AI and RPA: How data and risks define automation success
Integrating AI into RPA is transforming business processes, but success hinges on data readiness and effective risk management. Prepare your data.
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45 publications
Integrating AI into RPA is transforming business processes, but success hinges on data readiness and effective risk management. Prepare your data.
Platform Engineering and IDP are transforming development, optimizing cloud costs, and enhancing security amidst increasing infrastructure complexity.
Domain-specific AI models are becoming a key tool for modernizing enterprise applications in 2026-2027, overcoming legacy system limitations.
Integrating AI policies into API Gateways is critical for proactive microservice protection in 2027, countering cyber threats and AI-related risks.
Integrating Megapolis.DocNet with eSud optimizes business processes and interaction with government bodies, enabling the phasing out of outdated ECM systems.
Phased migration of legacy ERP systems in the public sector helps avoid downtime and ensures process continuity by focusing on automation and data.
Is new system integration taking months? AI in API Gateways ensures microservices security and scalability, reducing time-to-market.
AI analytics is transforming master data management (MDM) in 2026, ensuring accuracy and efficiency in enterprise system integration.
Industrial IoT and SCADA systems are transforming manufacturing. We examine the key trends for 2026: AI, cybersecurity, cloud solutions, and integration.
Industrial IoT and SCADA: key trends for 2026. Integration of AI, cloud solutions, and cybersecurity for manufacturing automation.
AI-driven Scriptum is set to transform document management and workflow automation by 2026, accelerating document processing and business process automation.
By 2026, over 80% of large enterprises will leverage a combination of RPA and low-code platforms to optimize business processes. This approach accelerates development time and enhances automation efficiency.