We all know that when you undertake tertiary study, there will always be a unit you have to do that you're not really excited about. Business Research Methods was that unit for me. Having already completed a research honours in biochemistry, I didn't think there was much extra I could learn. However, the topic I chose was so interesting that I wanted to share it with you all. So here are the interesting bits from my research proposal - Opportunities and Barriers to Adopting Artificial Intelligence for Small and Medium Enterprises in Public Sector Consulting. Enjoy!
INTRODUCTION
The use of Artificial Intelligence (AI) in management consulting is having an impact on the business landscape (Cardinali et al., 2022). The 2024 McKinsey Global Survey on AI found that adoption of AI was up 72 per cent and the professional services industry was the highest adopter (McKinsey, 2024). Demand for AI products is also increasing as the technology becomes more accessible and people become more familiar with it (Ledovskikh, 2023). The OECD (2024) defines an AI system as “a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.”
The benefits of AI come from its ability to automate tasks, analyse large volumes of data, find patterns in the data, and support decision-making (Appio et al., 2024; Nafizah et al., 2023). Management consulting companies are using AI to accelerate business functions, generate new service offerings, improve customer relations, and create efficiencies (Yigitbasioglu et al., 2022; Singh & Pandey, 2024). To remain competitive, businesses will need to adopt AI or run the risk of being left behind (Díaz-Arancibia et al., 2024). This is particularly true for Small to Medium Enterprises (SMEs) who rely on their unique selling point to maintain competitive advantage (Yang et al., 2024).
Currently, SMEs make up 86.8% of the management consultancy industry in Australia (Reilly, 2023). However, SMEs have been slower to adopt digital technologies compared to larger enterprises (Schwaeke et al., 2024). This is because implementing AI requires substantial planning, technical expertise, a skilled workforce, and sufficient funding and time to implement (Kumar et al., 2022; Tominc et al., 2024). In addition, SMEs are more vulnerable to external disruptions (Appio et al., 2024), are less innovative (Badghish & Soomro, 2024), and need external help to implement digital transformation initiatives (Hansen et al., 2024).
To encourage more SMEs to adopt AI, it is important to understand what the opportunities and barriers are to adopting AI. Research studies have looked at this in customer service (Bhattacharyya, 2024), human resources (Singh & Pandey, 2024), accounting (Mihai & Dutescu, 2024), professional services (Yang et al., 2024), and education and health care (Pasca & Arcese, 2024) setting. However, there is limited research on AI adoption in management consultancy, in Australia, in the public sector, related to communications specialists.
This study will address this gap by exploring the opportunities and barriers to AI adoption by SMEs in public sector consulting within Australia. The study seeks to answer the following research questions: (1) What are the opportunities and barriers to SMEs adopting AI technologies? (2) What can be done to maximise the opportunities and minimise the barriers?
LITERATURE REVIEW
AI can improve productivity, increase efficiencies, and improve the customer experience (Almashawreh et al., 2024; Appio et al., 2024; Badghish & Soomro, 2024;). AI can also help businesses grow and expand through data driven strategies, informed decision-making, improved resource allocation and operational performance (Tominc et al., 2024; Schwaeke et al., 2024). AI fosters innovation through new product and service design and enables companies to sustain a competitive advantage (Costa et al., 2023; De Lucas Ancillo et al., 2021).
However, there are significant barriers faced by SMEs when adopting AI including financing, organisational readiness, compatibility, complexity and legal issues (Cardinali et al., 2022; Ridzuan Noorzelan et al., 2024). SMEs also lack the skilled workforce, do not see the value in adopting AI, lack the organisational and managerial readiness to implement innovations, and do not have the organisational culture that supports adoption (Hansen et al., 2024; Nimawat & Gidwani 2021). Employee attitudes, organisational leadership and resistance to change have also been identified as key barriers (De Lucas Ancillo et al., 2021; Díaz-Arancibia et al., 2024;). SMEs also lack the understanding of the costs and benefits of AI adoption to make informed return on investment decisions (Nafizah et al., 2023; Schwaeke et al., 2024). SMEs also tend to focus on the short-term strategy not long-term investment growth, as they are consumed by the day-to-day business operations (Kumar et al., 2022; Le-Dain et al., 2023). Additionally, ethical concerns with using AI, privacy, regulatory and liability concerns, cyber security, and data management and ownership issues all impact SMEs adopting AI (Booyse & Scheepers, 2023; Mihai & Dutescu, 2024).
