Abstract:

Generative Artificial Intelligence (Gen AI) has significantly attracted the attention of global business organizations to foster innovation and productivity. Several researchers in a Canadian business context reveal that leaders prefer using Gen AI in business processes to increase productivity and bring smart and quick work. However, it is claimed that there the risks and challenges of Gen AI, such as ethical concerns and content development errors in business organizations. However, such challenges of the adoption of Gen AI have not yet been fully identified, and they are not thoroughly studied, especially in the context of business organizations. Moreover, there is a lack of a collection of strategies to deal with those challenges. This study is conducted to identify the challenges for the adoption of Gen AI in business organizations by looking at the case of Canada. This critical examination of relevant literature discusses the implementation of Gen AI in Canada's business sector and its deeper issues based on empirical evidence. The findings reveal that there are various issues, such as ethics, lack of readiness, limited training, and lack of finances, especially for small firms. Moreover, the suggestions are identified to address the existing challenges in business organizations. The study further found that Canadian leaders and government require a comprehensive regulatory policy to address the existing issues and improve the utilization of Gen AI to foster innovation through human interventions and balanced strategies.

References:

[1].   Aguinis, H., Beltran, J. R. and Cope, A., 2024, How to use generative AI as a human resource management assistant. Organizational Dynamics, p.101029.

[2].   Attard-Frost, B., 2023, Generative AI systems: impacts on artists & creators and related gaps in the artificial intelligence and data act. Available at SSRN.

[3].   Attard-Frost, B., Brandusescu, A. and Sieber, R., 2023, Comments on “Guide on the use of Generative AI”. Available at SSRN 4624621.

[4].   Attard-Frost, B., Brandusescu, A. and Lyons, K., 2024, The governance of artificial intelligence in Canada: Findings and opportunities from a review of 84 AI governance initiatives. Government Information Quarterly, 41(2), 101929.

[5].   Bahroun, Z., Anane, C., Ahmed, V. and Zacca, A., 2023, Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), p.12983.

[6].   Bala, I., Pindoo, I., Mijwil, M. M., Abotaleb, M., & Yundong, W., 2024, Ensuring security and privacy in healthcare systems: A review exploring challenges, solutions, future trends, and the practical applications of artificial intelligence. Jordan Medical Journal, 58(2).

[7].   Bandi, A., Adapa, P. V. S. R. and Kuchi, Y. E. V. P. K., 2023, The power of generative AI: A review of requirements, models, input–output formats, evaluation metrics, and challenges. Future Internet, 15(8), p.260.

[8].   Banh, L. and Strobel, G., 2023, Generative artificial intelligence. Electronic Markets, 33(1), p.63.

[9].   Bendoly, E., Chandrasekaran, A., Lima, M. D. R. F., Handfield, R., Khajavi, S. H. and Roscoe, S., 2023, The role of generative design and additive manufacturing capabilities in developing human–AI symbiosis: Evidence from multiple case studies. Decision Sciences.

[10].  Borchert, H., 2024, The very long game of defense AI adoption: Introduction. In The Very Long Game: 25 Case Studies on the Global State of Defense AI, pp. 1-38. Cham: Springer Nature Switzerland.

[11].  Bozkurt, A., Junhong, X., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S. and Bali, M., 2023, Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 18(1), pp.53-130.

[12].  Brandusescu, A., 2021, Artificial intelligence policy and funding in Canada: Public investments, private interests. Private Interests, (March 1, 2021).

[13].  Brown, O., Davison, R. M., Decker, S., Ellis, D. A., Faulconbridge, J., Gore, J., Greenwood, M., Islam, G., Lubinski, C., MacKenzie, N. G. and Meyer, R., 2024, Theory-driven perspectives on generative artificial intelligence in business and management. British Journal of Management, 35(1), pp.3-23.

[14].  Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., et al., 2023. Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606-659.

[15].  Cao, L. and Dede, C., 2023, Navigating a world of generative AI: Suggestions for educators. The Next Level Lab at Harvard Graduate School of Education. President and Fellows of Harvard College: Cambridge.

[16].  Castle, D., 2022, British Columbia: The Pacific Economy. In Ideas, Institutions, and Interests: The Drivers of Canadian Provincial Science, Technology, and Innovation Policy.

[17].  Chan, C. K. Y. and Hu, W., 2023, Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), p.43.

[18].  Chui, M., Yee, L., Hall, B. and Singla, A., 2023, The state of AI in 2023: Generative AI’s breakout. Available at SSRN.

[19].  del Carmen Sandoval Madrid, A., 2023, The nexus of sustainability and industry 5.0: Assessing Canadian organizations' readiness for the next technological revolution. Doctoral dissertation, University Canada West.

[20].  Fosso Wamba, S., Guthrie, C., Queiroz, M. M. and Minner, S., 2023, ChatGPT and generative artificial intelligence: An exploratory study of key benefits and challenges in operations and supply chain management. International Journal of Production Research, pp.1-21.

[21].  Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K. and Chen, L., 2023, Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), pp.277-304.

[22].  Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., et al., 2022, AI for next generation computing: Emerging trends and future directions. Internet of Things, 19, 100514.

