Process Intelligence 2025: A Technology Recap
In 2025, Process Intelligence has finally evolved from a pure analysis tool into a strategic core technology. What once primarily provided transparency into processes is now the foundation for informed decision-making, automation, and the targeted use of artificial intelligence. The focus has clearly shifted away from visualization alone toward impact, context, and measurable business value.
Process Intelligence as the Foundation for Agentic AI
A key driver of this evolution is the increasing adoption of agent-based AI. AI agents are designed to make decisions independently or even execute them autonomously. To do so, however, they require context – and this is exactly where Process Intelligence comes into play.
Process data provides the essential understanding of how work actually happens, where bottlenecks occur, and which dependencies exist. Without this process understanding, AI agents remain blind to cause-and-effect relationships.
By 2025, it has become clear: Process Intelligence is not just an analytical tool, but the foundation for agentic AI and smart actions.
Native Platform Mining Gains Momentum
At the same time, a clear architectural principle has emerged: process mining should happen where the data resides. Instead of copying data into separate systems, so-called native platform mining is gaining traction.
Modern data platforms such as Snowflake, Databricks, or Qlik are increasingly becoming central hubs for analytics, AI, and operational workloads. Process Intelligence integrates seamlessly into this ecosystem. In 2025, mpmX has demonstrated that native Process Intelligence on these platforms is not only technically feasible, but also scalable and future-proof.
The result:
- no redundant data silos
- no complex ETL pipelines
- significantly shorter time-to-value
Process Intelligence thus becomes an integral part of the data platform – not yet another isolated solution.
Generative AI Becomes a Process Advisor
Another milestone in 2025: Generative AI has evolved from experimentation to a true day-to-day companion. Large language models (LLMs) translate complex process and analytics results into clear, action-oriented language.
Instead of interpreting dashboards, users can ask questions such as:
- Why are delays occurring right now?
- Where is the greatest optimization potential?
- Which measures promise the highest impact?
The answers no longer come in the form of abstract KPIs, but as concrete recommendations in natural language – almost like a dialogue with a digital process consultant. This is not an isolated phenomenon, but a clear market trend across multiple industries.
Machine Learning Finally Becomes Understandable
Classic machine learning models are also experiencing renewed relevance in 2025. Their predictions have always been valuable, but often difficult to explain. By combining ML models with LLMs, these results become “speakable” for the first time.
Complex relationships (such as why certain cases escalate or lead times increase) can now be explained in a transparent and comprehensible way. For business users, ML insights become trustworthy and directly usable in daily operations.
This is where current mpmX prototypes come into play. Together with customers, mpmX is exploring how process data, ML models, and LLMs can be combined to explain root causes and derive concrete improvement actions – in a way that is understandable, contextual, and practical.
Business Value Takes Center Stage
As the technology matures, expectations around measurable impact increase as well. Process Intelligence must deliver business value and be able to quantify it.
Value engineering has become a core component of successful initiatives. The goal is to define relevant KPIs from the outset, track progress transparently, and clearly demonstrate the contribution of process improvements – whether in terms of time, cost, or quality.
In 2025, mpmX has consistently advanced this approach and embedded business value engineering as an integral part of the platform. The focus is no longer solely on analysis, but on sustainable customer success and tangible results.
Conclusion: Process Intelligence Becomes Action-Oriented
2025 marks a turning point for Process Intelligence:
- it provides context for AI and agents
- it integrates natively into modern data platforms
- it makes complex analytics understandable
- and it delivers measurable business value
Process Intelligence is no longer just a tool for process visibility, but a central building block for intelligent, data-driven organizations.
