Skip to main content
Springer Nature Link
Log in

An Integrated Approach Using Robotic Process Automation and Artificial Intelligence as Disruptive Technology for Digital Transformation

  • Conference paper
  • First Online:
Information Systems (EMCIS 2022)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 464))

  • 1535 Accesses

Abstract

Digital transformation is a phenomenon arising from social, behavioral and habitual changes due to global economic and technological development. Its main characteristic is adopting disruptive digital technologies by organizations to transform their capabilities, structures, processes and business model components. One of the disruptive digital technologies used in organizations’ digital transformation process is Robotic Process Automation. However, the use of Robotic Process Automation is limited by several constraints that affect its reliability and increase the cost. Artificial Intelligence techniques can improve some of these constraints. The use of Robotic Process Automation combined with Artificial Intelligence capabilities is called Hyperautomation. However, there is a lack of solutions that successfully integrate both technologies in the context of digital transformation. This work proposes an integrated approach using Robotic Process Automation and Artificial Intelligence as disruptive Hyperautomation technology for digital transformation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Hess, T., Matt, C., Benlian, A., Wiesböck, F.: Options for formulating a digital transformation strategy. MIS Q. Exec. 15(2), 123–139 (2016)

    Google Scholar 

  2. Da Silva Neto, V.J., Chiarini, T.: Technological progress and political systems: non-institutional digital platforms and political transformation. Technol. Soc. 64, 101460 (2021)

    Article  Google Scholar 

  3. Nadkarni, S., Prügl, R.: Digital transformation: a review, synthesis and opportunities for future research. Manag. Rev. Q. 71(2), 233–341 (2020). https://doi.org/10.1007/s11301-020-00185-7

    Article  Google Scholar 

  4. Ribeiro, J., Lima, R., Eckhardt, T., Paiva, S.: Robotic process automation and artificial intelligence in industry 4.0–a literature review. Procedia Comput. Sci. 181, 51–58 (2021)

    Google Scholar 

  5. Bu, S., Jeong, U.A., Koh, J.: Robotic process automation: A new enabler for digital transformation and operational excellence. Bus. Commun. Res. Pract. 5, 29–35 (2022)

    Article  Google Scholar 

  6. Daptardar, S.: A review-the golden triangle of RPA, AI and digital transformation. Int. Res. J. Mod. Eng. Technol. Sci. 3, 887–891 (2021)

    Google Scholar 

  7. Siderska, J.: Robotic process automation – a driver of digital transformation? Int. J. Inf. Manag. 12, 21–31 (2020)

    Google Scholar 

  8. Kaarnijoki, P.: Intelligent automation-assessing artificial intelligence capabilities potential to complement robotic process automation. M.S. thesis. Faculty of Engineering and Natural Sciences, Tampere University of Technology. Tampere, Finland (2019)

    Google Scholar 

  9. van der Aalst, W.M.P., Bichler, M., Heinzl, A.: Robotic process automation. Bus. Inf. Syst. Eng. 60(4), 269–272 (2018). https://doi.org/10.1007/s12599-018-0542-4

    Article  Google Scholar 

  10. König, M., Bein, L., Nikaj, A., Weske, M.: Integrating robotic process automation into business process management. In: Asatiani, A., et al. (eds.) BPM 2020. LNBIP, vol. 393, pp. 132–146. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58779-6_9

    Chapter  Google Scholar 

  11. Mendling, J., Decker, G., Hull, R., Reijers, H.A., Weber, I.: How do machine learning, robotic process automation, and blockchains affect the human factor in business process management? Commun. Assoc. Inf. Syst. 43, 19 (2018)

    Google Scholar 

  12. Yatskiv, N., Yatskiv, S., Vasylyk, A.: Method of robotic process automation in software testing using artificial intelligence. In: 10th International Conference on Advanced Computer Information Technologies (ACIT), pp. 501–504. IEEE, Deggendorf, Germany (2020)

    Google Scholar 

  13. Nakano, M.: Artificial intelligence and robotic process automation for accounting and auditing in society 5.0. J. Soc. Sci. 89, 51–61 (2022)

    Google Scholar 

  14. Hartmann, F.: Evolving digitisation: chances and risks of robotic process automation and artificial intelligence for process optimization within the supply chain. B.A. thesis, Berlin School of Economics and Law, Berlin, Germany (2018)

    Google Scholar 

  15. Turcu, C.E., Turcu, C.O.: Digital transformation of human resource processes in small and medium sized enterprises using robotic process automation. Int. J. Adv. Comput. Sci. Appl. 12(12), 70–75 (2021)

    Google Scholar 

  16. Madakam, S., Holmukhe, R.M., Jaiswal, D.K.: The future digital work force: robotic process automation (RPA). JISTEM-J. Inf. Syst. Technol. Manag. 16 (2019)

    Google Scholar 

  17. Houy, C., Hamberg, M., Fettke, P.: Robotic process automation in public administrations. Digitalisierung von Staat und Verwaltung (2019)

    Google Scholar 

  18. Bornet, P., Barkin, I., Wirtz, J.: Intelligent automation: welcome to the world of hyperautomation: learn how to harness artificial intelligence to boost business and make our world more human (2021)

    Google Scholar 

  19. Udovita, P.: Conceptual review on dimensions of digital transformation in modern era. Int. J. Sci. Res. Publ. 10, 520–529 (2020)

