Here's how intelligent automation minimizes the manual "legwork" and ramps up your team's ability to focus on high-level strategy.
Intelligent automation is the use of automation technologies and artificial intelligence that anticipates the needs of users and customers, which brings organizations closer to achieving their digital transformation goals. As a result, organizations and their employees are able to focus on high-value tasks that develop human connections for a more meaningful experience at both the customer and employee level.
According to global research firm IDC, intelligent automation is a key component of the future workspace where content and content-centric workflows are instantly accessible regardless of location. This enables secure collaboration and contribution that leads to overall benefits in cost savings, productivity, collaboration and operational workflow.
Intelligent automation combines several key technologies like robotic process automation, machine learning, business process automation, intelligent routing and natural language processing, to name a few. These technologies are interconnected and are part of a broader, strategic, well-funded digital transformation plan.
Intelligent capture identifies and extracts information from documents automatically — whether in paper or digital format. It uses a combination of optical character recognition (OCR), intelligent character recognition, optical mark recognition and barcode recognition to capture structured or unstructured data.
Workflow automation is software that defines a series of tasks based on a process and automatically acts on those tasks without the need for human intervention or manual steps. It is part of the larger business process management solution that optimizes business processes and provides real-time visibility for informed decision-making and better business insights.
Machine learning is a branch of artificial intelligence where systems learn from data, patterns and inference to act on unanticipated variations with minimal human intervention. These machine learning systems are able to autonomously continue their learning over time. Some examples of how machine learning is used in various industries are fraud detection in banking, disease diagnosis in healthcare and invoice processing in accounts payable.
Robotic process automation allows organizations to automate tasks performed on applications and systems that are repetitive with little variance. It is relatively fast and easy to integrate into existing IT architecture with immediate benefits such as reducing manual tasks, eliminating data entry errors and improving turnaround time.
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How should you choose the right automation tools for your organization’s needs and goals? Start with insights from advisory firm Deep Analysis, including types of automation tools and their differences, seven steps to deciding which automation tools to use and how leading companies approach their automation initiatives.
Automation is everywhere. It’s time to put it to work for you.
According to a study conducted by Forrester Consulting and commissioned by Hyland, decision makers are looking to intelligent automation to power their business forward in terms of efficiency, customer experience and improved innovation.
For example, in terms of content related tasks, respondents to the study say they expect to, or have already seen great advancement in these areas:
> Read more | 24 stats that will change the way you think about managing content
In this regard, intelligent automation benefits businesses by:
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