Exploring the Interplay of Process Mining and Generative AI : Research and Recommendations for CoEs

Title data

Reinkemeyer, Lars ; Röglinger, Maximilian ; Kratsch, Wolfgang ; Fabri, Lukas ; Schmid, Sebastian Johannes ; Wittmann, Jakob:
Exploring the Interplay of Process Mining and Generative AI : Research and Recommendations for CoEs.
Celonis
München ; Bayreuth , 2023 . - 41 p.

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Generative AI is rapidly emerging as a revolutionary technology with the potential to transform and disrupt entire industries and our everyday lives. However, its full extent and impact on various sectors remain largely unknown, as the technology is still in its infancy and has not yet progressed to large-scale corporate use. Process Mining, on the other hand, has evolved throughout the last two decades and allows for a unique, end-to-end, data-driven perspective on business processes, which raises the question of how the interplay of both technologies can unleash unknown potentials in the future. Specifically, we have zoomed into organizational aspects to assess how Process Mining Centers of Excellence (CoEs) should prepare to accelerate the usage of Generative AI.

To answer this question, this collaborative research conducted by Celonis and Fraunhofer FIT delves deep into the dynamics of Process Mining and Generative AI. Interviews with 14 Process Mining thought leaders from industry and academia were carried out to gain a better understanding of the future that lies ahead for Centers of Excellence.

Our research reveals that Process Mining and Generative AI enter a powerful synergy. Process Mining can provide a comprehensive Process Intelligence layer which is crucial to enable Generative AI to go beyond hallucinations towards reliable results. On the other hand Generative AI will democratize the usage of Process Mining and make it available for a much wider group of business users. To fully leverage the potential of this synergy, Centers of Excellence should take action in particular on two levels:
1. On a technology-level by establishing a Process Intelligence layer including data availability / quality / privacy / security.
2. On a governance-level by establishing the right value proposition, operating model, roles & responsibilities as well as community leadership.