Artificial Intelligence in Business Process Management

Artificial Intelligence is THE key technology of the 21st century and has long been an integral part of our everyday lives: voice assistants, navigation systems, smart homes and weather forecasts are just a few of the countless examples. Artificial Intelligence is also increasingly attracting attention in Business Process Management and equipping companies with unimagined possibilities for smart, data-driven and even more efficient process management.

What are the benefits of AI-driven Business Process Management?

Artificial Intelligence leads to faster results, better decision-making, and higher quality and efficiency in many areas of life and work, including Business Process Management (BPM). BPM emerged in practice in the late 1980s and has evolved into a critically successful management tool over time. Nowadays, companies of all sizes and industries utilize BPM to improve the efficiency, productivity, and quality of their operational processes.
With the emergence and rapid advancement of Artificial Intelligence, the methods and possibilities in process management are undergoing a fundamental revolution and significant expansion. One thing is certain: AI will noticeably change the future of Business Process Management, enabling companies to achieve their process optimization and transformation goals even faster and more effectively.

AI in Business Process Management

What is Artificial Intelligence?

Artificial Intelligence, also known as AI, is a subfield of computer science that focuses on the development and enablement of computer systems to perform tasks that typically require human intelligence. This involves the development of algorithms and models that are capable of learning from data, recognizing patterns, making decisions, and solving problems in a way that mimics human cognitive abilities. Typical applications include machine learning, natural language processing, robotics, and process mining.

Applications of Artificial Intelligence in Business Process Management

With the help of AI, process management practitioners can achieve the highest level of efficiency and value for their Business Process Management. When it comes to processing vast, complex datasets and deriving actionable recommendations, human capabilities eventually reach their limits. Therefore, Artificial Intelligence can be particularly beneficial in the following areas:

Process simulation

For example, Artificial Intelligence can support process simulation by analyzing historical process data. Through the use of machine learning and deep learning, AI algorithms can identify patterns and dependencies within the process data and integrate them into a simulation model. Within this simulation model, various scenarios and process variants can be simulated and tested. This allows companies to calculate key performance indicators (KPIs) such as process costs and lead times, as well as identify bottlenecks and estimate the impact of process changes in advance. They can quickly see the duration of each process step, where delays occur in the process, how often a process step is executed, and the cost of individual steps as well as the entire process. By varying the parameters, a wide range of use cases can be represented to develop an optimal setup without using real resources. Thanks to AI, particularly complex relationships and interactions between different process variables can be modeled, contributing to a better understanding. Overall, companies can gain a better understanding of their processes, identify risks and opportunities, and make informed decisions.

Process simulation with AI
Process mining with AI

Process mining

Artificial Intelligence can also support the analysis, visualization, and improvement of business processes in the context of process mining. One possible application is automated process discovery. AI can help automatically identify and model processes by analyzing data from various source systems (e.g., CRM or ERP systems). By analyzing log data or event logs from these sources, AI can identify patterns and relationships to visualize the process flow and identify individual steps.
Based on this data, AI can also detect deviations from defined processes by uncovering unusual activities, delays, or errors. This enables companies to identify and address potential issues in a timely manner. In addition to process deviations, AI can discover weaknesses, redundancies, and bottlenecks in business processes and provide suggestions for process optimization.
The significant advantage of AI-driven process mining is that processes can be monitored in real-time, not just analyzed after their completion. With real-time monitoring, companies can obtain up-to-date information about the process status and intervene immediately if necessary to solve problems or seize opportunities.

Process automation

Artificial Intelligence also plays an increasingly important role in the field of process automation. The use of AI in the form of software bots allows for the programming of automated sequences to execute manual, repetitive, and rule-based workflows. These digital robots independently handle tasks that would typically be performed by an employee, significantly speeding up processes, reducing costs, and minimizing errors. This also allows employees to focus on more demanding tasks and utilize human resources more effectively.
Workflows such as submitting vacation requests, processing invoice receipts, preparing employee onboarding, and reviewing purchase inquiries can all be automated using this approach. With continuous advancements and developments in the field of Artificial Intelligence and machine learning, not only simple and one-dimensional processes but also complex end-to-end processes involving multiple stakeholders, departments, and various systems can be automated - tasks that previously required human intelligence.

