As processes become more complex, the biggest challenge is not a single work step but controlling the entire process. Artificial intelligence agents support a continuous situational picture and help to react to deviations in a timely manner.

In many organizations, processes progress through multiple systems and teams. Information is accumulated in stages, and the overall picture often forms only afterwards through reporting. Dispersed situational information makes it difficult to anticipate and slows down reaction in situations where deviations would require quick action.

Agent-based automation brings a continuous monitoring perspective to processes. Instead of periodically reviewing the process state, agents monitor events in real time and highlight deviations from expectations.

The agent-based operating model shifts the focus from reactive control to proactive management. In this case, process development is based on observations, not assumptions.

Read more about the role of agents in basic process processing and information management.

Creating a situational picture from distributed data

In many operating environments, situational information is generated from multiple sources. In logistics, production environments, and extensive field operations, some information is updated automatically, while other information is based on reporting or situational updates that may not be received in a timely manner.

An agent can be defined as continuously monitoring information arriving from different channels and systems. It identifies objects that are missing updates or whose status differs from expectations, and combines observations with previous context and historical information.

The situational picture is formed within the process without separate compilation work. Experts can see in real time where attention is needed overall.

Identification and guided handling of deviations

Deviations are not a problem in themselves, but identifying them too late causes delays and additional work. In many processes, deviations are only detected when the effects are visible in customer work or reporting.

The agent can evaluate deviations based on predefined rules and historical data. Some deviations can be identified as acceptable, for example, based on planned stops or pre-agreed exceptional situations.

Situations for which no acceptable explanation can be found are directed for further processing. This way, the experts’ attention is focused only on cases that require consideration or decision-making.

Process development through continuous monitoring

As information about the process accumulates, the nature of the development work changes. Instead of individual development projects, the process can be viewed as a continuous whole, where bottlenecks and delays are identified in time.

The agent monitors, for example, processing times, transitions between stages, and the number of deviations. Based on these observations, a clear picture emerges of which stages have the greatest impact on lead time and load.

Development activities can be targeted at those points where the impact is greatest. The process adapts as operations and volume change without rebuilding the entire operating model.

Agents as part of a managed process entity

The value of agents arises especially in the control and monitoring of processes, where the timeliness of the situational picture and the identification of deviations directly affect the smoothness of operations. Common to these use cases is distributed information and the need to form an overall picture in time.

The agent-based model does not replace existing systems but acts as a connecting layer between them. Development can start with a single limited process and expand based on the benefits observed.

If process control, deviation management, or situational picture formation is a current development target, development can be initiated in a controlled manner in a joint workshop. The workshop examines the processes as a whole and identifies the points at which agent-based automation delivers the greatest value.

Discover the workshop on developing processes using artificial intelligence.

Marko Koskela
Chief Commercial Officer, partner