We know how BPM has impacted many industries with productivity, optimization, error reduction, high efficiency, and so on. We know it had transformed the operations of every industry giving it a competitive edge and optimization. But still yes, BPMs need human intelligence to some degree to make some critical decisions or provide the system with pre-determined business logic to act upon.
But with the growing complexity of business nature in the modern world, these tasks become extremely complicated. With more process complications there is a growing demand for process-aware BPM systems that is AI-augmented Business Process Management (ABPMS). Nevertheless, there is no lucid understanding of when it comes to ABPMS by many. [Note: Don’t confuse Advanced BPM with AI-augmented BPM]
For those who are not well aware of what is BPM, here is the definition ” a collection of tasks that are executed in a specific sequence to achieve some business goal, such as producing a service or product for customers “. It involves analyzing, modeling, and improving processes to make them more efficient and effective. BPM can help businesses achieve their goals by providing a framework for continuous improvement and innovation. It can also help businesses reduce costs, increase productivity, and improve customer satisfaction. With BPM, businesses can better understand their processes, identify areas for improvement, and implement changes that lead to better performance and results. Overall, BPM is a valuable tool for businesses looking to stay competitive and achieve success in today’s fast-paced business environment.
What is ABPMS?
To state simply, an ABPMS is an information system that leverages Artificial Intelligence (AI) to adapt and improve business processes autonomously. It operates within a set of restrictions and doesn’t require explicit changes to software applications. This system is different from other AI systems as it is process-aware and can support one or more processes.
But what is a process-aware system? Let me give you an example, let us take data capture software that takes in data from forms and documents, including hand-written documents and others, it performs only a single isolated task. Of course, that might be an essential component but they are isolated. So what does it mean? Software that performs multiple tasks and streamlines business processes and is adaptive to the dynamics or changes in the business processes.
Characteristics & Functions, Benefits & Differences
Characteristics of ABPMS
According to the postulation of a few researchers, ABPMS must possess
(1) (framed) autonomous to act independently and proactively;
(2) conversationally actionable to seamlessly interact with agents whenever necessary;
(3) adaptive to react to changes in its environment;
(4) (self-)improving to ensure the optimal achievement of its goals;
(5) explainable to ensure trust and hence the cooperation of the human agents.
Functions of ABPMS
- It supports one or more processes: A business process is a collection of tasks that are executed in a specific sequence to achieve a business goal, such as producing a service or product for customers. An ABPMS operates on the level of processes, not isolated tasks.
- It tracks the execution of processes: The system ensures that each process conforms to a set of restrictions, called the process frame. The process frame defines the boundaries within which the ABPMS should operate, and it may be tightly or loosely specified. The system uses various approaches to frame the process, such as Petri nets or temporal logic constraints.
- It orchestrates the activities of processes: The ABPMS operates largely autonomously, within the process frame’s boundaries. It performs activities, such as starting an activity once its preconditions are fulfilled, routing, or performing activities while facilitating human-machine cooperation and guidance when the restrictions are not or cannot be met.
- It uses AI technology to attain the goal of a business process: The system uses AI technology to drive the execution of business processes. AI technology helps the system to identify and respond to situations where the restrictions in a process frame cannot be met. It may use computer vision, signal processing, Natural Language Understanding (NLU), or knowledge graphs to detect and respond to such situations.
KEY DIFFERENCE BETWEEN ABPMS & BPMS
Benefits of AI Augmented Business Process Management System
An ABPMS has several benefits, such as:
- Continuous process improvement: The system can autonomously adapt and improve business processes to achieve better performance indicators.
- Increased efficiency: The system can perform activities autonomously and optimize the use of resources.
- Better decision-making: The system can use AI technology to identify and respond to situations where the restrictions in a process frame cannot be met, leading to better decision-making.
Challenges & Opportunities
However, there are numerous challenges that exist in order to bring this system into reality. They are,
- Situation-aware explainability: The idea of Autonomous Business Process Management Systems (ABPMSs) is gaining traction due to their intrinsic explainability capabilities. The ABPMSs can offer a variety of explanations, such as providing reasons for a task or decision and ensuring the trust and cooperation of human agents. However, existing techniques lack clear semantics of their reasoning, and they remain detached from the broader process context. To be effective, ABPMSs must provide situation-aware explainability that can capture the relevant situational factors and reflect potential inferential associations that go beyond the local reasoning context. The inclusion of AI in the context of processes offers a unique opportunity for further developments of new explainability techniques and process execution management infrastructure that allow for the valid establishment of reasoning in retrospect. The use of event knowledge graphs can symbolically represent situations of all kinds for situation-aware reasoning, facilitating the tracking of execution consistency for a better understanding of process flows and outcomes.
