A Positioning Framework for Generative AI and Robotics to Support Insourcing and Reduce Outsourcing Dependency

AI is predicted to contribute $15.7 trillion to the global economy by 2030, higher than the combined output of India and China. Both the US and UK governments have announced programmes to embrace AI in 2025. There are many case studies of companies achieving cost savings such as Klarna reducing marketing costs by $10m. AI has now been extended into providing content which is referred to as Generative AI (GenAI). Generative AI has the potential to revolutionise the way work is undertaken across all industries, with predictions expecting AI to automate half of all work between 2040 and 2060. Recent advances in GenAI and robotics are transforming organisational decision-making, production capabilities, and global supply chains. While prior research has extensively discussed the economic and ethical implications of these technologies, there is limited theoretical guidance to support organisations in systematically adopting GenAI and robotics to enable insourcing and reverse long-standing outsourcing practices. This paper addresses this gap by proposing a holistic positioning framework to support organisational decision-making regarding GenAI and robotics adoption. Using a thematic analysis of academic literature, sixteen GenAI adoption challenges were identified and synthesised into four core dimensions, Human, Organisational, Environmental, and Technical, augmented by a fifth dimension addressing robotics-specific factors. This research contributes a novel positioning framework to the emerging GenAI and robotics literature and offers practical value for organisations considering insourcing as an alternative to trade tariffs and offshoring.

Generative AI, Robotics, Positioning Framework, Insourcing, Reshoring

1. AIVA. (2025). AIVA, the AI Music Generation Assistant. https://www.aiva.ai/ [Google Scholar] [Crossref]

2. Al-Busaidi, A. S., Raman, R., Hughes, L., Albashrawi, M. A., Malik, T., Dwivedi, Y. K., Al- Alawi, T., AlRizeiqi, M., Davies, G., Fenwick, M., Gupta, P., Gurpur, S., Hooda, A., Jurcys, P., Lim, D., Lucchi, N., Misra, T., Raman, R., Shirish, A., & Walton, P. (2024). Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights. Journal of Innovation & Knowledge, 9(4), 100630. https://doi.org/10.1016/J.JIK.2024.100630 [Google Scholar] [Crossref]

3. Alanazi, S., & Asif, S. (2024). Exploring deepfake technology: creation, consequences and countermeasures. Human-Intelligent Systems Integration 2024 6:1, 6(1), 49–60. https://doi.org/10.1007/S42454-024-00054-8 [Google Scholar] [Crossref]

4. Amazon Web Services. (2024). Ferrari Advances Generative AI for Customer Personalization and Production Efficiency. https://aws.amazon.com/solutions/case-studies/ferrari-generative-ai-case-study/ [Google Scholar] [Crossref]

5. Anthropic. (2025). Claude. https://claude.ai/login?returnTo=%2F%3F [Google Scholar] [Crossref]

6. Athaluri, S. A., Manthena, S. V., Kesapragada, V. S. R. K. M., Yarlagadda, V., Dave, T., & Duddumpudi, R. T. S. (2023). Exploring the Boundaries of Reality: Investigating the Phenomenon of Artificial Intelligence Hallucination in Scientific Writing Through ChatGPT References. Cureus, 15(4). https://doi.org/10.7759/CUREUS.37432 [Google Scholar] [Crossref]

7. Atkins, A. S., Sharp, B., & Atkins, L. (2013). Evaluating UK Intra-National Outsourcing to North Staffordshire. In Cultural and Technological Influences on Global Business (pp. 384–396). IGI Global. http://dx.doi.org/10.4018/978-1-4666-3966-9.ch020 [Google Scholar] [Crossref]

8. Atkins, A. S., Sharp, B., & Atkins, L. (2010). Decision Support System for Strategic Outsourcing Risk Reduction. 4th International Conference on Software, Knowledge and Information Management and Applications, 155–170. http://moss.camt.cmu.ac.th/research_affair/DocLib/Proceeeding of SKIMA 2010.pdf [Google Scholar] [Crossref]

9. Barravecchia, F., Mastrogiacomo, L., & Franceschini, F. (2023). A general cost model to assess the implementation of collaborative robots in assembly processes. International Journal of Advanced Manufacturing Technology, 125(11–12), 5247–5266. https://doi.org/10.1007/S00170-023-10942-Z/FIGURES/12 [Google Scholar] [Crossref]

10. Bertomeu, J., Lin, Y., Liu, Y., & Ni, Z. (2025). The impact of generative AI on information processing: Evidence from the ban of ChatGPT in Italy. Journal of Accounting and Economics, 101782. https://doi.org/10.1016/J.JACCECO.2025.101782 [Google Scholar] [Crossref]

11. Booth, R. (2025). ‘Mainlined into UK’s veins’: Labour announces huge public rollout of AI. The Guardian. https://www.theguardian.com/politics/2025/jan/12/mainlined-into-uks-veins-labour-announces-huge-public-rollout-of-ai [Google Scholar] [Crossref]

