Conversational RPA: What Is It?
The future is already here—it’s just not very evenly distributed.
—William Gibson, science fiction author
The roots of Robotic Process Automation (RPA) go back to the early 2000s. Pioneers of this industry, such as Blue Prism, focused on screen-scraping to help automate Windows desktop applications. Because the technology was fairly rudimentary, little attention was paid to RPA. Nowadays, AI-driven RPA has made huge strides in driving immense business growth.
Yet, growth continued, especially when UIPath came onto the scene. The founder and CEO, Daniel Dines, realized that enterprise automation software was woefully inadequate. The option of Business Process Outsourcing (BPO) was also showing its limitations. So Dines built a platform that made it easier to focus on automating discrete tasks relatively quickly—say in a couple of months—by using drag-and-drop workflows to create bots.
The market exploded, as did the growth of UiPath. One of the company’s investors, Sequoia, noted that this was the fastest-growing enterprise software company ever.
But despite all the success, the RPA market still has problems. And this has opened up even more opportunities for new approaches and innovations.
One that holds much promise is Conversational RPA. It’s really about the next generation of this industry—and the market is certainly ready for it.
What then is AI-Driven RPA and Conversational RPA? Let’s take a look:
Cloud-Native Software: Because the RPA industry is maturing, the technology stack has lagged. Much of the core software remains on Windows/.Net infrastructure. While there are often cloud components, such as with orchestration, the tools are often on-premises.
However, this presents some nagging problems. For example, it can be nearly impossible to capture enough data for important efforts like analytics and AI. Next, as RPA vendors come out with new versions of their software, the maintenance can be a challenge.
Conversational RPA, on the other hand, is cloud-native. From inception, the architecture allows for complete data visibility and seamless management of the bots. This means that enterprises can gain ongoing insights about what’s happening without having to deal with the hassles of new versions conflicting with older workflows.
Delightful User Experience: In the enterprise software world, there is lots of talk about consumer-like interfaces. But this is still mostly talk, including among traditional RPA vendors.
Yet, creating rich experiences in the software can be just as important as the underlying features. Let’s face it, people have become accustomed to standout apps like Uber, Instagram, and Snap.
With AI-driven RPA and Conversational RPA, a key priority is making sure there is a superior user experience. That demands a natural, human-like interface that allows for performing duties, tasks, IT workflows, and business workflows. All this must be done in as few steps as possible and enable seamless access to any kind of web service.
An example of the power of the user experience is Slack (then again, the company was originally an online game!). The company founder, Stewart Butterfield (who, by the way, has an undergraduate degree in philosophy), was able to bring a much different perspective to collaboration software. He has also been relentless with customer feedback.
“We will take user feedback any way we can get it,” says Butterfield. “In the app, we include a command that people can use to send us feedback. We have a help button that people can use to submit support tickets.”
AI: Yes, this is quite buzzy. But with RPA, AI has the potential to move the needle in a big way. The reason is simple: RPA involves a huge number of keystrokes. This data can then be turned into valuable insights.
As for Conversational RPA, the opportunities involve use applications such as virtual assistants and smart collaboration tools for both employees and customers. All these tools should be out-of-the-box, which will help with adoption across the organization. The fact is that most people will not have time to learn sophisticated algorithms and data models.
For the most part, Conversational RPA is about delivering greater self-service, but also improving productivity while driving down costs. This means having proactive notifications when tasks are completed or have failed or stalled. It also leverages self-learning to expedite complex challenges like cloud and application integrations, compliance, and audit-trail creation.
Bottom Line
It’s certainly the case that RPA has accomplished much. The top players in the industry have been smart to focus on customer success.
But again, there are lingering issues and challenges. If anything, the main vendors have been caught in a classic innovator’s dilemma, as it will be incredibly difficult to retool their technology stacks.
Because of this, it will be startups that trailblaze the next generation of the industry. Customers want something that is much smarter and easier to use. And it’s Conversational RPA that will meet these demands.