Intelligent Automation has become one of those “all encapsulating” buzzwords, claiming to deliver everything from scale to better performance & operations. Unfortunately, relying on search engines to understand its meaning may leave you rather confused. Some would call it ‘an advanced form of RPA (Robotic Process Automation)’, while others use it interchangeably with the term ‘digital transformation’. So, let’s ignore the jargon for now and understand what it really means? And more importantly, how your business can benefit from it?
What is Intelligent Automation?
Simply put, intelligent automation is a combination of Artificial Intelligence (AI), Robotic Process Automation (RPA), and Process Orchestration. It offers a comprehensive, end-to-end solution to undertake digital transformation. It is not a stand-alone process, instead, it comprises of various interconnected technologies, organising work across human-robot teams.
Below is a break-down of the key components that make up intelligent automation.
Components of Intelligent Automation
Business Process Management (BPM)
Business Process Management is the orchestration of end-to-end data-driven and function-driven business processes. This encompasses the efficient coordination of people, collecting data, preparing data, and decision-making based on the data. BPM takes a holistic and structured approach to optimise repetitive tasks. It does so by bringing human and automated tasks into a managed sequence of steps. Automation fits in BPM when business processes are analysed and re-engineered to introduce elements of automation at different interaction points to replace human tasks or make them efficient.
Robotic Process Automation (RPA)
This is a software-based technology, not physical robots, that focuses on automating repetitive tasks to reduce human intervention in computer applications. By replacing simple tasks such as data entry, it allows employees to work on more important jobs that require decision-making and building customer relations. Examples are filling online forms, scanning and recognising human-written documents, etc.
Artificial Intelligence (AI) and Machine Learning (ML)
Artificial Intelligence is the simulation of human intelligence by machines. Some of the common virtues of AI in the current business environment are sequence labelling, pattern recognition, intelligent decision-making, Natural Language Processing (NLP), chatbots, and sentiment analysis. Machine Learning allows software algorithms to learn from human actions and mimic them intelligently by automatically contextualising the tasks.
Integration involves orchestrating processes carried out by human and robot teams. Like traditional Integration, Integration as part of IA also involves bringing together all enterprise data, systems, legacy, and front-end applications. However, compared to traditional integration, it is considerably straightforward, flexible, and agile. It comprises of a series of Cloud and on-premise based API connectors that use AI and ML to enhance the power of workflows. An example is an intelligent chatbot that can leverage APIs to do tasks requested by the user such as fetching the outstanding balance or looking up upcoming trips.
How does Intelligent Automation work?
Let’s now understand the role of each component in the overall lifecycle of IA.
Unlike conventional automation that relies on structured data inputs, IA starts with process discovery using AI-based tools. It takes inputs in the form of unstructured data such as work activities, human chat conversations, audio, and video files. Since such unstructured data makes up a large proportion of all business data, the ability to process it is critical for end-to-end automation.
It then analyses the data, identifies an optimal workflow, and proposes automation. IA is a self-adjusting process that allows end-to-end automation of any business process. With time, the need for intervention and management reduces.
What are the Business Objectives of Intelligent Automation?
The key objectives of Intelligent Automation are to:
- Enhance customer and employee experience
- Increase productivity through increased speed of processing
- Save time and costs (by streamlining processes, automating repetitive tasks, and reducing human intervention)
- Improve quality and reduce errors
Applications of Intelligent Automation
On your digital transformation journey, Intelligent Automation helps you avoid turbulence and safely reach your automation goals. Not surprisingly, the applications of Intelligent Automation are many. A few of the many effective uses of IA are below:
IA amalgamates human and bot teams to fill the gaps created by relying on a range of tools and/or overworked personnel. It thereby creates a more sustainable, smoothly running system.
Examples of processes automated using IA
An increasing number of organisations are already integrating a wholesome architecture of IA for their day-to-day operations. Luckily, it’s not too late to jump on the bandwagon because clearly it is here to stay. I have listed a few examples below of how organisations are using IA across the world:
A retail chain uses RPA to collect more information on customer calls and decrease the time taken for first-time resolution (FTR). As a result, the customer service agents of this organisation are able to spend more time sharing special offers and deals, to improve relations and in turn, grow the business.
A banking major is using Intelligent Automation strengthened with Machine Learning (ML) to analyse encrypted traffic and detect malware, helping to improve network accuracy and security.
Used in a different capacity, these make it easier to effectively manage compliance requirements and enhance audit-promptness with safety laws and regulations. As more data is gathered, over time, the system can optimise and continuously improve the accuracy of end-to-end processes.
An insurance conglomerate uses predictive analytics to help insurers assess past insurance claims and prevent future accidents.
Chatbots, one of the earliest implementations of IA, are being used by almost all enterprises today to help ease the workload of their sales and marketing teams. Chatbots interpret (unstructured) data in the form of text or voice questions and display user-specific, contextual answers.
Large Telcos today use software bots to perform routine maintenance tasks in a more scalable and consistent manner.
How you decide to adopt IA is entirely upto you. The important point is to get started! There are various factors that you would need to keep in mind when you set out to implement Intelligent Automation for your enterprise. These include the size of your organisation, your budget, and most importantly, your business priorities.
Choosing the right platform to set up Intelligent Automation is critical
Are you ready to enhance your org chart by bringing in bots as co-workers?
Torry Harris’s enthusiastic team of automation experts and bots(!) will be happy to assist you through each step of your business’ digital transformation journey. We will critically assess the process and technology readiness of your business to develop automation workflows that are best suited to your needs.
- Start with process discovery and redesign
- Use advanced analytics, identify optimal workflows and implement recommended automation
- Let the systems learn and adapt to data in real-time using AI-based tools
Category : Automation
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