28 Nov, 2018· read

Really intelligent automation needs expertise

Solving Problems with People

Intelligent automation (IA) is the combination of automation and artificial intelligence (AI) designed to extend the automation of simple processes to the automation of complex business tasks; problem solving, decision-making, risk assessments and collaboration.

Problem solving is a great example of a typically human skill. It requires the experience to know which questions to ask of multiple information sources, whilst dynamically processing the answers and calculating not only the diagnosis, but also the best corrective action.

Data rarely gives the complete picture

So how does intelligent automation attempt to replicate or augment this human skill-set? There is a misconception that the AI powering intelligent automation is synonymous with data-driven machine/deep learning AI only.  Cognitive services based on deep learning AI can be very effective at processing text, natural language, images and video data and at applying predictive models generated from data.

However, when the problem domain is not entirely represented in sufficient breadth and volume of data, then the problem remains.

Expertise is a critical input

The most effective intelligent automation approach combines best practice human expertise, captured and deployed as a solution that can also consume the output of deep learning data models generated by cognitive services.

Human expertise is represented by the decisions, regulations, rules, procedures and strategies used to solve complex business problems. Once automated, this expertise can be deployed consistently, rapidly and 24/7 throughout the organisation and help preserve this corporate asset when the experts retire or leave.

Our approach to intelligent automation

We create Digital Experts; really smart software robots trained with intelligent skills to address complex business tasks like problem solving. The Intelligent skills are built on a combination of human expertise, machine/deep learning and cognitive services. We empower the business domain experts themselves to build and train Digital Experts using our low code graphical development software.

Together with our partners, we are developing a workforce of Digital Experts address common challenges in business sectors. Some examples of intelligent automation applications where the combination of expertise and data-driven AI is critical include:

  • Configuration, pricing & quotations for complex products & services in ecommerce
  • Complex task/resource allocations & sequencing
  • Complex risk monitoring in financial services and industrial plant/process
  • Cognitive chatbots supporting complex conversations with users to make recommendations, offer advice or problem trouble-shooting

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