A Framework for Integrating Robotic Process Automation with Artificial Intelligence Applied to Industry 5.0
Source abstract
Abstract
The transition to Industry 5.0 highlights the growing integration of Robotic Process Automation (RPA) and Artificial Intelligence (AI) in industrial ecosystems. However, adoption remains fragmented, lacking standardized frameworks to align intelligent automation with human-centric principles. While RPA improves operational efficiency and AI enhances cognitive decision-making, challenges such as organizational resistance, interoperability, and ethical governance hinder scalable and sustainable implementation. The envisioned scenario involves seamless RPA-AI integration, fostering human–machine collaboration, operational resilience, and sustainability. Expected outcomes include (1) hyperautomation for efficiency gains, (2) agile, data-driven decision-making, (3) sustainable resource optimization, and (4) an upskilled workforce focusing on innovation. This study proposes a structured five-stage framework for RPA-AI deployment in Industry 5.0, combining automation, cognitive enhancement, and human–machine symbiosis. A systematic literature review (PICO method) identifies gaps and supports the framework’s design, validated through operational, human-impact, and sustainability metrics. Incorporating ethical governance and continuous upskilling, the model ensures technological advancement aligns with societal and environmental values. Results demonstrate its potential as a roadmap for responsible digital transformation, balancing efficiency with human-centricity. Future research should focus on empirical validation and sector-specific adaptations.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotic Process Automation Applications · Digital Transformation in Industry · Blockchain Technology Applications and Security
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Production and Systems, Algoritmi/LASI, University of Minho, 4804-533 Guimarães, Portugal
Department of Mechanical Engineering, Sao Carlos School of Engineering, University of Sao Paulo, Sao Paulo 13566-590, Brazil
ISEP—Instituto Superior de Engenharia do Porto, Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal
INEGI—Institute of Science and Innovation in Mechanical and Industrial Engineering, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
MEtRICs Research Center, School of Engineering, University of Minho, Campus of Azurém, 4800-058 Guimarães, Portugal
Funding
ALGORITMI Centre
References (59)
Show source-provided references
1. Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges10.1016/j.jmsy.2024.02.010 ↗
2. AI-Enhanced Robotic Process Automation: A Review of Intelligent Automation Innovations10.1109/ACCESS.2024.3513279 ↗
3. Flechsig, C., Anslinger, F., and Lasch, R. (2021). Robotic Process Automation in purchasing and supply management: A multiple case study on potentials, barriers, and implementation. J. Purch. Supply Manag., 28.10.1016/j.pursup.2021.100718 ↗
4. Artificial intelligence: Friend or foe?10.1111/ajo.13661 ↗
5. Integrating Hyper-Automation with RPA and AI for End-to-End Business Process Optimization10.36676/dira.v12.i3.67 ↗
6. Ahmed, K.R., and Hassanien, A.E. (2021). Combinando Inteligência Artificial com Automação de Processos Robóticos—Uma Abordagem de Automação Inteligente. Aprendizado Profundo e Big Data para Transporte Inteligente, Springer. Estudos em Inteligência Computacional.
7. Robotic Process Automation10.1007/s12599-018-0542-4 ↗
8. Syed, R., Suriadi, S., Adams, M., Bandara, W., Leemans, S.J.J., Ouyang, C., ter Hofstede, A.H.M., van de Weerd, I., Wynn, M.T., and Reijers, H.A. (2020). Robotic Process Automation: Contemporary Themes and Challenges. Comput. Ind., 115.10.1016/j.compind.2019.103162 ↗
9. Process Mining and Robotic Process Automation: A Perfect Match
10. Robotic Process Automation and Artificial Intelligence in Industry 4.0—A Literature review10.1016/j.procs.2021.01.104 ↗
11. Influence of Artificial Intelligence (AI) on Firm Performance: The Business Value of AI-Based Transformation Projects10.1108/BPMJ-10-2019-0411 ↗
12. Mourtzis, D., Tsoubou, S., and Angelopoulos, J. (2023). Otimização da confiabilidade de células robóticas com base em gêmeos digitais e manutenção preditiva. Electronics, 12.10.3390/electronics12091999 ↗
13. Agostinelli, S., Marrella, A., and Mecella, M. (2021). Towards Intelligent Robotic Process Automation for BPMers. arXiv.