12. Braun, V., & Clarke, V. (2006). Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 3, 77–101. https://doi.org/10.1191/1478088706qp063oa [Google Scholar] [Crossref]

13. Burleigh, E. (2025, May 2). U.S. Secretary of Commerce Howard Lutnick says the ‘new model’ is factory jobs for life—for you, your kids, and your grandkids. Fortune. https://fortune.com/article/secretary-of-commerce-howard-lutnick-trump-tariffs-factory-jobs-gen-z-trade-work/?itm_source=parsely-api [Google Scholar] [Crossref]

14. CapCut. (2025). All-in-one video editor & graphic design tool driven by AI. https://www.capcut.com/ [Google Scholar] [Crossref]

15. Cassidy, C. (2024, July 30). ‘Nobody is blind to it’: mass cheating through AI puts integrity of Australian universities at risk, academics claim. The Guardian. https://www.theguardian.com/australia-news/article/2024/jul/31/universities-australia-cheating-issues-ai-chatgpt [Google Scholar] [Crossref]

16. Chen, S. (2025, April 10). Data centres will use twice as much energy by 2030 — driven by AI. Nature. https://doi.org/10.1038/D41586-025-01113-Z [Google Scholar] [Crossref]

17. CompaniesMarketCap.com. (2025). Companies ranked by Market Cap. https://companiesmarketcap.com/gbp/ [Google Scholar] [Crossref]

18. Consultancy.uk. (2024). Generative AI could see three-in-ten back office jobs cut. https://www.consultancy.uk/news/38445/generative-ai-could-see-three-in-ten-back-office-jobs-cut [Google Scholar] [Crossref]

19. Cross, M. (2025, February 18). In depth: AI regulation falters as UK snubs international accord. The Law Society Gazette. https://www.lawgazette.co.uk/news-focus/in-depth-ai-regulation-falters-as-uk-snubs-international-accord/5122381.article [Google Scholar] [Crossref]

20. Currie, G. M., Hawk, K. E., & Rohren, E. M. (2024). Generative Artificial Intelligence Biases, Limitations and Risks in Nuclear Medicine: An Argument for Appropriate Use Framework and Recommendations. Seminars in Nuclear Medicine. https://doi.org/10.1053/J.SEMNUCLMED.2024.05.005 [Google Scholar] [Crossref]

21. Cuthbertson, A. (2025). DeepSeek users could face million-dollar fine and prison time under new law. The Independent. https://www.independent.co.uk/tech/deepseek-ai-us-ban-prison-b2692396.html [Google Scholar] [Crossref]

22. Daco, G. (2024, April 15). How GenAI will impact the labor market. EY. https://www.ey.com/en_gl/insights/ai/how-gen-ai-will-impact-the-labor-market [Google Scholar] [Crossref]

23. DeepSeek. (2025). DeepSeek. https://www.deepseek.com/ [Google Scholar] [Crossref]

24. Department for Science, I. & T. (2024). Public attitudes to data and AI: Tracker survey (Wave 4) report - GOV.UK. https://www.gov.uk/government/publications/public-attitudes-to-data-and-ai-tracker-survey-wave-4/public-attitudes-to-data-and-ai-tracker-survey-wave-4-report#familiarity-with-ai-and-views-of-its-impact [Google Scholar] [Crossref]

25. Eder, A., Koller, W., & Mahlberg, B. (2024). The contribution of industrial robots to labor productivity growth and economic convergence: a production frontier approach. Journal of Productivity Analysis, 61(2), 157–181. https://doi.org/10.1007/S11123-023-00707-X/FIGURES/4 [Google Scholar] [Crossref]

26. ElevenLabs. (2025). Free Text to Speech & AI Voice Generator. https://elevenlabs.io [Google Scholar] [Crossref]

27. European Commission. (2025). What personal data and information can an individual access on request? https://commission.europa.eu/law/law-topic/data-protection/rules-business-and-organisations/dealing-citizens/what-personal-data-and-information-can-individual-access-request_en [Google Scholar] [Crossref]

28. European Parliament. (2025). EU AI Act: first regulation on artificial intelligence. https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence [Google Scholar] [Crossref]

29. Falconer, S. (2023, October 23). Privacy in the age of generative AI. Stack Overflow. https://stackoverflow.blog/2023/10/23/privacy-in-the-age-of-generative-ai/ [Google Scholar] [Crossref]

30. Farquhar, S., Kossen, J., Kuhn, L., & Gal, Y. (2024). Detecting hallucinations in large language models using semantic entropy. Nature 2024 630:8017, 630(8017), 625–630. https://doi.org/10.1038/s41586-024-07421-0 [Google Scholar] [Crossref]

31. Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024). Generative AI. Business and Information Systems Engineering, 66(1), 111–126. https://doi.org/10.1007/S12599-023-00834-7/TABLES/2 [Google Scholar] [Crossref]