To overcome these barriers, studies have suggested that SMEs should train their staff, keep up to date with technology developments, and engage external technical experts (De Lucas Ancillo et al., 2021). The development of digital transformation strategies and innovation policies may also help to ensure SMEs can take advantage of new technologies more rapidly (Appio et al., 2024;). Changes to government policies may also encourage SMEs to adopt AI. This may be through training, awareness, funding, and tax relief for technology investment (Oldemeyer et al.; 2024).
ABOUT THE AUTHOR
Prue Rhodes is an industry award-winning strategic communicator with over a decade of experience in Defence and Government. She commenced her professional career as a public servant in the Department of Defence before moving to the Department of the Prime Minister and Cabinet and the Attorney General's Department. From there, she successfully transitioned to the private sector where she continued to hone her strategic writing, communications and Defence capability skill set before stepping out on her own as Director of P Rhodes Advisory. Prue enjoys sharing her knowledge and experience with others and empowering staff to explore new possibilities.
REFERENCES
Almashawreh, R., Talukder, M., Charath, S. K., & Khan, M. I. (2024). AI adoption in Jordanian SMEs: The influence of technological and organizational orientations. Global Business Review. https://doi.org/10.1177/09721509241250273
Appio, F. P., Cacciatore, E., Cesaroni, F., Crupi, A., & Marozzo, V. (2024). Open innovation at the digital frontier: unraveling the paradoxes and roadmaps for SMEs’ successful digital transformation. European Journal of Innovation Management, 27(9), 223–247. https://doi.org/10.1108/ejim-04-2023-0343
Badghish, S., & Soomro, Y. A. (2024). Artificial intelligence adoption by SMEs to achieve sustainable business performance: Application of technology–organization–environment framework. Sustainability, 16(5), 1864. https://doi.org/10.3390/su16051864
Bhattacharyya, S. S. (2024). Study of adoption of artificial intelligence technology-driven natural large language model-based chatbots by firms for customer service interaction. Journal of Science and Technology Policy Management. https://doi.org/10.1108/jstpm-11-2023-0201
Booyse, D., & Scheepers, C. B. (2023). Barriers to adopting automated organisational decision-making through the use of artificial intelligence. Management Research Review, 47(1), 64–85. https://doi.org/10.1108/mrr-09-2021-0701
Cardinali, S., Pagano, A., Carloni, E., Giovannetti, M., & Governatori, L. (2022). Digitalization processes in small professional service firms: drivers, barriers and emerging organisational tensions. Journal of Service Theory and Practice, 33(2), 237–256. https://doi.org/10.1108/jstp-06-2022-0132.
Costa, A. C. F., Capelo Neto, F., Espuny, M., Rocha, A. B. T. da, & Oliveira, O. J. de. (2023a). Digitalization of customer service in small and medium-sized enterprises: drivers for the development and improvement. International Journal of Entrepreneurial Behavior & Research, 30(2/3), 305–341. https://doi.org/10.1108/ijebr-10-2022-0953
De Lucas Ancillo, A., Gavrila Gavrila, S., Fernández del Castillo Díez, J. R., & Corro Beseler, J. (2021). LATAM and Spanish SME barriers to Industry 4.0. Academia Revista Latinoamericana de Administración, 35(2), 204–222. https://doi.org/10.1108/arla-07-2021-0137
Díaz-Arancibia, J., Hochstetter-Diez, J., Bustamante-Mora, A., Sepúlveda-Cuevas, S., Albayay, I., & Arango-López, J. (2024). Navigating digital transformation and technology adoption: A literature review from small and medium-sized enterprises in developing countries. Sustainability, 16(14), 5946. https://doi.org/10.3390/su16145946.
