Thursday, 13th August 2020

RPA: a small yet giant step in the ‘Intelligent’ Automation Journey

There’s no question, AI is set to revolutionise society as we know it. We’ll see unprecedented developments in the public sector and medicine and we’ll realise drastic improvements in the way we do business. Most businesses are now fully aware of the need to start embracing intelligent automation for competitive advantage and are looking long-term at how different forms of artificial intelligence (AI) will impact their market. By Amyn Jaffer, Head of Intelligent Automation, Ultima.

But it’s important to build your Intelligent Automation capability in incremental steps so that you can propagate a culture of Intelligent Automation over time. As RPA (robotic process automation) continues to gain pace in UK businesses recent industry successes make this a good place to start your journey to fully embrace AI. RPA is the process of using software robots to automate mundane, repetitive tasks. Once these are automated, companies can look at moving to more complex AI-based automation – using visual and cognitive intelligence to deliver more advanced automation that draws information from multiple sources and interprets it to deliver improved business intelligence.

Right now, even SMEs can start to automate business processes using software robots as there are now RPA offerings that use software robots as part of a SaaS offering. This makes them affordable as well as effective. Combined with Artificial Intelligence-based technologies, the use cases for process automation are even wider, and provide even greater returns for both enterprises and SMEs.

In HR, for example, RPA can be used to ensure each department has the same information about each employee without the typical challenges of multiple system records and repetitive re-entry of information. It can also be used for absence management and for processing applications saving time for your employees to focus on more strategic work. As a second phase, organisations can then make HR information more accessible by implementing chatbots.

RPA can be used to simplify the process of reporting on credit for thousands of customers. The information required to produce credit reports for one retailer involved accessing data on an inefficient, legacy mainframe system. Using an RPA ‘virtual worker’ that was able to precisely imitate a human producing one of these reports, the retailer reduced reporting time by 91% creating savings of over £100k.

For a manufacturing company it was taking an unacceptable 1.5 days to deliver key customer service reports. They wanted to find a technological solution to expand and improve their services, without increasing costs. By using a ‘virtual workforce’, reports that previously took this company 1.5 days, are now produced in a mere 6 minutes - a 300% increase in productivity.

At Ultima, we have been using RPA technology to automate our own back-end operations and we’ve seen productivity rise by a factor of two since implementing the technology across five processes. For example, we automated our forecasting and planning tasks. Software robots collate real-time sales and marketing information and process all the information they collect during the day to produce detailed forecasts and business intelligence for the next morning. Usually this took eight to ten hours per day of staff time. As a result, the business has improved business intelligence to plan with, and staff have more time to spend on customer service and strategic thinking.

Adding another layer of intelligence – AI and cognitive computing

Once a company has automated its basic tasks it can move on to using more intelligent cognitive services to enable a greater degree of automation and further maximise return on investment. For example, by using cognitive services such as text and sentiment analysis and optical or image character recognition, enterprises can look at processing and effectively responding to natural language text within various formats including emails, documents, PDFs and live webchats. Data can be extracted from these without needing to hand over to a human.

Contact centres, for example, are simplifying the service agent process with the automation of tasks, and the introduction of Natural Language Processing (NLP) for extracting key information from emails and messaging chats, so their agents are now able to focus on providing the best experience for customers. One client is using speech recognition software to answer the phone and respond automatically to customers once the software robot has analysed the call and sourced the correct information to help the caller.

Vision is another good example where cognitive services can be used to improve business efficiency. One company is using vision recognition services to tag information in photographs then store it in a database under relevant categories. Normally this would take hundreds of man-hours to do, but with cognitive services it takes seconds.

The holy grail of AI

Once these processes are in place and data is being collected and stored in intelligent ways, companies can start to use more sophisticated AI to mine their data and start to ask questions of their structured and unstructured data that will deliver unique business insights. Eventually, it’s likely we will all have a ‘virtual worker’ by our sides helping us do our jobs, freeing us up to be creative and driving business innovation. What AI is capable of will continue to develop and our journeys to digital transformation will advance over many months and years. But in order for it to move forwards at all the right foundations need to be in place; only then will you be able to use AI to transform and maintain your competitive edge.


Robotic process automation (RPA) is the use of software and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform them. These tasks can include queries, calculations and maintenance of records and transactions.

Intelligent automation or Intelligent Process Automation (IPA) is a more advanced form of what is commonly known as robotic process automation (RPA). Any large-scale activities or groups of repetitive tasks that draw on or feed information to multiple systems is an intelligent automation candidate. It often refers to the application of Artificial Intelligence and related new technologies, including Computer Vision, Cognitive Automation and Machine Learning to RPA.

Artificial intelligence (AI) is an area of computer science that emphasises the creation of intelligent machines that work and react like humans. It is a very broad term for a wide range of technologies and capabilities which can have a profound impact on organisations in any vertical.

Amyn Jaffer bio

Amyn Jaffer, Head of Intelligent Automation, Ultima is a proven and experienced architect and technical design authority who has in-depth understanding of end-user requirements and experience in a wide range of transformative technologies.

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