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Personal AI Operating Systems: Architectural Foundations, Ethical Assurance, and Commercial Potential in AI-Native Computing


Authors : Pushpesh Srivastava; Akshat Sharma; Dr. Gaurvi Shukla

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/8ehkz5t4

DOI : https://doi.org/10.38124/ijisrt/26apr1291

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Abstract : We are facing a problem with modern computers, which is that the software is getting too complicated. The old ways of managing computer systems are not working well for big and complex systems. This paper is about an idea called Personal AI Operating Systems, which is a big change in how we think about computer systems. It uses something called Large Language Model agents to make the system smarter and able to manage itself. We used an approach to study this new idea, which is called Design Science Research. We compared the ways of doing things with the new ways and we also did a detailed study of how Large Language Models can help with managing computer resources and keeping them secure. What we found out is that Personal AI Operating Systems are really good at planning and understanding what people want to do. They are better than the systems, which can only react to problems. We also looked at the trade-offs between making the system fast and reliable and using machine learning to make decisions. Our results show that Personal AI Operating Systems can make computer systems more resilient and easier to use. Finally we talked about how to make sure that Personal AI Operating Systems are used in a way especially when it comes to peoples personal data. We think that this is an important area and it is going to be worth a lot of money. $56.3 Billion, by 2034.

Keywords : Personal AI Operating System, AI-Native Computing, Large Language Models, Autonomic Computing, Design Science Research, System Kernel Architecture.

References :

