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AI Adoption for Small and Medium-Sized Enterprises

Cloud computing and modular AI solutions are closing the technology gap between SMEs and large corporations.

Farah MitchellFarah Mitchell·
AI adoption for SMEs visual

According to PwC's (2021) research, the technology gap between large-scale enterprises and SMEs is closing rapidly thanks to scalable and customizable AI solutions. The PwC report emphasizes that declining costs are making AI-based technologies an economically viable option for small businesses as well. Marchetti and Scardovi's (2024) study proves that the potential of AI solutions to reduce operational costs and boost productivity is no longer exclusive to companies with massive budgets.

Barriers are falling one by one for SMEs

Violini and Brown (2020) note that small and medium-sized enterprises have historically stayed away from these technologies due to high implementation costs and a lack of technical expertise. Research by Sanyaolu and Atsaboghena (2022) identifies complex software maintenance processes and data quality issues as the biggest obstacles in SME AI projects. Wang and team (2016) demonstrate that cloud-based HR systems eliminate the infrastructure burden, offering SMEs flexible and low-cost data processing power. As emphasized by Diyin et al. (2024), AI serves as a strategic driving force enabling SMEs to remain more agile and competitive.

Scalability and operational efficiency

Venkanna and colleagues (2025) show that modular AI interview simulators standardize interview procedures, making the process far more scalable. Thanks to ease of integration, these systems enable companies of all sizes to reach the highest talent assessment standards. Kupiec's (2025) study documents that AI's capacity to analyze large data sets equips small HR teams with massive processing power, noting that the ability to conduct numerous interviews simultaneously contributes directly to the growth pace of SMEs.

SMEs' new "Superpower" in the talent hunt

Marchetti and Scardovi's (2024) research shows that AI tools make communication with candidates more targeted, thereby elevating SMEs' brand value. Sahu (2025) predicts that multilingual support capabilities to be added in the future will completely remove the barriers preventing small firms from accessing global talent markets. As noted in IBM's (2018) report, AI-powered "skills inference" methods enable SMEs to discover brilliant talent that traditional filters might overlook. This digital integration can be of vital importance for SMEs seeking to build a sustainable business model.

Thus, the scalable and cost-effective strategies offered by AI can create a level playing field in the business world. Innovation-driven SMEs can compete with industry giants by using AI as a "bridge" rather than a "barrier." As emphasized by Drela and team (2025), small businesses that blend AI with human expertise can rise to a significantly more advantageous position when it comes to building the most engaged and productive workforce in the digital age. In this way, the democratization of technology can transform SMEs into the powerful talent magnets of tomorrow.

References

  • Diyin, Z., Bhaumik, A., & Wang, D. (2024). Artificial Intelligence's Impact on Hr and Talent Acquisition. Journal of Electrical Systems, 20-11s, 4879-4885.
  • Drela, K., Grabowska, A., & Brojak-Trzaskowska, M. (2025). The Future of AI in HRM. A Case Study of the HR Decision-Making. 28th European Conference on Artificial Intelligence (ECAI 2025).
  • IBM. (2018). The Business Case for AI in HR. IBM Smarter Workforce Institute.
  • Kupiec, T. (2025). AI-supported individual interviews: opportunities and threats for evaluation. Polski Przegląd Ewaluacyjny.
  • Marchetti, D., & Scardovi, R. (2024). Artificial Intelligence and Human Resources: innovative trends and main impacts. Master Thesis, Politecnico di Milano.
  • PwC. (2021). AI Predictions 2021: Narrowing the Gap.
  • Sahani, K. K., et al. (2025). A smart interview simulator using AI avatars and real-time feedback mechanisms. International Journal of Engineering Technologies and Management Research.
  • Sahu, A., et al. (2025). AI Interviewer Using Generative AI. ICAAAI 2025 Proceedings.
  • Sanyaolu, E., & Atsaboghena, R. (2022). Role of Artificial Intelligence in Human Resource Management: Overview of its benefits and challenges. Journal of Business Ethics.
  • Venkanna, G., et al. (2025). AI Interview Simulator: An Intelligent Hiring & Preparation Assistant. ICCSCE 2025 Proceedings.
  • Violini, E., & Brown, D. (2020). The social enterprise at work: Paradox as a path forward. Deloitte Global Human Capital Trends.
  • Wang, X. L., et al. (2016). Cloud computing in human resource management (HRM) system for small and medium enterprises (SMEs). The International Journal of Advanced Manufacturing Technology.