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AI and Intelligent Process Automation are real and businesses leveraging them
Many organizations implement their project by assuming that AI can tell them what the right answer that lies within a large data pool when it comes to unstructured content.

By
Apac CIOOutlook | Wednesday, May 15, 2019
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While scope for application of AI is still being explored these days, there are many examples of businesses which have started to gain real traction behind the scenes by applying AI to automate manual, back-office business processes.
At some instances, referred to as Intelligent Process Automation (IPA), most of the back-office cases primarily includes manual, document-based workflows such as contract analytics, audit planning and reporting, customer support analysis and automation, assessment and claims analysis. Rather than following simple task-based automation to perform all these cases, there is a requirement of AI-based decision making to augment the workflow.
In most of the times a lot of AI initiatives that begin as discovery projects without any real business outcome in mind. While implementing AI initiatives to gain real outcomes, enterprises need to consider the following key points.
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Be realistic about the capabilities of AI
Many organizations implement their project by assuming that AI can tell them what the right answer that lies within a large data pool when it comes to unstructured content. In reality, AI is great at finding out what exactly matches to an already defined and desired state by recommending the further steps.
Make sure to have access for the right data
For an enterprise, it doesn't necessarily have to be a lot of illustrations to get access for right data, but there is a need for a business to get clear idea about AI initiatives that can give right insights against a larger set of data.
Ensure a common understanding
The broad application of AI technology and smart process automation is still in early days. Before an enterprise is going to apply AI to automate business process, it is important to initiate with a common understanding of the different steps in a process. Use scientific method to identify the traction with different business processes and continue to build on the value to deliver the real business outcomes.
As many disruptive competitors are employing data-driven decision making and digital approaches to take markets into new directions, most of the existing companies need to increase their capabilities in driving the automation in their business processes to acquire the benefits.
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