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The Impact of AI Automation on Small to Medium Sized Enterprises (SMEs)

Pastel, Lucas (2025)

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Pastel, Lucas
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025052013646
Tiivistelmä
Artificial intelligence (AI) automation is now a strategic tool to boost the efficiency and competitiveness of small and medium sized enterprises (SMEs), but strong systematized evidence of its financial and operational impact is still lacking. This thesis explored how AI automation impacts the cost structures, productivity, and opportunities for growth of SMEs. The study focused on firms with fewer than 250 employees and took a qualitative methods design combining a structured review of the existing research on the period from 2019 to 2025 with qualitative case study research on four real companies using content analysis as the research method. The case studies were purposefully selected to illustrate practical outcomes in retailing, professional services, logistic services, and e-commerce firms. The study was conducted between January 2025 and May 2025.

These results show that SMEs spent a median USD 1.8 k annually on AI solutions and realized median annual savings of USD 7.5 k and had positive return on investment in most cases in twelve months. Productivity improvements ranged from 20 to 40 percent shorter process cycle times, considerable reduction of errors, and a saving of 13 hours per week on average by owners and employees. Major barriers were low budgets, shortages of skills and data quality issues, while cloud based software, phased rollout and external experts were found to be key solutions.

The research exemplifies how AI automation enables SMEs to scale up operations without associated labor costs and make better decisions using data driven insights. The recommendations are pragmatic and include the use of low cost cloud solutions to start with, the rollout of readiness audits, and the inclusion of ethics and compliance from the outset. The research presents empirical benchmarks to the stakeholders of SMEs and a robust action map to leverage AI benefits and sidestep common snares.
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