Maximum system performance with minimal friction
Imagine a drive where repetitive processes are handled automatically and critical systems work together smoothly. Error rates are significantly reduced and technical teams can focus on optimizing platforms, future-proof architecture and ensuring scalability.
Companies with a high degree of process automation report up to 30% fewer manual errors and often achieve an ROI of 200% within the first year (McKinsey, 2023).
Robustness and scalability in focus
Automation has become a strategic tool for maintaining stable system operations, ensuring integration and accelerating technical development. Here is seven key trends, which shapes tomorrow's technological setup.
Automation as a lever for system optimization
Organizations rolling out automation across infrastructure and applications experience up to 40% higher efficiency. Especially when integrating with legacy systems, bottlenecks can be eliminated without the risk of breakdowns.
Response time and capacity under pressure
Companies are using automation in response to a lack of specialists and increasing need for uptime. 78% invest in RPA to maintain operations, while 85% use it to reduce technical waste and improve time-to-resolution.
Technology management and RPA as a tool in governance
90% of IT managers or technical managers find that their responsibilities are extended to ESG, data management and organizational agility. Automation is central to maintaining compliance and providing stable services across departments.
Process mining and test automation as operational assurance
82% of decision makers list process mining as the key to reliable automation projects. When bottlenecks and deviations are identified early, testing and deployment can be standardized and accelerated.
Low-code for rapid development and decentralized innovation
Low-code allows for supporting technical decentralization without compromising control. It reduces development costs and minimizes reliance on key teams.
AI and RPA integrate and create intelligent workflows
By connecting NLP, OCR and machine learning directly with automation, new possibilities arise: e.g. intelligent e-mail routing, validation of documentation and data extraction – all with a focus on performance and scaling.
New technology profiles and changed competence requirements
Automation creates a need for new roles with a focus on system monitoring, data validation and setting up robotic processes. Technology management must ensure that recruitment and skills development match the speed of development.