32. Fraser, G. (2025, May 23). Indian IT giant investigates M&S cyber-attack link. BBC News. https://www.bbc.co.uk/news/articles/c989le2p3lno [Google Scholar] [Crossref]

33. Future of Life Institute. (2025). Article 99: Penalties. https://artificialintelligenceact.eu/article/99/ [Google Scholar] [Crossref]

34. Gamma Tech, I. (2025). Presentations and Slide Decks with AI. https://gamma.app/ [Google Scholar] [Crossref]

35. Gartner. (2025). Gartner Predicts 40% of AI Data Breaches Will Arise from Cross-Border GenAI Misuse by 2027. https://www.gartner.com/en/newsroom/press-releases/2025-02-17-gartner-predicts-forty-percent-of-ai-data-breaches-will-arise-from-cross-border-genai-misuse-by-2027 [Google Scholar] [Crossref]

36. GDPR.eu. (2025). What is GDPR, the EU’s new data protection law? . https://gdpr.eu/what-is-gdpr/ [Google Scholar] [Crossref]

37. Golda, A., Mekonen, K., Pandey, A., Singh, A., Hassija, V., Chamola, V., & Sikdar, B. (2024). Privacy and Security Concerns in Generative AI: A Comprehensive Survey. IEEE Access, 12, 48126–48144. https://doi.org/10.1109/ACCESS.2024.3381611 [Google Scholar] [Crossref]

38. Göllner, S., Tropmann-Frick, M., & Brumen, B. (2024). Towards a Definition of a Responsible Artificial Intelligence (p. 16). https://doi.org/10.3233/faia231146 [Google Scholar] [Crossref]

39. Google. (2025a). Gemini. https://gemini.google.com/app [Google Scholar] [Crossref]

40. Google. (2025b). Gemini Travel Planner. https://ai.google.dev/competition/projects/gemini-travel-planner [Google Scholar] [Crossref]

41. Google Threat Intelligence Group. (2025). Adversarial Misuse of Generative AI. https://cloud.google.com/blog/topics/threat-intelligence/adversarial-misuse-generative-ai [Google Scholar] [Crossref]

42. GOV.UK. (2025). How copyright protects your work: Overview. https://www.gov.uk/copyright [Google Scholar] [Crossref]

43. Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. In Education Sciences (Vol. 13, Issue 7, p. 692). Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/educsci13070692 [Google Scholar] [Crossref]

44. Gucluturk, O. (2024, February 22). How to handle GDPR data access requests in AI-driven personal data processing. OECD.AI. https://oecd.ai/en/wonk/gdpr-data-access-requests [Google Scholar] [Crossref]

45. Gupta, V., & Yang, H. (2024). Generative Artificial Intelligence (AI) Technology Adoption Model for Entrepreneurs: Case of ChatGPT. Internet Reference Services Quarterly, 28(2), 223–242. https://doi.org/10.1080/10875301.2023.2300114;REQUESTEDJOURNAL:JOURNAL:WIRS20;WGROUP:STRING:PUBLICATION [Google Scholar] [Crossref]

46. Hamid, J. (2025). Wall Street could be heading for an AI winter in 2025 – Here is why. https://www.msn.com/en-us/money/markets/wall-street-could-be-heading-for-an-ai-winter-in-2025-here-is-why/ar-AA1welzP?ocid=finance-verthp-feeds [Google Scholar] [Crossref]

47. Hamill, J. (2024). “We’ll move slowly”: Wells Fargo shares cautious GenAI plans. The Stack. https://www.thestack.technology/wells-fargo-generative-ai/ [Google Scholar] [Crossref]

48. Hemphill, T. A. (2025). Advanced artificial intelligence at a corporate responsibility crossroads: employees as risk management advocates. Journal of Ethics in Entrepreneurship and Technology, 5(1), 40–46. https://doi.org/10.1108/JEET-01-2025-0003 [Google Scholar] [Crossref]

49. Hiebl, M. R. W. (2023). Sample Selection in Systematic Literature Reviews of Management Research. Organizational Research Methods, 26(2), 229–261. https://doi.org/10.1177/1094428120986851/ASSET/FE5905F8-5345-4E33-A8D4-8A6ADAD7027F/ASSETS/IMAGES/LARGE/10.1177_1094428120986851-FIG1.JPG [Google Scholar] [Crossref]

50. History of Data Science. (2021). AI Winter: The Highs and Lows of Artificial Intelligence. https://www.historyofdatascience.com/ai-winter-the-highs-and-lows-of-artificial-intelligence/ [Google Scholar] [Crossref]

51. Hoskins, P., & Rahman-Jones, I. (2025). Nvidia shares sink as Chinese AI app DeepSeek spooks US markets - BBC News. BBC News. https://www.bbc.co.uk/news/articles/c0qw7z2v1pgo [Google Scholar] [Crossref]