- Automated Process Automation: AI-Augmented Business Process Management Systems (ABPMS) have the potential to achieve more complex automation than traditional Business Process Management Systems (BPMS) by using AI to minimize human-dependent training and support human users in executing complex tasks that involve decision-making. While Robotic Process Automation (RPA) technology provides a partial solution by automating repetitive tasks on the user interface of software applications, it cannot fully replace human users. Instead, ABPMS aims to augment human capabilities by leveraging AI techniques to interact with human users as “learning apprentices.” This requires a two-sided interaction where the ABPMS recognizes situations and escalates key decisions to human decision-makers, while human users can override decisions to prevent mistakes and enhance the ABPMS’s internal learning of the process.
- Automated Process Adaptation: For an ABPMS to effectively manage processes in dynamic contexts, it must provide real-time monitoring and automated adaptation features during process execution to adapt to exceptions, exogenous events, and contextual changes that may occur. Previous research work identified a common pattern where a process designer identifies potential exceptions and specifies suitable exception handlers to catch and fix them. At runtime, errors and other events may interrupt the process flow, and an exception handler is invoked to catch the exception. Various techniques, such as adaptation patterns, case-based reasoning, and AI planning, have been applied to increase the degree of automated process adaptation. SmartPM provides an important demonstration of how automated adaptation can be incorporated into an ABPMS, but designing the family of tasks involved in a process can be a daunting task. Specific design patterns and heuristics may help improve the system’s ability to deal with unanticipated situations at runtime.
- Perspective Agility: Unlike traditional Business Process Management Systems (BPMSs), Agile Business Process Management Systems (ABPMSs) must support processes with incomplete or unknown structures at design time, which may emerge at run-time. ABPMSs require a mix of formalisms and interrelated artifact types, including temporal constraints, goal specifications, flowcharts, and data objects, to achieve agile process executions. The challenge of multi-perspective support of processes must be addressed by integrating various formalisms and conceptualizations, as well as behavioral characteristics and constraints of entities interacting in the shared process context. To address this challenge, a simple graph-based model can be used to encode the concepts and phenomena studied separately in a uniform format. A solution to perspective agility must allow the description and inference of the process in any chosen combination of perspectives.
- Actionable Conversation: Developing solutions that facilitate the interaction between users and an ABPMS is a major challenge. While there is a trend towards automating processes with chatbots, an ABPMS should provide an interface that relies on AI to create dynamic conversations. This interface should not only respond to user queries and perform actions but also initiate conversations to inform users of process progression, alert them of relevant changes, and make recommendations for improvement. To achieve this, an integrated use of Natural Language Processing and Machine Learning techniques should be adopted to enable tailored responses for recurrent users. Recent research has emphasized the importance of natural language understanding and generative machine learning models for less reactive chatbot development. However, scalability, agent overlap, and access control remain significant challenges.
Let’s Reimagine The Future with ABPM…
As businesses continue to evolve and adapt to the changing needs of the marketplace, the role of artificial intelligence (AI) is becoming increasingly vital. This AI-augmented Business Process Management Systems (ABPMS) technology is eyed by the AI community now and will certainly have it built very soon in the future. With the ability to streamline complex business processes, reduce operational costs, and enhance the customer experience, ABPMS is poised to transform the way businesses operate. As more and more companies begin to adopt this innovative technology, there is a growing sense of anticipation and excitement around how ABPMS will shape the future of AI in business. With so much potential for disruption and innovation, it’s no wonder that many industry experts believe ABPMS will be the driving force behind the next wave of business transformation. The question now is, how exactly will ABPMS revolutionize the way businesses do? Toolfe is on the highway to realize the dreams of the future laid by enthusiasts!
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References:
- Dumas, M., Fournier, F., Limonad, L., Marrella, A., Montali, M., Rehse, J. R., Accorsi, R., Calvanese, D., De Giacomo, G., Fahland, D., Gal, A., La Rosa, M., Völzer, H., & Weber, I. (2023, January 31). AI-augmented Business Process Management Systems: A Research Manifesto. ACM Transactions on Management Information Systems, 14(1), 1–19. https://doi.org/10.1145/3576047