AI Adoption in Business Process Management (BPM)

This survey is part of a bachelor thesis in the Data Science and Business program at Berlin International University of Applied Sciences, conducted under the supervision of Prof. Dr.-Ing. Hasan Koç. The research focuses on the role of artificial intelligence (AI) in business process management (BPM).

The aim is to better understand how organizations adopt AI, what benefits they experience, what challenges they encounter, and how prepared they are for AI integration.

Your responses will help complement insights from expert interviews by providing a broader industry-wide perspective. The survey takes approximately 5 minutes, and your input will offer valuable context for interpreting in-depth interview findings and contribute to a more comprehensive understanding of AI adoption in BPM practice.

All data is collected anonymously and used solely for academic purposes.

If you have any questions about the study or survey, feel free to contact me at vandavinecka@berlin-international.de.

Thank you for your time and valuable contribution!

Zabezpečeno

AI Adoption in Business Process Management (BPM)

How would you describe the level of digital transformation in your organization?

How would you describe the current use of AI in business process management in your organization?

In which areas is AI used in your BPM context?

In what ways do you personally use AI tools in your work (outside of BPM systems)?

AI helps us make better and faster decisions by providing accurate data insights and supporting complex choices.

AI makes our work processes more efficient and faster by helping automate tasks and reduce delays or unnecessary steps.

AI reduces our operational costs by automating routine tasks that used to require manual effort.

AI helps us improve or redesign how our processes work — from small improvements to completely new ways of doing things.

AI makes it easier to share knowledge, learn from data, and apply insights across teams.

AI improves how our processes perform overall — including how fast, flexible, and high-quality they are.

We lack internal expertise (e.g., skilled people or AI knowledge) to implement and manage AI projects.

Our data is incomplete, inconsistent, or not well prepared for use in AI systems.

It is difficult to integrate AI solutions into our existing systems and workflows.

There is resistance or hesitation among employees to work with AI (e.g., due to fear or uncertainty).

We lack sufficient financial resources or budget to invest in AI-related initiatives.

Our top management is not actively supporting or prioritizing AI adoption.

We are concerned about legal, ethical, or regulatory risks (e.g., data privacy, transparency, compliance).

Our organization has the IT infrastructure to support AI applications.

Top management actively supports and promotes AI initiatives

We have sufficient human and technical resources to implement AI projects.

Our organizational culture supports collaboration and openness to AI innovation.

The size of our organization enables us to dedicate resources to AI effectively.

Your Job Role

Type of your role in relation to AI in business processes

Size of the organization you work in

Industry