Using artificial intelligence to increase productivity

Introducing new solutions is challenging, but necessary for digital transformation, says Blue Prism’s Paula Liebergen. That’s why the company has integrated with Microsoft AI to add key skills for intelligent automation to its Digital Workforce solution

By Guest on 31 December 2018
Using  artificial intelligence to increase productivity

This article was originally published in the Autumn 2018 issue of The Record.

Blue Prism has identified six key skills for automating complex processes and operational efficiency. These essential best practice building blocks include: 

1. Knowledge and insight: Our robots can harvest information from different data sources, understand it, and deliver previously unreachable insights to support business outcomes and complete tasks that have traditionally required manual processing because of the cognitive skills required. Examples include the natural language processing, language understanding and translation functions within Microsoft Cognitive Services; email processing; or insights from real-time data analytics.

2. Visual perception: The ability to read, understand, and contextualise visual information digitally is another critical skill for automation. Our integration with optical character recognition tools and Microsoft’s computer vision services means that digital workers can identify objects within an image and apply contextual knowledge bases to determine an appropriate action.

3. Learning: With the ability to adapt to changing process patterns and derive contextual meaning from data sets, digital workers can recognise changes and adapt accordingly via Microsoft machine learning technologies, process information with a neural network paradigm and quickly model algorithms – in real time and at scale.

4. Planning and sequencing: Identifying opportunities and planning workflow and workload execution lets enterprises deliver the best outcomes. Blue Prism robots can apply if/then logic to workflows, identify the ideal order of steps, conduct tasks at optimal times of day, and schedule work based on existing conditions. Examples include using process mining to analyse processes based on event logs, and instantly and intelligently scaling workloads needed. 

5. Problem solving: Complex operational processes with exceptions, variables and diverging paths usually require a human being’s problem-solving capabilities. Our digital workforce solution can identify the context of variables and solve logic, business, and system problems without intervention. Examples include using visualisation to get insights from data, as well as integrating business process management and security solutions within a robotic process automation (RPA) process.

6. Collaboration: Finally, digital workers need to be able to communicate, work with and complete tasks with people, systems, and other software robots. Examples include deploying chatbots within an RPA process to autonomously service customers, escalating to humans when needed.

Blue Prism’s Digital Workforce works with people to increase productivity, improve overall customer experience and deliver true operational agility. Together, Blue Prism and Microsoft offer great potential for business leaders looking to drive innovation while also successfully managing the modern enterprise. 

Paula Liebergen is Microsoft Alliance director at Blue Prism


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