The integration of artificial intelligence (AI) into small, medium and micro enterprises (SMEs) has gained traction in recent years, signaling an evolution in the way these businesses operate in competitive markets. In an illuminating exploration of this phenomenon, Olujimi, Owolawi, Pretorius and colleagues meticulously conducted a bibliometric analysis that maps the complex research landscape surrounding agentic AI in SMEs. Their findings not only shed light on existing models, but also highlight critical knowledge gaps that need to be addressed to foster a robust understanding of the role of AI in this area.
Understanding what constitutes agentic AI is essential to understanding its potential impact on SMEs. Unlike traditional AI systems that operate primarily within given parameters, agentic AI refers to intelligent systems capable of making independent decisions. This attribute allows them to adapt to changing circumstances and perform tasks with minimal human oversight. For SMBs, this means an unprecedented opportunity to improve efficiency and scalability. Imagine a small business using AI to analyze consumer behaviors in real time, adapting marketing strategies on the fly to optimize sales. The growth potential is significant.
The bibliometric analysis conducted by the authors constitutes a fundamental resource for academics, industry practitioners and policy makers. By reviewing scientific articles, conference papers, and other forms of research output, the authors elucidate trends in academic discourse surrounding applications of agentic AI within SMEs. Through this rigorous approach, they reveal how knowledge in this area has evolved and where it is currently lacking. Their work provides a comprehensive overview that could inform future research programs and guide investment decisions.
Of particular note, the research highlights a growing recognition of the transformative power of AI technologies among SME owners and operators. Many companies are beginning to understand that AI is not only a technological advancement but also a strategic asset. This change in perception could potentially lead more SMEs to adopt these technologies, thereby strengthening their competitive advantage. However, the study also highlights significant barriers hindering AI adoption, including lack of technical expertise, financial constraints, and the rapid pace of technological change that can prevent businesses from keeping pace.
Additionally, the authors highlight knowledge gaps related to practical applications of agentic AI in various sectors of the SMME sector. While some industries have adopted AI with remarkable success, others are lagging behind, revealing a disparity in adoption rates that merits further investigation. These findings invite a closer look at how different industries can leverage the benefits of agentic AI and understand the industry-specific challenges that come into play.
The bibliometric analysis further highlights the need for interdisciplinary collaboration to develop effective AI solutions for SMEs. Researchers, technologists and business leaders must come together to create frameworks that meet the unique needs of small and medium-sized businesses. Without this spirit of collaboration, the potential benefits of agentic AI could remain largely untapped, leading to missed opportunities for innovation and growth.
In addition to clarifying current trends, the research has also sparked discussions about the ethical implications of deploying AI in smaller business contexts. As AI systems become more autonomous, questions around accountability, privacy, and decision-making become increasingly relevant. SMEs must manage these complexities while reassuring customers and stakeholders of their commitment to ethical AI practices. This emerging concern highlights the need to create clear guidelines and accountability mechanisms to govern the use of AI in SMEs, thereby ensuring trust in these evolving technologies.
Looking ahead, the authors advocate greater investment in education and training tailored to SME owners and employees. Equipping individuals with the skills to engage in agentic AI not only improves the technology landscape, but also strengthens the economic viability of these companies. By fostering a workforce that is proficient in AI capabilities, SMEs can remain adaptable and competitive in an increasingly digital economy, able to leverage AI’s potential for growth.
As the research landscape evolves, the results of bibliometric analysis highlight the importance of continued exploration and investigation in this area. As agentic AI evolves, the global research community must remain vigilant and anticipate new trends and changes that may influence SMME operations. This proactive approach to research will be key to harnessing the full potential of AI technologies and ensuring that SMEs can thrive amid rapid digital transformation.
The implications of the study extend beyond academic circles; Industry players need to pay close attention to the rapidly evolving role of AI in SMEs. Insights gained from understanding bibliometric models can guide investments in AI-based solutions that specifically address the needs of small businesses. Understanding where research is going and identifying knowledge gaps can allow companies and investors to target their resources effectively.
In summary, the investigation of agentic AI in SMEs is not only about technological progress; it is a comprehensive examination of how businesses can adapt and thrive in an increasingly digital world. The research conducted by Olujimi and colleagues provides a critical resource for understanding the agentic AI landscape and highlights critical gaps that must be addressed for continued progress. The book presents an encouraging vision of a future where SMEs not only survive but thrive in the face of digital transformation, thanks to the promise offered by AI technologies.
In conclusion, the era of agentic AI in SMEs is upon us, presenting a myriad of opportunities that have the potential to reshape the business landscape. This wave of innovation invites SMEs to consider the benefits of AI integration, guiding them towards new horizons of growth, efficiency and competitive advantage. As the research community continues to explore these frontiers, this journey will undoubtedly unveil even more possibilities, ensuring that SMEs not only adapt but thrive in an era defined by technological progress.
Research subject: Agentic AI in small, medium and micro-enterprises (SMME)
Article title: Mapping the agentic AI research landscape in SMEs through bibliometric analysis of patterns and knowledge gaps.
Article references:
Olujimi, PA, Owolawi, PA, Pretorius, A. et al. Mapping the research landscape on agentic AI in SMEs through bibliometric analysis of patterns and knowledge gaps.
Discovery Artif Intell (2025). https://doi.org/10.1007/s44163-025-00764-1
Image credits: AI generated
DOI: 10.1007/s44163-025-00764-1
Keywords: Agentic AI, small and medium businesses, bibliometric analysis, AI adoption, digital transformation, business efficiency.
Tags: Agentic AI in Small BusinessesIntegrating AI in Small and Medium BusinessesAI-Based Marketing Strategies for SMEsBibliometric Study of AI in SMEsCompetitive Advantages of AI in Small BusinessesImproving Efficiency with AIFuture Trends in Agentic AI for BusinessImpact of AI on Micro BusinessesIndependent Decision-Making in AIKnowledge Gaps in Applications Real-Time Consumer Behavior AnalysisAgentic AI Research Landscape