    Google Scholar 

  20. Bradley, J., Loucks, J., Macaulay, J., Noronha, A., Wade, M.: Digital vortex: how digital disruption is redefining industries. Global Center for Digital Business Transformation: an IMD and Cisco Initiative (2015)

    Google Scholar 

  21. Liermann, V., Li, S., Waizner, J.: Hyperautomation (automated decision-making as part of RPA). In: Liermann, V., Stegmann, C. (eds.) The Digital Journey of Banking and Insurance, Volume II, pp. 277–293. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-78829-2_16

    Chapter  Google Scholar 

  22. Martins, P., Sá, F., Morgado, F., Cunha, C.: Using machine learning for cognitive robotic process automation (RPA). In: 15th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–6. IEEE (2020)

    Google Scholar 

  23. Patel, M., Shukla, A., Porwal, R., Kotecha, R.: Customised automated email response bot using machine learning and robotic process automation. In: 2nd International Conference on Advances in Science and Technology (ICAST). SSRN, Maharashtra, India (2019)

    Google Scholar 

  24. Bellman, M., Göransson, G.: Intelligent process automation: building the bridge between robotic process automation and artificial intelligence. M.S. thesis. School of Industrial Engineering and Management, Kth Royal Institute of Technology. Stockholm, Sweden (2019)

    Google Scholar 

  25. Parchande, S., Shahane, A., Dhore, M.: Contractual employee management system using machine learning and robotic process automation. In: 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA), pp. 1–5. IEEE, Pune, India (2019)

    Google Scholar 

  26. Hu, S., Jiang, T.: Artificial intelligence technology challenges patent laws. In: International Conference on Intelligent Transportation, Big Data and Smart City (ICITBS), pp. 241–244. IEEE, Changsha, China (2019)

    Google Scholar 

  27. Nunes, T., Leite, J., Pedrosa, I.: Automação Inteligente de Processos: Um Olhar sobre o Futuro da Auditoria Intelligent Process Automation: An Overview over the Future of Auditing. In: 5th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, Sevilla, Spain (2021)

    Google Scholar 

  28. Ray, S.: A quick review of machine learning algorithms. In: International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon), pp. 35–39. IEEE, Faridabad, India (2019)

    Google Scholar 

  29. Grekousis, G.: Artificial neural networks and deep learning in urban geography: a systematic review and meta-analysis. Comput. Environ. Urban Syst. 74, 244–256 (2019)

    Article  Google Scholar 

  30. Madakam, S., Holmukhe, R.M., Revulagadda, R.K.: The next generation intelligent automation: hyperautomation. J. Inf. Syst. Technol. Manag. 19 (2022)

    Google Scholar 

  31. Jha, N., Prashar, D., Nagpal, A.: Combining artificial intelligence with robotic process automation—an intelligent automation approach. In: Ahmed, K.R., Hassanien, A.E. (eds.) Deep Learning and Big Data for Intelligent Transportation. SCI, vol. 945, pp. 245–264. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-65661-4_12

    Chapter  Google Scholar 

  32. Abiodun, O.I., Jantan, A., Omolara, A.E., Dada, K.V., Mohamed, N.A., Arshad, H.: State-of-the-art in artificial neural network applications: a survey. Heliyon 4(11), e00938 (2018)

    Article  Google Scholar 

  33. Somvanshi, M., Chavan, P., Tambade, S., Shinde, S.V.: A review of machine learning techniques using decision tree and support vector machine. In: International Conference on Computing Communication Control and Automation (ICCUBEA). IEEE, Pune, India (2016)

    Google Scholar 

  34. Charity, B., Abdulazeez, A.: Classification based on decision tree algorithm for machine learning. J. Appl. Sci. Technol. Trends 2, 20–28 (2021)

    Article  Google Scholar 

  35. Kuo, P., Huang, C.: A high precision artificial neural networks model for short-term energy load forecasting. Energies 11(1), 213 (2018)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-801, Vila Real, Portugal

    Anderson Araújo & Vítor Filipe

  2. INESC TEC, Universidade Aberta, R. da Escola Politécnica nº 147, 1269-001, Lisbon, Portugal

    Henrique S. Mamede & Vitor Santos

  3. INESC TEC – INESC Tecnologia e Ciência, 4200-465, Porto, Portugal

    Vítor Filipe

Authors
  1. Anderson Araújo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Henrique S. Mamede
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vítor Filipe
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vitor Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anderson Araújo .

Editor information

Editors and Affiliations

  1. British University in Dubai, Dubai, United Arab Emirates

    Maria Papadaki

  2. University of Coimbra, Coimbra, Portugal

    Paulo Rupino da Cunha

  3. University of Nicosia, Nicosia, Cyprus

    Marinos Themistocleous

  4. University of Nicosia, Nicosia, Cyprus

    Klitos Christodoulou

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Araújo, A., Mamede, H.S., Filipe, V., Santos, V. (2023). An Integrated Approach Using Robotic Process Automation and Artificial Intelligence as Disruptive Technology for Digital Transformation. In: Papadaki, M., Rupino da Cunha, P., Themistocleous, M., Christodoulou, K. (eds) Information Systems. EMCIS 2022. Lecture Notes in Business Information Processing, vol 464. Springer, Cham. https://doi.org/10.1007/978-3-031-30694-5_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-30694-5_32

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30693-8

  • Online ISBN: 978-3-031-30694-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics