Digitalization is sweeping business operations and increasing pressure on IT. Every business is becoming a digital business. Digital business requires speed, agility, and creativity. Successful companies deploying digitalization will awe their customers with self-service and always-available access while supporting business partners with efficient digital interactions. Everything will move faster. Without intelligent tools, staff will struggle to keep up and deliver stable operations. Workload automation (WLA) is a key part of successfully delivering digital services.
While WLA products are mature and full-featured, effectively tuning and operating thousands of jobs is still complex, and managing the management tool can be manually intensive. AI and machine learning are no longer futuristic dreams. They are maturing into real and powerful tools to solve many problems. When applied to IT operations, AI and machine learning can bring insights, predict and prevent problems, and speed decision making. Learn how you can use machine learning to automate the management of the automation tool.
Join Dan Twing, President and COO of EMA, and Jayanti Murty, Technology Evangelist, Digitate for a webinar that will leverage highlights from EMA research and discuss the impact of machine learning on managing workload automation.
- The challenges of workload automation
- The role of workload automation in digitalization
- What makes a tool a machine learning-based tool
- How machine learning can improve workload automation
- The power of Digitate's ignio for Batch, the first ever use of machine learning for workload automation