Interconnected AI agents poised to revolutionize SMME competitiveness and resilience

A comprehensive systematic review has identified agentic artificial intelligence (AI) as a transformative force capable of reshaping operations, decision-making, and ecosystem collaboration within small, medium, and micro-enterprises (SMMEs). The study, titled “Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents”, was published in AI and offers the first structured synthesis of how interconnected autonomous agents can help SMMEs address persistent technological, infrastructural, and ethical barriers.

Drawing from 66 peer-reviewed and grey literature sources published between 2019 and 2024, the research applies the PRISMA 2020 framework to uncover emerging trends in agentic AI design, implementation, and impact across diverse sectors. The findings show that agentic AI systems, defined as autonomous, goal-directed agents capable of adaptive learning and decentralized collaboration, are enabling SMMEs to scale operations, improve responsiveness, and integrate into broader digital ecosystems.

How are agentic AI systems shaping operational efficiency in SMMEs?

The review reveals that SMMEs are increasingly relying on agentic AI frameworks to automate routine tasks, optimize workflows, and facilitate real-time decision-making. These AI agents operate independently, but are interconnected within a business’s digital infrastructure, allowing them to learn from data, adjust strategies dynamically, and interact with other systems and agents across the ecosystem.

A notable advantage of agentic AI lies in its modularity and ability to function in resource-constrained environments. Unlike traditional enterprise software, agentic systems are more flexible and do not require extensive computational infrastructure, making them ideal for smaller firms. Use cases identified in the study include inventory management, customer service automation, supply chain coordination, and predictive analytics.

The agents exhibit properties of contextual awareness and cognitive adaptability, enabling them to learn from environmental changes and stakeholder feedback. In doing so, they provide decision support to human managers while maintaining operational continuity even under uncertain or rapidly changing conditions. This agentic capacity enhances organizational resilience - a critical asset for SMMEs operating in volatile markets.

What challenges are addressed by ecosystemic interconnected agents?

A central contribution of the study is its analysis of ecosystemic interconnected agents, agentic AI systems designed not only for internal optimization but also for outward-facing collaboration within digital business ecosystems. These agents engage with external partners, platforms, and institutions, forming dynamic value networks that facilitate resource sharing, market access, and co-innovation.

Such interconnected architectures are particularly beneficial for SMMEs seeking to integrate into supply chains or participate in platform-based economies. By automating inter-organizational transactions and compliance monitoring, agentic AI reduces friction in digital collaboration and helps firms meet regulatory and market demands more efficiently.

The study notes that SMMEs often suffer from weak digital infrastructure and fragmented data practices. Agentic AI mitigates these limitations by decentralizing intelligence and reducing reliance on centralized data systems. Agents can process data locally and interact through standardized protocols, enabling interoperability without complex integration costs.

Furthermore, agentic frameworks support ethical and transparent decision-making by enabling traceability, adaptive governance, and stakeholder-specific customization. The research highlights that this adaptability is critical for fostering trust and regulatory compliance in data-sensitive sectors such as health, fintech, and agribusiness.

What are the research gaps and strategic implications for SMMEs?

While the study affirms the strategic promise of agentic AI, it also underscores significant gaps in implementation, education, and infrastructure. Many SMMEs lack awareness of agentic AI capabilities, and few possess the technical expertise to deploy and maintain such systems. The review calls for investment in digital literacy, platform interoperability, and low-code/no-code AI development environments tailored to small enterprises.

The study recommends that policymakers and innovation agencies provide support mechanisms, including financial incentives, technical guidance, and regulatory sandboxes, to facilitate responsible adoption. It also suggests that academia and industry collaborate to develop sector-specific agentic AI templates that reduce barriers to entry.

Another gap lies in the limited empirical validation of long-term outcomes. Most studies in the review focus on conceptual models, prototypes, or pilot projects. The authors call for longitudinal research to evaluate how agentic AI affects firm performance, employment patterns, and ethical accountability over time.