Process automation with AI
Intelligent decision-making with AI

Intelligent decision-making

Only a few employees are satisfied with how decisions are made in their companies. This is because significant decisions are often time-consuming and involve multiple stakeholders. AI can support complex decision-making processes by providing extensive information, simulating alternative scenarios, or suggesting optimal decisions. It processes structured and unstructured data from internal and external sources, extracting all the necessary information to identify patterns relevant to the decision-making process. This enables decision-makers to make better-informed decisions and consider potential risks or impacts.
It is even possible to automate process decisions using AI without the need for further human intervention. Based on predefined rules, patterns, or algorithms, AI can autonomously make decisions and trigger actions. The result: fewer errors and faster decision-making.

Predictive analytics

Another application area of AI includes process and risk predictions. For this purpose, historical data on process flow and outcomes are collected and analyzed to identify patterns and trends. This information is then used to make predictions about how the process will unfold in the future. This allows companies, for example, to proactively detect and address bottlenecks to avoid delays in the process flow. It also enables companies to respond more quickly to market changes and demand and adjust their processes accordingly. Overall, AI enables a proactive and forward-looking approach. Typical examples include:

  • Detect credit risks and fraudulent activities in the financial and insurance sectors.
  • Determine pricing strategies, projected sales volumes, and optimal inventory levels in supply chain management.
  • Predict when machines need to be serviced or replaced.
  • Identify potential applicants, reduce employee turnover, and increase employee engagement.
  • Detect dissatisfied customers to initiate appropriate countermeasures at an early stage.
Predictive analytics with AI

Good to know!

Regularly review the quality and availability of your data. AI systems require high-quality data to function effectively. Ensure that the data is clean, well-structured, and sufficient to provide meaningful results. Additionally, comply with all legal regulations and ensure the privacy of your employees and customers.

The advantages of AI-driven Business Process Management

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Increased productivity
With the help of AI technologies, business processes can be optimized many times over by automating repetitive and time-consuming tasks. This relieves employees from these activities, allowing them to focus on more demanding tasks.

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Enhanced quality
Artificial intelligence can ensure higher accuracy and quality in business processes. By reducing human errors and applying precise algorithms, processes are executed more reliably and consistently.

Real-time decisions
AI enables instant analysis of real-time data, allowing decisions to be made based on it. This is particularly relevant for companies that need to quickly respond to changing conditions and customer requirements.

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Full objectivity
Unlike a human, an AI can consider not only a limited amount of information but all available information. Furthermore, the AI can analyze this information base completely unbiased and independent of personal experiences and emotions.

Extensive data analysis
AI ensures advanced data analysis and processing by analyzing large amounts of structured and unstructured data, identifying patterns and correlations, and making accurate predictions. This leads to informed decisions and an improved data foundation for process management.

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Effective risk management
AI can help identify and minimize risks in business processes in a timely manner by detecting deviations and anomalies in the data. This allows companies to take proactive action and address problems early on to avoid financial or operational damages.

The future of Artificial Intelligence in the BPM environment

One thing is certain: No company can ignore AI in the long run. The potential of Artificial Intelligence for process management is significant, and we are far from reaching its limits. According to forecasts by the McKinsey Global Institute (MGI), Artificial Intelligence is even attributed with greater potential than the steam engine. Furthermore, it is predicted that AI could increase the global gross domestic product (GDP) by an average of 1.2 percentage points per year by 2030.
The continuous advancement of AI technologies and the increasing accessibility and intuitive usability indicate that more and more companies will adopt AI-driven process management. However, Artificial Intelligence will not completely replace human expertise and judgment but rather represent a powerful combination to establish long-term success in the market.

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