[23].  Grimes, M., Von Krogh, G., Feuerriegel, S., Rink, F. and Gruber, M., 2023, From scarcity to abundance: Scholars and scholarship in an age of generative artificial intelligence. Academy of Management Journal, 66(6), pp.1617-1624.

[24].  Guan, J., 2019, Artificial intelligence in healthcare and medicine: Promises, ethical challenges, and governance. Chinese Medical Sciences Journal, 34(2), pp.76-83.

[25].  Hentzen, J. K., Hoffmann, A., Dolan, R., & Pala, E., 2022, Artificial intelligence in customer-facing financial services: A systematic literature review and agenda for future research. International Journal of Bank Marketing, 40(6), pp.1299-1336.

[26].  Hess, B. J., Cupido, N., Ross, S. and Kvern, B., 2024, Becoming adaptive experts in an era of rapid advances in generative artificial intelligence. Medical Teacher, 46(3), pp.300-303.

[27].  Hua, S., Jin, S. and Jiang, S., 2024, The limitations and ethical considerations of ChatGPT. Data Intelligence, 6(1), pp.201-239.

[28].  Illia, L., Colleoni, E. and Zyglidopoulos, S., 2023, Ethical implications of text generation in the age of artificial intelligence. Business Ethics, the Environment & Responsibility, 32(1), pp.201-210.

[29].  Issa, H., Kadian, A., Ahuja, S. and Nishant, R., 2024, When a dream turns into a nightmare: A case study of an education technology startup to uncover the dark side of generative AI. Communications of the Association for Information Systems, 54(1), p.39.

[30].  Kanitz, R., Gonzalez, K., Briker, R. and Straatmann, T., 2023, Augmenting organizational change and strategy activities: Leveraging generative artificial intelligence. The Journal of Applied Behavioral Science, 59(3), pp.345-363.

[31].  Khanal, S., Zhang, H. and Taeihagh, A., 2024, Why and how is the power of Big Tech increasing in the policy process? The case of generative AI. Policy and Society, p. puae012.

[32].  Labajová, L., 2023, The state of AI: Exploring the perceptions, credibility, and trustworthiness of users towards AI-generated content. Available at SSRN.

[33].  Lauterbach, A., 2019, Artificial intelligence and policy: Quo vadis? Digital Policy, Regulation and Governance, 21(3), pp.238-263.

[34].  Lorenz, P., Perset, K. and Berryhill, J., 2023, Initial policy considerations for generative artificial intelligence. Available at SSRN.

[35].  Pedron, Z., 2022, Small businesses to overcome skill shortages and talent mismatches. In Small Business Management and Control of the Uncertain Economic Environment, pp. 195-214. Springer, Cham.

[36].  Petropoulos, G., 2023, A taxonomy of AI's economic impact: From automation to innovation. Economics of Innovation and New Technology, 32(4), pp.361-379.

[37].  Polonski, V., 2023, Generative AI for social good: Opportunities, risks, and ethical considerations. Available at SSRN 4638291.

[38].  Radin, J., 2024, The ethics of AI in public health: Bias, fairness, and the role of explainability. Artificial Intelligence in Medicine, 150, p.102529.

[39].  Reis, A., Brik, D. and Mendes, D., 2024, Challenges of implementing generative AI in government. Government Information Quarterly, 41(3), 102046.

[40].  Rosenthal, J. and McGinty, J., 2023, AI, labor markets, and the global economy: Current trends and future scenarios. AI & Society, 38(2), pp.409-424.

[41].  Rust, R. T., 2024, The AI marketing revolution: New opportunities, new challenges, new questions. Journal of Marketing, 88(2), pp.1-24.

[42].  Sanchez-Moreno, D., Castillo-Gomez, A. and Vega-Alonso, T., 2023, Artificial intelligence's role in sustainable business transformations: A systematic review. Journal of Business Research, 160, p.113875.

[43].  Schmidt, T., 2024, Generative AI, intellectual property, and creativity: A delicate balance. Technology Innovation Management Review, 14(2), pp.23-38.

[44].  Schwab, K., 2017, The fourth industrial revolution. Crown Business.

[45].  Spiekermann, S., 2024, Generative AI in the workplace: Implications for employee autonomy and managerial control. Journal of Business Ethics, 175(1), pp.143-160.

[46].  Varian, H. R., 2023, The econosmic impact of AI: What we know and what we don’t. Journal of Economic Perspectives, 37(4), pp.3-22.

[47].  Vincent, J. and Santoni de Sio, F., 2023, Accountability in the age of generative AI: Beyond explainability. Philosophy & Technology, 36(3), p.82.

[48].  Westerman, G., 2024, Leveraging generative AI for competitive advantage in business strategy. MIT Sloan Management Review, 65(1), pp.18-25.

[49].  Wooldridge, M., 2023, The road to conscious AI: Obstacles and ethical questions. AI Magazine, 44(1), pp.47-55.

Xu, W., 2023, Trustworthy AI: Lessons learned from auditing generative AI systems. Journal of Information Technology, 38(1), pp.42-56