14. A Method to Improve the Early Stages of the Robotic Process Automation Lifecycle
15. Kokina, J., and Blanchette, S. (2019). Early Evidence of Digital Labor in Accounting: Innovation with Robotic Process Automation. Int. J. Account. Inf. Syst., 35.10.1016/j.accinf.2019.100431 ↗
16. Huang, F., and Vasarhelyi, M.A. (2022). Applying Robotic Process Automation (RPA) in Auditing: A Framework. Int. J. Account. Inf. Syst., 45.
17. Industry 5.0: The Potential for Additive Manufacturing
18. Longo, F., Padovano, A., and Umbrello, S. (2020). Value-Oriented and Ethical Technology Engineering in Industry 5.0: A Human-Centric Perspective for the Design of the Factory of the Future. Appl. Sci., 10.10.3390/app10124182 ↗
19. Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., Liu, X., Wu, Y., Dong, F., and Qiu, C.-W. (2021). Artificial Intelligence: A Powerful Paradigm for Scientific Research. Innovation, 2.10.1016/j.xinn.2021.100179 ↗
20. Artificial Intelligence Applications for Industry 5.0: A Literature-Based Study
21. Ghobakhloo, M., and Fathi, M. (2022). Industry 5.0 and Its Applications in Orthopedics. J. Clin. Orthop. Trauma, 34.
22. Kaasinen, E., Anttila, A.-H., Heikkilä, P., Laarni, J., Koskinen, H., and Väätänen, A. (2022). Smooth and Resilient Human–Machine Teamwork as an Industry 5.0 Design Challenge. Sustainability, 14.10.3390/su14052773 ↗
23. Akter, S., McCarthy, G., Sajib, S., Michael, K., Dwivedi, Y.K., D’Ambra, J., and Shen, K.N. (2021). Algorithmic Bias in Data-Driven Innovation in the Age of AI. Int. J. Inf. Manag., 60.10.1016/j.ijinfomgt.2021.102387 ↗
24. Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., and Eirug, A. (2021). Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice and Policy. Int. J. Inf. Manag., 57.10.1016/j.ijinfomgt.2019.08.002 ↗
25. Industry 5.0, a Transformative Vision for Europe: Governing Systemic Transformations Towards a Sustainable Industry
26. Identifying Industry 5.0 Contributions to Sustainable Development: A Strategy Roadmap for Delivering Sustainability Values10.1016/j.spc.2022.08.003 ↗
27. Winkler, D., Biffl, S., Mendez, D., Wimmer, M., and Bergsmann, J. (2021). Assisted Requirements Engineering—What Will Remain in the Hands of the Future Requirements Engineer? (Invited Keynote). Software Quality: Future Perspectives on Software Engineering Quality. SWQD 2021, Springer. Lecture Notes in Business Information Processing.10.1007/978-3-030-65854-0 ↗
28. Winkler, D., Biffl, S., Mendez, D., Wimmer, M., and Bergsmann, J. (2021). Testing Autogenerated OPC UA NodeSet Models for Product Variants in Industry. Software Quality: Future Perspectives on Software Engineering Quality. SWQD 2021, Springer. Lecture Notes in Business Information Processing.10.1007/978-3-030-65854-0 ↗
29. Braček Lalić, A., and Purg, D. (2021). Introduction. Hidden Champions in Dynamically Changing Societies, Springer.10.1007/978-3-030-65451-1 ↗
30. Braček Lalić, A., and Purg, D. (2021). Research Methodology. Hidden Champions in Dynamically Changing Societies, Springer.10.1007/978-3-030-65451-1 ↗
31. Braček Lalić, A., and Purg, D. (2021). Hidden Champions: Leadership Success Factors. Hidden Champions in Dynamically Changing Societies, Springer.10.1007/978-3-030-65451-1 ↗
32. Braček Lalić, A., and Purg, D. (2021). Hidden Champions: Common Lessons Learned on the Path to Success. Hidden Champions in Dynamically Changing Societies, Springer.10.1007/978-3-030-65451-1 ↗
33. Intelligent Manufacturing in the Context of Industry 4.0: A Review10.1016/J.ENG.2017.05.015 ↗
34. Industrial Artificial Intelligence for Industry 4.0-Based Manufacturing Systems
35. Smart Manufacturing Process and System Automation—A Critical Review of the Standards and Envisioned Scenarios10.1016/j.jmsy.2020.06.010 ↗
36. Nahavandi, S. (2019). Industry 5.0—A Human-Centric Solution. Sustainability, 11.10.3390/su11164371 ↗
37. Breque, M., De Nul, L., and Petridis, A. (2021). Industry 5.0: Towards a Sustainable, Human-Centric and Resilient European Industry, European Commission.
