Emergent Behavior and Uncertainty in IoT-Enhanced Business Processes: Challenges and Future Directions

Computer Science > Emerging Technologies
[Submitted on 28 Aug 2026]
Title:Emergent Behavior and Uncertainty in IoT-Enhanced Business Processes: Challenges and Future Directions
View PDF HTML (experimental)Abstract:IoT-enhanced business processes are characterized by high complexity due to heterogeneous actors, varying levels of autonomy among participating systems, continuously evolving execution contexts spanning the digital and physical worlds, and continuous event streams. In such settings, process behavior partially emerges only at runtime through complex interactions involving humans, IoT devices, physical objects, software systems, agents, and services. This complexity introduces partial observability, uncertainty, and runtime dynamics that are difficult to anticipate and that challenge traditional business process management (BPM) assumptions and systems. We discuss these challenges from three perspectives, addressing 1) uncertainty representation, 2) operationalization of IoT-enhanced processes, and 3) runtime management of emergent behavior. Based on a motivating scenario and an analysis of the state of the art, we identify open research gaps and outline short-, medium-, and long-term recommendations to shape a research agenda on emergent behavior in IoT-enhanced business processes.
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Facts Only

* IoT-enhanced business processes involve heterogeneous actors and varying levels of system autonomy.
* Process behavior emerges only at runtime through complex interactions between humans, IoT devices, physical objects, software systems, agents, and services.
* The complexity introduces partial observability, uncertainty, and runtime dynamics.
* Challenges include representing uncertainty, operationalizing IoT-enhanced processes, and managing emergent behavior.
* The work identifies research gaps and outlines recommendations for future research on emergent behavior in these processes.

Executive Summary

IoT-enhanced business processes exhibit high complexity stemming from heterogeneous actors, varying system autonomies, evolving execution contexts across digital and physical domains, and continuous event streams. Process behavior emerges dynamically at runtime through interactions involving humans, IoT devices, physical objects, software systems, agents, and services. This dynamic environment introduces challenges related to partial observability, uncertainty, and runtime dynamics that complicate traditional Business Process Management assumptions. The discussion addresses these challenges by focusing on three areas: uncertainty representation, the operationalization of IoT-enhanced processes, and the runtime management of emergent behavior. The paper aims to identify research gaps and propose recommendations for shaping future research on emergent behavior in this context.

Full Take

The focus on emergent behavior within IoT-enhanced systems highlights a critical tension between the formal, deterministic nature of traditional Business Process Management (BPM) and the complex, unpredictable realities of cyber-physical interactions. The challenge is not merely technical but epistemological: how to manage systems whose state is constantly shifting based on physical reality and asynchronous digital events. The necessity of addressing uncertainty representation, operationalization, and runtime management suggests that current BPM paradigms are insufficient for truly adaptive systems. A key implication is that future frameworks must shift from static modeling to dynamic, real-time governance capable of handling system evolution rather than just tracking pre-defined flows. The research agenda proposed points toward the need for integrating methods from control theory, multi-agent systems, and probabilistic reasoning into process management to account for genuine runtime emergence, moving beyond simple state transitions. What is missing is a deeper analysis of the practical costs associated with uncertainty propagation in high-stakes business contexts, and what organizational structures are required to effectively monitor and govern these dynamic behaviors across the digital-physical divide.

Sentinel — Human

Confidence

The text exhibits the characteristic structure and density of a formal academic abstract, suggesting it originates from human scholarly work rather than synthetic generation.

Signals Detected

Moderate sentence length variance; academic but flows logically.

High internal coherence characteristic of academic abstracts; no overt emotional inflection.

Standard academic structure (Abstract, framing challenges, outlining directions); lacks typical journalistic boilerplate.

The content reads like a genuine academic abstract/introduction setting up research gaps; no obvious LLM confabulation detected.

Human Indicators

The specific framing around 'emergent behavior,' 'partial observability,' and structuring recommendations based on distinct perspectives strongly suggests domain-specific human academic discourse.