By 2026, over 75% of new enterprise applications are projected to be developed using low-code or no-code platforms. This trend addresses the growing need for rapid business process digitalization and adaptation to dynamic market conditions. For Business Process Management (BPM) systems, this signifies revolutionary changes, especially with the integration of artificial intelligence capabilities.
Evolution of BPM systems: from manual configuration to AI optimization
Traditional BPM system development often requires significant resources, lengthy development cycles, and deep technical expertise. Low-code platforms have already simplified this process, enabling business analysts and developers to create functional solutions with minimal coding. However, AI integration elevates this paradigm to a new level. AI-driven low-code platforms can automatically generate code snippets, suggest optimal process pathways, identify bottlenecks, and even predict system behavior based on historical data.
This not only accelerates initial development but also ensures continuous, real-time process optimization. For instance, AI agents can monitor task execution, detect anomalies, and propose changes to enhance efficiency, making BPM systems more flexible and adaptable.
Key advantages of AI-driven low-code for BPM
- Accelerated Development: AI tools automate routine tasks such as form generation, workflow logic creation, and system integration via API, reducing the time-to-market for new BPM solutions.
- Enhanced Quality and Reliability: AI can analyze potential errors in process design, recommend best practices, and ensure regulatory compliance, minimizing risks.
- Optimization and Adaptability: Systems with AI can learn independently from process execution data, identify inefficient steps, and suggest improvements to enhance performance without developer intervention.
- Reduced Dependency on Highly-Skilled Developers: The low-code interface, combined with AI suggestions, allows business users to actively participate in process creation and modification, reducing the burden on IT departments.
AI in BPM: use cases
Integrating AI into low-code BPM platforms opens up new opportunities for automation and optimization:
| Scenario | Description | AI Functionality |
|---|---|---|
| Intelligent task routing | Automatically assigning tasks to the most competent or available employees. | Machine learning for performance and skill analysis, workload prediction. |
| Bottleneck prediction and prevention | Identifying potential process delays before they occur. | Historical data analysis, pattern recognition, scenario modeling. |
| Automated document generation | Creating standard documents (contracts, reports) based on process data. | NLP for data extraction, generative models for text formation. |
| Resource optimization | Efficient allocation of human and technical resources for process execution. | Optimization algorithms, scheduling, simulation. |
Member company solutions and technologies
Intecracy Group members are actively developing AI-driven low-code solutions for BPM systems. InBase is the developer of the open-source low-code platform UnityBase, which serves as the foundation for numerous enterprise solutions. The Scriptum low-code BPM platform, enabling rapid business process automation, is built on this platform. Data Management IG offers advanced process automation capabilities for enterprise operations and is also involved in the implementation and support of enterprise systems in production.
Softengi, known for its expertise in custom enterprise software development, is actively integrating AI systems and AI agents, such as bidXplore, salesXplore, and solveXplore, into BPM solutions built on low-code platforms. This facilitates the creation of more intelligent and adaptive process management systems. IQusion, in turn, provides IT services and solutions for the public sector, including BPM system implementation, leveraging its experience in system integration and IT consulting to optimize processes within government institutions.
The integration of AI into low-code BPM platforms is not merely a trend but a necessity for companies aiming to remain competitive in the rapidly evolving digital landscape. Through this synergy, business process development and optimization become faster, more efficient, and more accessible, allowing organizations to focus on strategic goals and innovation.
