Business-process reengineering (BPR) is a generic term covering a variety of perspectives on how to change organizations. There are at least two distinct roles for AI in BPR. One role is as an enabling technology for reengineered processes. A second, less common but potentially important role is in tools to support the change process itself.
Brander, Simon (University of Applied Sciences Northwestern Switzerland FHNW) | Hinkelmann, Knut (University of Applied Sciences Northwestern Switzerland FHNW) | Martin, Andreas (University of Applied Sciences Northwestern Switzerland FHNW) | Thoenssen, Barbara (University of Applied Sciences Northwestern Switzerland FHNW)
Organizational agility is a key challenge in today's business world. The Knowledge-Intensive Service Support approach tackles agility by combining process modeling and business rules. In the paper at hand, we present five approaches of process mining that could further increase the agility of processes by improving an existing process model.
Robotic Process Automation (RPA) accelerates the digital transformation of business processes by automatically replicating tedious actions that have no added value. SAP Intelligent Robotic Process Automation is a complete automation suite where software robots are designed to mimic humans by replacing manual clicks, interpreting text-heavy communications, or making process suggestions to end users for definable and repeatable business processes. The course will give an introduction to RPA as an industry standard, introduce the SAP solution with its individual cloud and on-premise components, show an example of an automated scenario with SAP Intelligent RPA, and explain the business value of the solution as well as key differentiators. After attending this course, participants will be able to understand what RPA is and how the SAP solution functions. Moreover, they'll learn how to rate use cases for RPA and understand the value of it for today's businesses.
It is a fact that businesses built with a digital core tend to outperform those with a traditional operating model. According to research by McKinsey, digitally driven organisations are more profitable than their industry competitors. It is therefore no surprise that adoption of emerging technologies such as Robotic Process Automaton (RPA) and Artificial Intelligence (AI) is on the rise. A recent survey by Gartner found that 37 per cent of global companies have now implemented AI in some form and that the number of enterprises utilising AI has increased by 270 per cent over the past four years. Rather than relying on traditional business processes being operated by office workers, managers, engineers, advisors and customer service reps, a growing number of organisations now depend on digital workers, automation and AI to run their core business processes.
"Accurate automation could be the intensity of the intelligence", that's what we believe the definition of the artificial intelligence. Through this thumb criteria we could able to develop the superlative, ARTIFICIAL INTELLIGENCE enables enterprise application which would help to stabilize the business process with smooth operation and as an outcome growth could be achieved through the understanding of the in and out of the business reading ARTIFICIAL INTELLIGENCE enabled analytical data. We have been talking about Artificial intelligence for a long time but why now only ARTIFICIAL INTELLIGENCE era coming into the technical industries. I believe that because of the stability in the Business Process, Strong enough data process methodology and high-tech servers to process the infinite data in a fraction of seconds and digitization in the business industry. Ultimate we have the readiness to utilize the ARTIFICIAL INTELLIGENCE technology since we do have a readiness of the business strategy and technical capabilities.