Celonis boss: 'If we're honest, AI adoption hasn’t gone as quickly as expected’

2026-06-04 · Source: Sifted · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management · Depth: Fundamental Awareness, short

Summary

Celonis CEO Alex Rinke states that enterprise AI adoption has not progressed as quickly as anticipated, despite its prominence in boardroom discussions. Rinke, leading the \$13bn software giant with 3,000 employees, attributes this slower pace to challenges in implementation and data readiness within companies. Celonis aims to address this by developing "process intelligence engines," which combine process mining with AI to identify automation opportunities and streamline operations. The company recently acquired Lenses.io, adding 50 AI experts, to bolster its capabilities. Celonis positions itself as a category creator, competing with firms like Palantir, SAP, IBM, and Microsoft in the evolving AI landscape.

Key takeaway

For Directors of AI/ML or VPs of Engineering evaluating enterprise AI strategies, recognize that successful adoption hinges on robust data and process readiness, not just technology. Your teams should prioritize establishing a "process intelligence engine" by integrating process mining with AI to identify concrete automation opportunities. This approach helps move AI initiatives beyond pilot stages into impactful, scalable deployments, mitigating risks associated with premature or unfocused AI investments.

Key insights

Enterprise AI adoption lags due to implementation and data readiness, necessitating "process intelligence engines."

Principles

• AI adoption requires robust data and process readiness.
• "Process intelligence engines" bridge AI hype and reality.
• Acquiring specialized AI talent accelerates capability.

Method

Celonis proposes combining process mining with AI to create a "process intelligence engine" that identifies and automates process improvements.

In practice

• Utilize process mining to pinpoint AI application areas.
• Invest in data readiness before scaling AI initiatives.
• Consider strategic acquisitions for AI talent.

Topics

• AI Adoption
• Process Mining
• Enterprise AI
• Celonis
• Process Intelligence
• Digital Transformation

Best for: Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Sifted.