the study. Moreover, Institutional policies must also align with the vision of NEP 2020 regarding AI in education. Policies also try to create friendly environments for using AI, reducing infrastructural bottlenecks or gaps, establishing ethical use guidelines, and involving teachers in processes of decision-making.This research has also emphasized the role of teachers in realizing AI’s potential and advocating for effective strategies needed to overcome challenges associated with AI Integration. By empowering teachers through adequate training and resources, the education sector can harness the power of AI to create an inclusive, effective, and future-ready learning environment.