38. Industry 5.0 and Human-Robot Co-Working
39. European Commission (2021). Horizon Europe Strategic Plan 2021–2024, Publications Office of the EU.
40. Digital Transformation of Manufacturing Small and Medium Enterprises: A Maturity Model for Leveraging Industry 4.010.1108/JMTM-11-2020-0455 ↗
41. Literature Review of Industry 4.0 and Related Technologies10.1007/s10845-018-1433-8 ↗
42. When Titans Meet—Can Industry 4.0 Revolutionise the Environmentally Sustainable Manufacturing Wave?10.1016/j.techfore.2018.01.017 ↗
43. Central venous catheter replacement strategies: A systematic review of the literature10.1097/00003246-199708000-00033 ↗
44. The impact of patient, intervention, comparison, outcome (PICO) as a search strategy tool on literature search quality: A systematic review10.5195/jmla.2018.345 ↗
45. Maddikunta, P.K.R., Pham, Q.-V., Prabadevi, B., Deepa, N., Dev, K., Gadekallu, T.R., Ruby, R., and Liyanage, M. (2022). Industry 5.0: A survey on enabling technologies and potential applications. J. Ind. Inf. Integr., 26.10.1016/j.jii.2021.100257 ↗
46. Akundi, A., Euresti, D., Luna, S., Ankobiah, W., Lopes, A., and Edinbarough, I. (2022). State of Industry 5.0—Analysis and Identification of Current Research Trends. Appl. Syst. Innov., 5.10.3390/asi5010027 ↗
47. Industry 5.0: Prospect and retrospect10.1016/j.jmsy.2022.09.017 ↗
48. Žižić, M., Mladineo, M., Gjeldum, N., and Celent, L. (2022). From Industry 4.0 towards Industry 5.0: A Review and Analysis of Paradigm Shift for the People, Organization and Technology. Energies, 15.10.3390/en15145221 ↗
49. Behind the definition of Industry 5.0: A systematic review of technologies, principles, components, and values
50. Mourtzis, D., Angelopoulos, J., and Panopoulos, N. (2022). A Literature Review of the Challenges and Opportunities of the Transition from Industry 4.0 to Society 5.0. Energies, 15.10.3390/en15176276 ↗
51. Introna, V., Santolamazza, A., and Cesarotti, V. (2024). Integrating Industry 4.0 and 5.0 Innovations for Enhanced Energy Management Systems. Energies, 17.10.3390/en17051222 ↗
52. Birth of Industry 5.0: Making Sense of Big Data with Artificial Intelligence, “The Internet of Things” and Next-Generation Technology Policy10.1089/omi.2017.0194 ↗
53. Human-centric artificial intelligence architecture for industry 5.0 applications10.1080/00207543.2022.2138611 ↗
54. Human-Collaborative Artificial Intelligence Along With Social Values in Industry 5.0: A Survey of the State-of-the-Art10.1109/TCDS.2023.3326192 ↗
55. Robotic process automation for industry: Adoption status, benefits, challenges and research agenda10.1108/BIJ-01-2021-0033 ↗
56. Nalgozhina, N., Razaque, A., Raissa, U., and Yoo, J. (2023). Developing Robotic Process Automation to Efficiently Integrate Long-Term Business Process Management. Technologies, 11.10.3390/technologies11060164 ↗
57. Robotic Process Automation: A Scientific and Industrial Systematic Mapping Study10.1109/ACCESS.2020.2974934 ↗
58. A Systematic Review of Robotic Process Automation in Business Operations: Contemporary Trends and Insights10.56578/jisc020304 ↗
59. Robotic Process Automation in Artificial Intelligence10.38124/ijisrt/IJISRT24MAR321 ↗