52. IBM. (2023). AI Bias Examples. https://www.ibm.com/think/topics/shedding-light-on-ai-bias-with-real-world-examples [Google Scholar] [Crossref]

53. Ingham, L., & Baker, J. (2024). Are Klarna’s AI-led job cuts a model for the payments industry? FXCintelligence. https://www.fxcintel.com/research/reports/ct-klarna-ai-job-cuts [Google Scholar] [Crossref]

54. Institute of Analytics. (2024). Are We Entering a New AI Winter? https://ioaglobal.org/blog/entering-new-ai-winter/ [Google Scholar] [Crossref]

55. International Association of Privacy Professionals. (2025). Data protection and privacy laws now in effect in 144 countries. https://iapp.org/news/a/data-protection-and-privacy-laws-now-in-effect-in-144-countries [Google Scholar] [Crossref]

56. Intersoft Consulting. (2025a). Art. 16 GDPR – Right to rectification - General Data Protection Regulation (GDPR). https://gdpr-info.eu/art-16-gdpr/ [Google Scholar] [Crossref]

57. Intersoft Consulting. (2025b). Art. 17 GDPR – Right to erasure (‘right to be forgotten’) - General Data Protection Regulation (GDPR). https://gdpr-info.eu/art-17-gdpr/ [Google Scholar] [Crossref]

58. Jackson, F. (2024, September 26). Deloitte: 50% More Professionals Rank Data Privacy as a Top GenAI Concern in 2024. TechRepublic. https://www.techrepublic.com/article/genai-data-privacy-concern-deloitte/ [Google Scholar] [Crossref]

59. Javaid, M., Haleem, A., Singh, R. P., Suman, R., & Santibañez Gonzalez, E. (2022). Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. Sustainable Operations and Computers, 3, 203–217. https://doi.org/10.1016/j.susoc.2022.01.008 [Google Scholar] [Crossref]

60. Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard--measures that drive performance. Harvard Business Review, 70(1), 71–79. [Google Scholar] [Crossref]

61. Khosrowi, D., Finn, F., & Clark, E. (2024). Engaging the many-hands problem of generative-AI outputs: a framework for attributing credit. AI and Ethics 2024, 1–19. https://doi.org/10.1007/S43681-024-00440-7 [Google Scholar] [Crossref]

62. Klingbeil, A., Grützner, C., & Schreck, P. (2024). Trust and reliance on AI — An experimental study on the extent and costs of overreliance on AI. Computers in Human Behavior, 160, 108352. https://doi.org/10.1016/J.CHB.2024.108352 [Google Scholar] [Crossref]

63. Kshetri, N. (2024). Generative AI in Advertising. IT Professional, 26(5), 15–19. https://doi.org/10.1109/MITP.2024.3457328 [Google Scholar] [Crossref]

64. Kufel, J., Bargieł-Łączek, K., Kocot, S., Koźlik, M., Bartnikowska, W., Janik, M., Czogalik, Ł., Dudek, P., Magiera, M., Lis, A., Paszkiewicz, I., Nawrat, Z., Cebula, M., & Gruszczyńska, K. (2023). What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine. Diagnostics 2023, Vol. 13, Page 2582, 13(15), 2582. https://doi.org/10.3390/DIAGNOSTICS13152582 [Google Scholar] [Crossref]

65. Kumar, L. (2025). DeepSeek’s AI raises censorship concerns: Avoids speaking on many China related topics. Business Today. https://www.businesstoday.in/technology/news/story/deepseeks-ai-raises-censorship-concerns-avoids-speaking-on-many-china-related-topics-462531-2025-01-30 [Google Scholar] [Crossref]

66. Landi, M. (2025, February 7). ChatGPT maker OpenAI taking claims of data breach ‘seriously.’ The Independent. https://www.independent.co.uk/tech/openai-data-breach-chatpt-email-b2694280.html [Google Scholar] [Crossref]

67. Lee, D. (2024, December 20). AI in 2025: Wall Streets Need to Prepare for a Slowdown. Bloomberg UK. https://www.bloomberg.com/opinion/articles/2024-12-20/ai-in-2025-wall-streets-need-to-prepare-for-a-slowdown [Google Scholar] [Crossref]

68. Leonardo AI. (2025). AI Image Generator - Create Art, Images & Video. https://leonardo.ai/ [Google Scholar] [Crossref]

69. Licardo, J. T., Domjan, M., & Orehovački, T. (2024). Intelligent Robotics—A Systematic Review of Emerging Technologies and Trends. Electronics 2024, Vol. 13, Page 542, 13(3), 542. https://doi.org/10.3390/ELECTRONICS13030542 [Google Scholar] [Crossref]

70. Looka. (2025). Free AI Logo Generator - Create Professional Logos Instantly. https://looka.com/ai-logo-generator/ [Google Scholar] [Crossref]

