AI in Business-Process Reengineering

AI Magazine

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.


What is Business Process Mining (and When Do You Need It?)

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You have now started the journey of automating your business processes and have started seeing the tremendous value it brings. However this is just the beginning of the journey. Business process automation while it saves you and your end users a lot of time doesn't mean that all your processes are perfect. There is always room to improve and make your employees', customers', partners' and suppliers' lives easier. This is where Business Process Improvement comes into the picture.


Brander

AAAI Conferences

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.


The business leader's guide to robotic process automation and intelligent automation Deloitte UK

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Robot-led automation has the potential to transform today's workplace as dramatically as the machines of the Industrial Revolution changed the factory floor. Both Robotic Process Automation (RPA) and Intelligent Automation (IA) have the potential to make business processes smarter and more efficient, in very different ways. Both have significant advantages over traditional IT implementations. Robotic process automation tools are best suited for processes with repeatable, predictable interactions with IT applications. These processes typically lack the scale or value to warrant automation via IT transformation.


How to Map Out a Successful Artificial Intelligence Strategy

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A mortgage lender enables a new customer to onboard for a loan from his mobile device. An insurance customer submits and manages a claim via her smart device with swipes and clicks instead of manually inputting data. A transportation carrier manages all its invoices, bills of lading and customs documents digitally, transforming that data into a single pane of glass to optimize routes, inventory, schedules and closing out loads. All of these examples were the result of artificial intelligence (AI) projects that went right, said Anthony Macciola, chief innovation officer for ABBYY. Content was digitized, and unstructured data was transformed into structured actionable information and automated into various business processes.