  1. AUTONOMIC COMPUTING - Research Publish Journals, accessed September 30, 2025, https://www.researchpublish.com/upload/book/AUTONOMIC%20COMPUTING-5580.pdf
  2. Comparing the performance of the system with and without autonomic... - ResearchGate, accessed September 30, 2025, https://www.researchgate.net/figure/Comparing-the-performance-of-the-system-with-and-without-autonomic-computing_fig3_323140962
  3. The Rise of AI OS - Walturn, accessed September 30, 2025, https://www.walturn.com/insights/the-rise-of-ai-os
  4. fiatrete/OpenDAN-Personal-AI-OS: OpenDAN is an open ... - GitHub, accessed September 30, 2025, https://github.com/fiatrete/OpenDAN-Personal-AI-OS
  5. Autonomic computing - Wikipedia, accessed September 30, 2025, https://en.wikipedia.org/wiki/Autonomic_computing
  6. Embedded Systems Task Scheduling Algorithms and Deterministic Behavior - JUST, accessed September 30, 2025, https://www.just.edu.jo/~tawalbeh/cpe746/slides/Scheduling_Algorithms.pdf
  7. Towards a Machine Learning-Assisted Kernel with ... - Ariel Szekely, accessed September 30, 2025, https://arielszekely.github.io/papers/lake.pdf
  8. leveraging ai and ml for predictive scheduling in real-time operating systems, accessed September 30, 2025, https://www.researchgate.net/publication/387958272_LEVERAGING_AI_AND_ML_FOR_PREDICTIVE_SCHEDULING_IN_REAL-TIME_OPERATING_SYSTEMS
  9. accessed September 30, 2025, https://syekhnurjati.ac.id/journal/index.php/itej/article/download/127/88/#:~:text=The%20main%20challenges%20in%20integrating,system%20performance%20without%20compromising%20security.
  10. How to Create a Personal AI Assistant for Your Business in 2025 - Biz4Group, accessed September 30, 2025, https://www.biz4group.com/blog/how-to-create-a-personal-ai-assistant
  11. Accountability Frameworks for Autonomous AI Agents: Who's Responsible?, accessed September 30, 2025, https://www.arionresearch.com/blog/owisez8t7c80zpzv5ov95uc54d11kd
  12. Regulating Autonomous AI: Legal Perspectives on Accountability and Liability, accessed September 30, 2025, https://www.researchgate.net/publication/392700339_Regulating_Autonomous_AI_Legal_Perspectives_on_Accountability_and_Liability
  13. Formal Design and Verification of Self-Adaptive Systems with Decentralized Control | D3S, accessed September 30, 2025, https://d3s.mff.cuni.cz/publications/arcaini_formal_2017/
  14. Key Characteristics of Intelligent Agents: Autonomy, Adaptability, and Decision-Making, accessed September 30, 2025, https://smythos.com/developers/agent-development/intelligent-agent-characteristics/
  15. (PDF) Enhancing Operating System Performance with AI: Optimized Scheduling and Resource Management - ResearchGate, accessed September 30, 2025, https://www.researchgate.net/publication/391880725_Enhancing_Operating_System_Performance_with_AI_Optimized_Scheduling_and_Resource_Management
  16. The Ultimate Guide to Self-Healing Applications - System heal thyself - CioPages, accessed September 30, 2025, https://www.ciopages.com/self-healing-applications/
  17. Self-Healing AI Agents vs Traditional Fault-Tolerant Systems: A Comprehensive Comparison of Pros and Cons - SuperAGI, accessed September 30, 2025, https://superagi.com/self-healing-ai-agents-vs-traditional-fault-tolerant-systems-a-comprehensive-comparison-of-pros-and-cons/
  18. What Is AI Safety? - IBM, accessed September 30, 2025, https://www.ibm.com/think/topics/ai-safety
  19. Design Science Research Methodology | by Yassine Lazaar - Medium, accessed September 30, 2025, https://medium.com/@yassin.lazar/design-science-research-methodology-4577f732a1fa
  20. (PDF) A survey of formal methods in self-adaptive systems - ResearchGate, accessed September 30, 2025, https://www.researchgate.net/publication/254463840_A_survey_of_formal_methods_in_self-adaptive_systems
  21. Autonomous Systems Accountability → Term - Prism → Sustainability Directory, accessed September 30, 2025, https://prism.sustainability-directory.com/term/autonomous-systems-accountability/
  22. Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data - arXiv, accessed September 30, 2025, https://arxiv.org/html/2504.21634v1
  23. [2501.18174] Advancing Personalized Federated Learning: Integrative Approaches with AI for Enhanced Privacy and Customization - arXiv, accessed September 30, 2025, https://arxiv.org/abs/2501.18174
  24. AI Principles - Springer Nature Group, accessed September 30, 2025, https://www.springernature.com/gp/group/ai/ai-principles
  25. FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare - National Institutes of Health (NIH) |, accessed September 30, 2025, https://pmc.ncbi.nlm.nih.gov/articles/PMC11795397/
  26. Self-Healing Dilemmas in Distributed Systems: Fault Correction vs. Fault Tolerance - White Rose Research Online, accessed September 30, 2025, https://eprints.whiterose.ac.uk/id/eprint/179226/1/DIAS.pdf
  27. Self-Healing vs. Fault Tolerance, accessed September 30, 2025, https://www.cs.kent.ac.uk/events/conf/2003/wads/Slides/Panel/koopman.pdf
  28. Ethical AI Scheduling: Preventing Algorithmic Bias - myshyft.com, accessed September 30, 2025, https://www.myshyft.com/blog/algorithmic-bias-prevention/
  29. Privacy Attacks in Federated Learning | NIST, accessed September 30, 2025, https://www.nist.gov/blogs/cybersecurity-insights/privacy-attacks-federated-learning
  30. Explainability in AI: The Key to Trustworthy AI Decisions - The Conference Board, accessed September 30, 2025, https://www.conference-board.org/publications/explainability-in-ai
  31. Using Explainable AI in Decision-Making Applications - MobiDev, accessed September 30, 2025, https://mobidev.biz/blog/using-explainable-ai-in-decision-making-applications
  32. AI Personal Assistant Market Outlook 2025-2032 - Intel Market Research, accessed September 30, 2025, https://www.intelmarketresearch.com/ai-personal-assistant-market-7265
  33. 4 challenges of building cloud efficient operating system. - GrowthJockey, accessed September 30, 2025, https://www.growthjockey.com/blogs/challenges-building-cloud-efficient-operating-system
  34. Innovating in New Operating Domains Begins Not in the Pragmatic and Known, but the Fantastic and Weird, accessed September 30, 2025, https://ciasp.scholasticahq.com/article/115748-innovating-in-new-operating-domains-begins-not-in-the-pragmatic-and-known-but-the-fantastic-and-weird
  35. Challenges And Innovations In Operating System Development - FasterCapital, accessed September 30, 2025, https://fastercapital.com/topics/challenges-and-innovations-in-operating-system-development.html/1

We are facing a problem with modern computers, which is that the software is getting too complicated. The old ways of managing computer systems are not working well for big and complex systems. This paper is about an idea called Personal AI Operating Systems, which is a big change in how we think about computer systems. It uses something called Large Language Model agents to make the system smarter and able to manage itself. We used an approach to study this new idea, which is called Design Science Research. We compared the ways of doing things with the new ways and we also did a detailed study of how Large Language Models can help with managing computer resources and keeping them secure. What we found out is that Personal AI Operating Systems are really good at planning and understanding what people want to do. They are better than the systems, which can only react to problems. We also looked at the trade-offs between making the system fast and reliable and using machine learning to make decisions. Our results show that Personal AI Operating Systems can make computer systems more resilient and easier to use. Finally we talked about how to make sure that Personal AI Operating Systems are used in a way especially when it comes to peoples personal data. We think that this is an important area and it is going to be worth a lot of money. $56.3 Billion, by 2034.

Keywords : Personal AI Operating System, AI-Native Computing, Large Language Models, Autonomic Computing, Design Science Research, System Kernel Architecture.

Paper Submission Last Date
30 - April - 2026

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