Intelligent automation: where RPA meets AI

In the pursuit of greater efficiency amidst steady growth and stiff competition, many organizations have adopted a variety of digital technologies to improve the way they operate. It remains evident that at some point, they will need solutions that didn’t require that much human input and could carry out certain tasks based on predetermined instructions.

This mentality saw the rise of solutions in the realms of robotic process automation (RPA) and artificial intelligence (AI). With RPA, organizations have been able to put in place configurations for computer software, packaged as robots, to retrieve and process data while also interacting with other programs in order to produce a desired result. And AI can analyze data and make decisions or recommendations.

The benefits of both RPA and AI are well-documented, and both technologies reduce the reliance on humans for every task. With that in mind, RPA and AI are complementary solutions that open even more possibilities when they work together as intelligent automation. 

What is Intelligent Automation?

Intelligent automation is a fusion of various technologies including RPA and AI to achieve a more holistic digital workflow that transcends the individual capabilities of each of these techniques. Think of it like this: if RPA enables you to automate tasks and processes, intelligent automation brings a decision-making element to the table. 

By incorporating AI with RPA, the robots can make decisions as well as or even better than a human could. Intelligent automation aims to take care of those parts of the workflow that require more creativity and human judgment. Intelligent automation also creates a generally smarter workflow where patterns are identified, lessons are drawn from them, and those lessons are used to improve processes with as little human input as possible.

The major Intelligent Automation components

Process orchestration

This part largely deals with data-driven processes and involves the automation of various stages, which include gathering and organizing the data, deriving insights from it and acting on those insights. For example, employee performance data can be drawn from a particular department’s systems and converged in one place.

Here, decisions such as updating each employee’s record and erasing earlier versions can be made, along with giving each employee a score/rank based on specified criteria. After this stage, instead of a human being coming in to administer rewards, the reward process can be handled automatically in accordance with the scores given.

Robotic Process Automation (RPA)

RPA is quite useful when utilizing computer programs for tasks that are significantly monotonous irrespective of the number of times they are repeated. RPA leans more towards commands at the secondary layers of software or the user interface level rather than the core machine language or code.

Using RPA tools can feel more like mapping out a conventional flowchart and this automation can be further simplified by features that capture actions on screen and keystrokes. The resultant presets can be tested and categorized according to the tasks they automate, then stored as collections also known as object libraries, with room for additional customization before reuse.

Artificial Intelligence (AI) and Machine Learning (ML)

With these components, the goal is to embed cognitive abilities within your systems so they can operate as if they were being fed live instructions by a human being. Another goal here is to create a training routine for these systems by having them set up to receive information and learn from it in order to get better at how they execute different tasks.

This may include fostering techniques like pattern spotting, marking sequences, natural language processing, and sentiment analysis among others.

How can Intelligent Automation benefit businesses?

Applying intelligent automation benefits businesses in a number of ways such as:

• Reduction in full-time equivalent (FTE) costs since some employees end up working less hours as more tasks are delegated to computers.
• Improved data integrity as digital systems get better at detecting errors or inconsistencies and correcting them.
• Greater adaptability to changing customer needs due to the predictive abilities within intelligent automation and the handling of large workloads in a shorter time.
• More personalized interactions and ultimately, better experiences and overall customer satisfaction.

How to ease your way into Intelligent Automation

There are at least five major steps to take when trying to introduce intelligent automation into an organization and these include:

Pinpointing automation opportunities. This will involve identifying processes that can benefit from automation, choosing the ones that can be used as a trial, engaging with the relevant stakeholders, and anticipating the impact of a trial.

Establishing organizational goals. In this step, you’ll have to lay out the problems you’re facing, envision the benefits of automation, determine the relationship between your challenges and anticipated benefits, list all the metrics to follow when tracking progress and plan on how to redirect resources after automation.

Deducing the ideal mode of operation. Here, the objective is to examine the unique aspects of your organization’s structure, put together a team and settle on a framework within which automation will happen, along with choosing who’ll be responsible for monitoring the use of bots and other tools.

Selecting partners. This part entails listing prominent vendors in the automation space, zeroing in on those who are best tailored to your organization’s needs, evaluating the different sourcing options available and choosing a pricing plan that doesn’t erode your desired ROI.

Developing a roadmap. In this case, you’ll have to plot your automation journey by establishing priority areas, aligning them with the availability of funds and other resources, setting their respective milestones and attaching timelines to them.

All this may seem like a lot and you might be wondering which way to go. Whether it’s intelligent automation vs RPA, implementing basic AI and ML, or some other custom hybrid of the various techniques and sub-techniques mentioned above, it pays to have a well-versed automation partner on your side. Try out Robocorp for a more flexible approach to automation.

Gerald Ainomugisha is a freelance Content Solutions Provider (CSP) offering both content and copy writing services for businesses of all kinds, especially in the niches of management, marketing and technologyGerald Ainomugisha is a freelance Content Solutions Provider (CSP) offering both content and copy writing services for businesses of all kinds, especially in the niches of management, marketing and technology