Hansen, A. K., Christiansen, L., & Lassen, A. H. (2024). Technology isn’t enough for Industry 4.0: On SMEs and hindrances to digital transformation. International Journal of Production Research, 1–21. https://doi.org/10.1080/00207543.2024.2305800
Kumar, S., Raut, R. D., Aktas, E., Narkhede, B. E., & Gedam, V. V. (2022). Barriers to adoption of industry 4.0 and sustainability: a case study with SMEs. International Journal of Computer Integrated Manufacturing, 36(5), 657–677.
Le-Dain, M.-A., Benhayoun, L., Matthews, J., & Liard, M. (2023). Barriers and opportunities of digital servitization for SMEs: the effect of smart Product-Service System business models. Service Business, 17(1), 359–393. https://doi.org/10.1007/s11628-023-00520-4
Ledovskikh, A. (2023). Industry report OD5562 - Artificial intelligence in Australia. In IBISWorld. https://my.ibisworld.com/au/en/industry-specialized/od5562/at-a-glance
McKinsey. (2024, May 30). The state of AI in early 2024: Gen AI adoption spikes and starts to generate value | McKinsey. McKinsey and Company. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai#/
Mihai, M., & Dutescu, A. (2024). TOE framework elements used on Artificial Intelligence implementation in the accounting and audit sector. International Journal of Research in Business and Social Science (2147- 4478), 13(4), 335–349. https://doi.org/10.20525/ijrbs.v13i4.3374
Nafizah, U. Y., Roper, S., & Mole, K. (2023). Estimating the innovation benefits of first-mover and second-mover strategies when micro-businesses adopt artificial intelligence and machine learning. Small Business Economics, 62(1), 411–434.
Nimawat, D., & Gidwani, B. D. (2021). Identification of cause and effect relationships among barriers of Industry 4.0 using decision-making trial and evaluation laboratory method. Benchmarking: An International Journal, 28(8), 2407–2431. https://doi.org/10.1108/bij-08-2020-0429
OECD. (2024). Explanatory Memorandum on the Updated OECD Definition of an AI System. In OECD (pp. 1–11). OECD Publishing. https://www.oecd.org/en/publications/explanatory-memorandum-on-the-updated-oecd-definition-of-an-ai-system_623da898-en.html.
Oldemeyer, L., Jede, A., & Teuteberg, F. (2024). Investigation of artificial intelligence in SMEs: a systematic review of the state of the art and the main implementation challenges. Management Review Quarterly. https://doi.org/10.1007/s11301-024-00405-4
Pasca, M. G., & Arcese, G. (2024). ChatGPT between opportunities and challenges: an empirical study in Italy. The TQM Journal, ahead-of-print. https://doi.org/10.1108/tqm-08-2023-0268
Reilly, M. (2023). Industry report M6962A - Management consulting in Australia. In IBISWorld. IBISWorld Pty Ltd. https://my.ibisworld.com/au/en/industry/m6962a/at-a-glance
Ridzuan Noorzelan, M., Kamarudin, M., & Masrom, R. (2024). Exploring the challenges of Industry 4.0 entrepreneurs: A grounded theory approach. Journal of Technology Management and Technopreneurship, 12(1), 10–23. https://jtmt.utem.edu.my/jtmt/article/view/6083
Schwaeke, J., Peters, A., Kanbach, D. K., Kraus, S., & Jones, P. (2024). The new normal: The status quo of AI adoption in SMEs. Journal of Small Business Management, 1–35. https://doi.org/10.1080/00472778.2024.2379999
Singh, A., & Pandey, J. (2024). Artificial intelligence adoption in extended HR ecosystems: enablers and barriers. An abductive case research. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1339782.
Tominc, P., Oreški, D., Čančer, V., & Rožman, M. (2024). Statistically significant differences in AI support levels for project management between SMEs and large enterprises. AI, 5(1), 136–157. https://doi.org/10.3390/ai5010008
Yang, J., Blount, Y., & Amrollahi, A. (2024). Artificial intelligence adoption in a professional service industry: A multiple case study. Technological Forecasting and Social Change, 201, 123251. https://doi.org/10.1016/j.techfore.2024.123251
Yigitbasioglu, O., Green, P., & Cheung, M.-Y. D. (2022). Digital transformation and accountants as advisors. Accounting, Auditing & Accountability Journal, 36(1), 209–237. https://doi.org/10.1108/aaaj-02-2019-3894.
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