Transitioning from RPA to IA

By Jon Walden

Chief Technology Officer and VP Sales Strategy Officer

SS&C Blue Prism

August 15, 2022


Transitioning from RPA to IA

Even as more businesses than ever embrace Robotic Process Automation (RPA), already we’re seeing a shift in the industry to something new: Intelligent Automation (IA), which builds on the successes of RPA and adds new technologies that result in digital workers who can think, learn, and collaborate in real-time with their human co-workers.

RPA and IA. What’s The Difference?

So, how do these two critical tools differ? Traditional RPA is a rules-based technology that interacts with structured data, such as moving data from one system to another.

On the other hand, Intelligent Automation builds on RPA by layering it with advanced technologies such as artificial intelligence, prescriptive analytics, intelligent document processing, and process & task mining. This allows for data-driven processes using unstructured data, such as evaluating a car accident insurance claim by analyzing and classifying images and making decisions or recommendations on the claim outcome.

While it may not seem like it, this is a significant shift. RPA focuses on information worker tasks that involve accessing, transferring, and manipulating perfect data sets for a fixed set of outcomes. IA shifts this to automating or augmenting knowledge worker tasks and can make decisions based on imperfect information with variable outcomes. In short, IA is just smarter about the work it is asked to do.

Think of it another way: RPA was like one of those off Choose Your Own Adventure Books. Yes, there were decision branches and varied outcomes, but they were a fixed number. You weren’t going to simply break out of the decision path and write your own ending.

With IA, you can. IA can handle decision trees that expand exponentially with every new variable and probabilistic modes of operation powered by deep neural networks that can balance many different variables for an optimum outcome. IA uses machine learning to combine interactional, transactional, financial, and operational data sources to provide insights and segment, profile, and make decisions.

Finally, while RPA digital workers usually work separately from human workers, IA digital workers are effectively colleagues. You just can’t get coffee with them.

What are the Technologies Powering Intelligent Automation?

Machine learning, in particular deep learning, is what powers IA. Deep learning uses digital neurons and synapses— similar to how human brains operate. These networks enable digital workers to see using computer vision, understand language through natural language processes, and talk back through natural language generation. Process synthesis allows them to understand a business’s procedures and understand human colleagues through affective computing, which can simulate empathy.

What Changes When We Embrace IA?

IA and its underlying technologies are supremely powerful. Through process and task mining, IA can automatically discover and assess what is working in a company’s procedures and what isn’t. It can work with existing legacy systems by analyzing their infrastructure and software, and recommend best practices for easy integration.

IA allows for fly-by-wire management and auto-scaling of workforces, both digital and human, to expand or shrink to meet demand. And it will enable human and digital worker collaboration on processes and tasks.

And these IA-generated processes and systems? They can self-heal and self-manage with intelligent automation.

What’s the Impact on People?

It changes information workers, who extract data and shift it from one system to another, to knowledge workers augmented by automation, who can focus their time on high-value interactions with customers, leveraging their creativity to solve problems and create new and better services and products.

Secondly, it allows for greater flexibility in the workplace for human workers. There is less emphasis on being in the office and more concern for mental and emotional health. IA systems, if coded properly, can also cut down on discrimination that many human hiring managers may not even be aware they’re perpetuating.

What’s the Practical Effect?

By eliminating rote tasks and making space for human creativity, we firmly believe IA makes for a happier and more productive workforce. That, in turn, makes for more satisfied customers who benefit from high-tech, high-touch interactions.

We believe IA can lead to new products and services getting to market faster, thanks to the ability to reconfigure systems using IA quickly. We also think IA can create more value in a business model by analyzing and extracting value from parts of a business that might not evolve quickly enough because data is locked away in information silos. That boils down to increased revenue and growth, and a flexible workforce that can expand or contract to meet real-time demand.

You Sold Me. What Should I Do Now?

First, realize that IA is a strategic imperative, not a quick, tactical fix. As an executive, you need to articulate the vision, prioritize the execution of that vision, and then actually do it—before your competitors do the same.

You’ll need to level with your human workforce to foster trust and accountability and get buy-in from them on the big changes coming. It would help if you also planned to invest in your human worker’s existing skillset. This is especially important for skills that highlight what humans do best: compassion, emotional intelligence, high-level customer service, managing complexity across multiple fields of expertise, improvising, and making decisions without all the data.

Then, get your human employees to reimagine their processes so that IA can build and improve on them. The goal should be to improve quality, manage complexity, and build stronger customer connections.


RPA was revolutionary, but IA is going to be even more so. Through it, businesses will achieve more efficiency and productivity than ever before, as it changes how information workers interact with data and customers. With the right investment in human worker skillsets and buy-in from your employees, you can use IA to create more value in your business model and increase revenue growth.

Jon Walden is Chief Technology Officer and VP Sales Strategy Officer, Americas, at SS&C Blue Prism.