71. Malandruccolo, M. (2024). Harnessing the Power of Machine Learning and AI to Decrease Health Expenditures Worldwide-A Review. Premier Journal of Science, 1(100004), 1–6. https://doi.org/10.70389/PJS.100004 [Google Scholar] [Crossref]

72. McKinsey. (2023). Generative AI’s impact on jobs and workflows. https://www.mckinsey.com/mgi/our-research/generative-ai-how-will-it-affect-future-jobs-and-workflows [Google Scholar] [Crossref]

73. Meta. (2025). Meta AI. https://www.meta.ai/ [Google Scholar] [Crossref]

74. Microsoft. (2025a). Data, Privacy, and Security for Microsoft 365 Copilot. https://learn.microsoft.com/en-us/copilot/microsoft-365/microsoft-365-copilot-privacy [Google Scholar] [Crossref]

75. Microsoft. (2025b). Microsoft Copilot: Your AI companion. https://copilot.microsoft.com/ [Google Scholar] [Crossref]

76. Midjourney. (2025). Midjourney. https://www.midjourney.com/home [Google Scholar] [Crossref]

77. Milmo, D. (2024). Company worker in Hong Kong pays out £20m in deepfake video call scam. The Guardian. https://www.theguardian.com/world/2024/feb/05/hong-kong-company-deepfake-video-conference-call-scam [Google Scholar] [Crossref]

78. MIT Technology Review. (2023, July 18). The great acceleration: CIO perspectives on generative AI. https://www.technologyreview.com/2023/07/18/1076423/the-great-acceleration-cio-perspectives-on-generative-ai/ [Google Scholar] [Crossref]

79. Mucci, T. (2025). The History of Artificial Intelligence. IBM. https://www.ibm.com/think/topics/history-of-artificial-intelligence [Google Scholar] [Crossref]

80. Mudaliar, A. (2024, February 1). ChatGPT Leaks Sensitive Data - Spiceworks. https://www.spiceworks.com/tech/artificial-intelligence/news/chatgpt-leaks-sensitive-user-data-openai-suspects-hack/ [Google Scholar] [Crossref]

81. Mugu, S. R., Zhang, B., Kolla, H., Balaji, S. R. A., & Ranganathan, P. (2024). Lessons from the CrowdStrike Incident: Assessing Endpoint Security Vulnerabilities and Implications. 2024 Cyber Awareness and Research Symposium, CARS 2024. https://doi.org/10.1109/CARS61786.2024.10778784 [Google Scholar] [Crossref]

82. Noble, S. M., Mende, M., Grewal, D., & Parasuraman, A. (2022). The Fifth Industrial Revolution: How Harmonious Human–Machine Collaboration is Triggering a Retail and Service [R]evolution. Journal of Retailing, 98(2), 199–208. https://doi.org/10.1016/J.JRETAI.2022.04.003 [Google Scholar] [Crossref]

83. Notta. (2025). Speech to Text Online Converter. https://www.notta.ai [Google Scholar] [Crossref]

84. NVIDIA. (2025, April 14). NVIDIA to Manufacture American-Made AI Supercomputers in US for First Time. https://blogs.nvidia.com/blog/nvidia-manufacture-american-made-ai-supercomputers-us/ [Google Scholar] [Crossref]

85. Open Worldwide Application Security Project. (2023). LLMRisks 2023-24 Archive - OWASP Top 10 for LLM & Generative AI Security. https://genai.owasp.org/llm-top-10-2023-24/ [Google Scholar] [Crossref]

86. Open Worldwide Application Security Project. (2025). LLM Risks Archive - OWASP Top 10 for LLM & Generative AI Security. https://genai.owasp.org/llm-top-10/ [Google Scholar] [Crossref]

87. OpenAI. (2025). ChatGPT. https://openai.com/chatgpt/overview/ [Google Scholar] [Crossref]

88. OpenArt. (2025). Create Art or Modify Images with AI. https://openart.ai [Google Scholar] [Crossref]

89. OpusClip. (2025). AI Video Editor. https://www.opus.pro/ai-video-editor [Google Scholar] [Crossref]

90. Otter.ai. (2025). AI Meeting Note Taker & Real-time AI Transcription. https://otter.ai/ [Google Scholar] [Crossref]

91. Pearlson, K., & Saunders, C. S. (2009). Strategic management of information systems. Wiley. [Google Scholar] [Crossref]

92. Perrigo, B. (2023, January 18). OpenAI Used Kenyan Workers on Less Than $2 Per Hour. Time. https://time.com/6247678/openai-chatgpt-kenya-workers/ [Google Scholar] [Crossref]

93. Presentations.AI. (2025). Presentations.AI - ChatGPT for Presentations. https://www.presentations.ai/?r=0 [Google Scholar] [Crossref]

94. PwC. (2025). PwC’s Global Artificial Intelligence Study. https://www.pwc.com/gx/en/issues/artificial-intelligence/publications/artificial-intelligence-study.html [Google Scholar] [Crossref]

