Role of Generative AI in Small and Medium Enterprises: Opportunities & Challenges

Komal Amre, K Vaishnav Gandhi, Shriya Mhatre, Nandini Vyas · Zenodo (CERN European Organization for Nuclear Research) · 4 Jul 2026

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Where this sits in the debate

Will AI actually boost productivity and growth? · its finding: it depends (why studies differ)

Direction of the finding as read from the abstract by an AI model (AI-written).

Key takeaway AI-written

A literature synthesis of 2022–2025 studies on generative AI in SMEs, finding a persistent "awareness–adoption gap": SMEs increasingly know about AI's productivity and customer-engagement potential but implementation lags due to cost, skills shortages, organizational resistance, and cybersecurity concerns. It matters because SMEs are the bulk of employment in most economies, so if AI diffusion stalls at the SME level, aggregate productivity gains from AI will be concentrated in large firms and slow to show up in macro data—reinforcing the diffusion-lag view of AI's economic impact.

The paper in three steps AI-written

Written by an AI agent from the paper's abstract, which is the primary source and is quoted below.

The question

What opportunities and obstacles does generative AI bring for small and medium enterprises?

The approach

A review synthesizing studies published between 2022 and 2025 on AI integration in SMEs.

The findings

Awareness of AI is rising but practical implementation is slow, an awareness-adoption gap driven by implementation costs, lack of technical expertise, resistance to change and cybersecurity risks.

How to read it: review. A synthesis of existing studies — breadth over novelty; quality depends on what it includes and excludes.

Limitations and counterpoints AI-written

A literature synthesis with no new data; the abstract does not state how studies were selected.

Abstract

AbstractSmall and Medium Enterprises (SMEs) are essential contributors to global economic growth, innovation, and employment, yet they face unique barriers in their digital transformation journeys. The emergence of generative artificial intelligence (AI) presents a significant opportunity for SMEs to enhance productivity, strengthen customer engagement, and build competitive advantage. Applications of AI in areas such as process automation, predictive analytics, and personalised services offer potential for innovation and long-term growth. However, adoption remains limited due to persistent challenges, including high implementation costs, shortage of technical expertise, organisational resistance to change, and cybersecurity vulnerabilities. This paper synthesises findings from recent studies (2022–2025) to examine both the opportunities and challenges associated with AI integration in SMEs. The review highlights that while awareness of AI technologies is rising, practical implementation is slow, indicating a critical awareness–adoption gap. To bridge this divide, SMEs must adopt phased and strategic approaches, supported by employee training, enabling policy incentives, and human-centred AI practices that balance technological potential with ethical considerations.

About this publication

Preprint. A preprint — posted publicly before or without journal peer review; findings may still be revised.

Published: 2026 (4 months ago)
Citations: 0 (OpenAlex)