95. Rahman-Jones, I. (2025). AI chatbots unable to accurately summarise news, BBC finds - BBC News. BBC News. https://www.bbc.co.uk/news/articles/c0m17d8827ko [Google Scholar] [Crossref]

96. Raiaan, M. A. K., Mukta, M. S. H., Fatema, K., Fahad, N. M., Sakib, S., Mim, M. M. J., Ahmad, J., Ali, M. E., & Azam, S. (2024). A Review on Large Language Models: Architectures, Applications, Taxonomies, Open Issues and Challenges. IEEE Access, 12, 26839–26874. https://doi.org/10.1109/ACCESS.2024.3365742 [Google Scholar] [Crossref]

97. Raman, A. (2023). Keeping Up With International Data Privacy Regulations. Forbes. https://www.forbes.com/councils/forbestechcouncil/2023/07/05/keeping-up-with-international-data-privacy-regulations/ [Google Scholar] [Crossref]

98. Recraft. (2025). Free AI Logo Generator: Create unique logo with texts. https://www.recraft.ai/generate/logos [Google Scholar] [Crossref]

99. Reis, O., Eneh, N. E., Ehimuan, B., Anyanwu, A., Olorunsogo, T., & Abrahams, T. O. (2024). PRIVACY LAW CHALLENGES IN THE DIGITAL AGE: A GLOBAL REVIEW OF LEGISLATION AND ENFORCEMENT. International Journal of Applied Research in Social Sciences, 6(1), 73–88. https://doi.org/10.51594/IJARSS.V6I1.733 [Google Scholar] [Crossref]

100. Resemble AI. (2025). AI Voice Generator with Text to Speech and Speech to Speech. https://www.resemble.ai [Google Scholar] [Crossref]

101. Royal Institute of British Architects. (2024). ‘No turning back’: 41% of architects now using AI. https://www.architecture.com/knowledge-and-resources/knowledge-landing-page/no-turning-back-41-of-architects-now-using-ai?srsltid=AfmBOopwSyDL6a5LKhXzUX1Mg2oN30hXltV9Fy8DUytY9HoCY6B3wLIp [Google Scholar] [Crossref]

102. Sai, S., Sai, R., & Chamola, V. (2024). Generative AI for Industry 5.0: Analyzing the impact of ChatGPT, DALLE, and Other Models. IEEE Open Journal of the Communications Society. https://doi.org/10.1109/OJCOMS.2024.3400161 [Google Scholar] [Crossref]

103. Sajid, H. (2025). Generative AI in Manufacturing: Real-World Applications . Encord. https://encord.com/blog/generative-ai-in-manufacturing/ [Google Scholar] [Crossref]

104. Sarker, I. H. (2021). Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions. In SN Computer Science (Vol. 2, Issue 6, pp. 1–20). Springer. https://doi.org/10.1007/s42979-021-00815-1 [Google Scholar] [Crossref]

105. Schneider, J. (2024). Explainable Generative AI (GenXAI): a survey, conceptualization, and research agenda. Artificial Intelligence Review 2024 57:11, 57(11), 1–38. https://doi.org/10.1007/S10462-024-10916-X [Google Scholar] [Crossref]

106. Sengar, S. S., Hasan, A. Bin, Kumar, S., & Carroll, F. (2024). Generative artificial intelligence: a systematic review and applications. Multimedia Tools and Applications, 1–40. https://doi.org/10.1007/S11042-024-20016-1/TABLES/9 [Google Scholar] [Crossref]

107. Shailendra, S., Kadel, R., & Sharma, A. (2024). Framework for Adoption of Generative Artificial Intelligence (GenAI) in Education. IEEE Transactions on Education, 1–9. https://doi.org/10.1109/TE.2024.3432101 [Google Scholar] [Crossref]

108. Shen, Y., Heacock, L., Elias, J., Hentel, K. D., Reig, B., Shih, G., & Moy, L. (2023). ChatGPT and Other Large Language Models Are Double-edged Swords. Radiology, 307(2), 2023. https://doi.org/10.1148/RADIOL.230163 [Google Scholar] [Crossref]

109. Sivathasan, N., & Beal, T. (2025, April 25). Why the Post Office paid £600m to stay shackled to the faulty Horizon system. BBC News. https://www.bbc.co.uk/news/articles/cgm8lmz1xk1o [Google Scholar] [Crossref]

110. Sparato, J. (2023). Introducing Microsoft 365 Copilot – your copilot for work. Microsoft. https://blogs.microsoft.com/blog/2023/03/16/introducing-microsoft-365-copilot-your-copilot-for-work/ [Google Scholar] [Crossref]

111. Statcounter. (2025a). Desktop Operating System Market Share Worldwide. https://gs.statcounter.com/os-market-share/desktop/worldwide [Google Scholar] [Crossref]

112. Statcounter. (2025b). Search Engine Market Share Worldwide. https://gs.statcounter.com/search-engine-market-share [Google Scholar] [Crossref]

113. Statista. (2024a). Global AI market size 2030. https://www.statista.com/forecasts/1474143/global-ai-market-size [Google Scholar] [Crossref]

114. Statista. (2024b). Worldwide AI tool users 2030. https://www.statista.com/forecasts/1449844/ai-tool-users-worldwide [Google Scholar] [Crossref]

115. Stone, M. (2024). 2025 Microsoft Copilot Security Concerns Explained. https://concentric.ai/too-much-access-microsoft-copilot-data-risks-explained/ [Google Scholar] [Crossref]

116. Stryker, C., & Kavlakoglu, E. (2024). What Is Artificial Intelligence (AI)? IBM. https://www.ibm.com/think/topics/artificial-intelligence [Google Scholar] [Crossref]

117. Sun, Y., Sheng, D., Zhou, Z., & Wu, Y. (2024). AI hallucination: towards a comprehensive classification of distorted information in artificial intelligence-generated content. Humanities and Social Sciences Communications 2024 11:1, 11(1), 1–14. https://doi.org/10.1057/s41599-024-03811-x [Google Scholar] [Crossref]

118. Suno. (2025). Suno. https://suno.com/home [Google Scholar] [Crossref]

119. Supermind. (2025). Mapify: AI Mind Map Summarizer. https://mapify.so/?ref=futuretools.io [Google Scholar] [Crossref]

120. Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). The processes of technological innovation. Issues in organization and management series. Lexington Books. https://doi.org/10.1016/j.cca.2013.05.002 [Google Scholar] [Crossref]

121. Trendall, S. (2024a). DWP bans officials from using ChatGPT. Civil Service World. https://www.civilserviceworld.com/professions/article/dwp-bans-officials-from-using-chatgpt [Google Scholar] [Crossref]

122. Trendall, S. (2024b). DWP seeks suppliers to help tap into ‘unprecedented opportunity and challenge’ of generative AI – PublicTechnology. Public Technology. https://www.publictechnology.net/2024/07/24/science-technology-and-research/dwp-seeks-suppliers-to-help-tap-into-unprecedented-opportunity-and-challenge-of-generative-ai [Google Scholar] [Crossref]

123. Trip Planner AI. (2025). Trip Planner AI: Free & Customizable Travel Itinerary App. https://tripplanner.ai/ [Google Scholar] [Crossref]

124. Urrea, C., & Kern, J. (2025). Recent Advances and Challenges in Industrial Robotics: A Systematic Review of Technological Trends and Emerging Applications. Processes 2025, Vol. 13, Page 832, 13(3), 832. https://doi.org/10.3390/PR13030832 [Google Scholar] [Crossref]

125. Uymaz, A. (2021). Is Artificial Intelligence our mirror or Themis’s? Artifıcial intelligence and Gender Discrimination. In Business Studies and New Approaches (pp. 43–58). Livre de Lyon. [Google Scholar] [Crossref]

126. Vecchietti, G., Liyanaarachchi, G., & Viglia, G. (2025). Managing deepfakes with artificial intelligence: Introducing the business privacy calculus. Journal of Business Research, 186, 115010. https://doi.org/10.1016/J.JBUSRES.2024.115010 [Google Scholar] [Crossref]

127. Walmart. (2024a). Walmart’s Generative AI search puts more time back in customers’ hands. https://tech.walmart.com/content/walmart-global-tech/en_us/blog/post/walmarts-generative-ai-search-puts-more-time-back-in-customers-hands.html [Google Scholar] [Crossref]

128. Walmart. (2024b). Walmart Reveals Plan for Scaling Artificial Intelligence, Generative AI, Augmented Reality and Immersive Commerce Experiences. https://corporate.walmart.com/news/2024/10/09/walmart-reveals-plan-for-scaling-artificial-intelligence-generative-ai-augmented-reality-and-immersive-commerce-experiences [Google Scholar] [Crossref]

129. Weiser, B. (2023, May 28). US lawyer in legal trouble after citing cases “invented” by ChatGPT. Business Standard. https://www.business-standard.com/world-news/us-lawyer-in-legal-trouble-after-citing-cases-invented-by-chatgpt-123052800935_1.html [Google Scholar] [Crossref]

130. Wheeler, K. (2024, October 2). Amazon Embraces AI and Robotics to Enhance Worker Experience. Technology Magazine. https://technologymagazine.com/ai-and-machine-learning/amazon-embraces-ai-and-robotics-to-enhance-worker-experience [Google Scholar] [Crossref]

131. Whimsical. (2025). AI Mind Map. https://whimsical.com/ai/ai-mind-maps [Google Scholar] [Crossref]

132. Willetts, M., & Atkins, A. (2023a). Software Positioning Tool to Support SMEs in Adoption of Big Data Analytics using a Case Study Application. International Journal of Software Engineering and Computer Systems, 9(1), 46–58. https://doi.org/10.15282/IJSECS.9.1.2023.5.0109 [Google Scholar] [Crossref]

133. Willetts, M., & Atkins, A. S. (2023b). Qualitative Study on Barriers of Adopting Big Data Analytics for UK SMEs. International Journal of Big Data Management, 3(1). https://doi.org/10.1504/IJBDM.2024.10052988 [Google Scholar] [Crossref]

134. Willetts, M., & Atkins, A. S. (2023c). Performance measurement to evaluate the implementation of big data analytics to SMEs using benchmarking and the balanced scorecard approach. Journal of Data, Information and Management 2023, 1–15. https://doi.org/10.1007/S42488-023-00088-8 [Google Scholar] [Crossref]

135. Willetts, M., & Atkins, A. S. (2024). Evaluation of a software positioning tool to support SMEs in adoption of big data analytics. Journal of Electronic Science and Technology, 22(1), 100229. https://doi.org/10.1016/J.JNLEST.2023.100229 [Google Scholar] [Crossref]

136. Willetts, M., Atkins, A. S., & Stanier, C. (2020). A Strategic Big Data Analytics Framework To Provide Opportunities for SMEs. INTED2020 Proceedings, 1, 3033–3042. https://doi.org/10.21125/inted.2020.0893 [Google Scholar] [Crossref]

137. Willetts, M., Atkins, A. S., & Stanier, C. (2022a). A Teaching and Learning Case Study on Data Mining Using Association Rules for SMEs. 16th International Technology, Education and Development Conference, 1401–1410. https://doi.org/10.21125/inted.2022.0417 [Google Scholar] [Crossref]

138. Willetts, M., Atkins, A. S., & Stanier, C. (2022b). Quantitative Study on Barriers of Adopting Big Data Analytics for UK and Eire SMEs. In N. Sharma, A. Chakrabarti, V. E. Balas, & A. M. Bruckstein (Eds.), Data Management, Analytics and Innovation (pp. 349–373). Springer Singapore. https://doi.org/https://doi.org/10.1007/978-981-16-2937-2_23 [Google Scholar] [Crossref]

139. Willetts, M., Atkins, A. S., & Stanier, C. (2021). Teaching and Learning Case Study on Social Media Analytics for Small And Medium-Sized Enterprises. ICERI2021 Proceedings, 3158–3167. https://doi.org/10.21125/iceri.2021.0785 [Google Scholar] [Crossref]

140. World Economic Forum. (2024). AI and energy: Will AI reduce emissions or increase demand? https://www.weforum.org/stories/2024/07/generative-ai-energy-emissions/ [Google Scholar] [Crossref]

141. World Economic Forum. (2025). Future of Jobs Report 2025. www.weforum.org [Google Scholar] [Crossref]

142. Wu, X., Duan, R., & Ni, J. (2024). Unveiling security, privacy, and ethical concerns of ChatGPT. Journal of Information and Intelligence, 2(2), 102–115. https://doi.org/10.1016/J.JIIXD.2023.10.007 [Google Scholar] [Crossref]

143. Xin, Y., Kong, L., Liu, Z., Chen, Y., Li, Y., Zhu, H., Gao, M., Hou, H., & Wang, C. (2018). Machine Learning and Deep Learning Methods for Cybersecurity. IEEE Access, 6, 35365–35381. https://doi.org/10.1109/ACCESS.2018.2836950 [Google Scholar] [Crossref]

144. Ye, X., Yan, Y., Li, J., & Jiang, B. (2024). Privacy and personal data risk governance for generative artificial intelligence: A Chinese perspective. Telecommunications Policy, 48(10), 102851. https://doi.org/10.1016/J.TELPOL.2024.102851 [Google Scholar] [Crossref]

145. Yusof, M. M., Kuljis, J., Papazafeiropoulou, A., & Stergioulas, L. K. (2008). An evaluation framework for Health Information Systems: human, organization and technology-fit factors (HOT-fit). International Journal of Medical Informatics, 77(6), 386–398. https://doi.org/10.1016/J.IJMEDINF.2007.08.011 [Google Scholar] [Crossref]

146. Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments 2024 11:1, 11(1), 1–37. https://doi.org/10.1186/S40561-024-00316-7 [Google Scholar] [Crossref]

• What the Desert Fathers Teach Data Scientists: Ancient Ascetic Principles for Ethical Machine-Learning Practice
• Comparative Analysis of Some Machine Learning Algorithms for the Classification of Ransomware
• Comparative Performance Analysis of Some Priority Queue Variants in Dijkstra’s Algorithm
• Transfer Learning in Detecting E-Assessment Malpractice from a Proctored Video Recordings.
• Dual-Modal Detection of Parkinson’s Disease: A Clinical Framework and Deep Learning Approach Using NeuroParkNet