AIbyRPACIOs and business leaders alike have tremendous interest in utilizing artificial intelligence (AI) for their companies for a variety of applications. For instance, applying AI to customer data can help decision makers to quickly identify and act on shifts in customer behavior.

Meanwhile, AI can also be used to identify opportunities to streamline operations within a company to help make processes more efficient. This includes the use of virtual assistants that can address customer questions in a customer service setting.

Despite these opportunities, many organizations are struggling to put AI into production for a variety of reasons. This includes a lack of adequate skills and challenges associated with integrating AI into existing applications.

This helps explain why fewer than 10% of companies that are using AI have fully put it into operation with their business processes or have enterprise-wide strategies in place, according to a study by CCS Insight.

One of the hottest technologies gaining widespread adoption among companies to address these challenges is robotic process automation (RPA). RPA involves the use of software robots to automate repetitive, labor-intensive rules-based processes in order to free up employees to spend more time to work with customers and other higher-value cognitive activities.

UiPath is the market leader in the RPA space, having recently garnered a $7 billion valuation thanks to its meteoric growth. The company was recently named as the fastest-growing company in North America on Deloitte’s 2019 Technology Fast 500 list.

HMG Strategy recently spoke with UiPath Co-Founder and CEO Daniel Dines who shared his insights on how RPA is evolving and what these developments mean for CEOs and technology executives.

HMG Strategy: How do you see the confluence of AI and RPA playing out in business today?

Daniel Dines: Everybody is still evolving with AI. What has been difficult so far is to operationalize AI into enterprises. We have many clients with data scientist teams to build machine learning, but it’s not so easy to put them into production and to work for people.

For example, many processes involve checking signatures and AI can help with this. It’s valuable to apply AI to simplify these types of activities for humans.

How do you see RPA evolving?

DD: It’s important to look upon the past of RPA. Compared to other forms of technology, it’s a technology that emulates automation. So you don’t change the infrastructure at all, you change the human factor.

RPA features computer vision which applies AI to help robots see and understand every element on a computer screen. Of course, humans can understand different applications and changes on a screen but for a robot to do this reliably, that is very difficult. With high reliabilty, scalability and security now standard for our robots, adoption has spread quickly across multiple departments and processes throughout an organization.

If you look at work today, it’s about email, spreadsheets, line-of-business applications, SaaS applications, etc.. All of these systems and processes are built using user interfaces. Going forward, we’ll use APIs and virtual desktop interfaces to enable end-to-end automation.

What are some of the inherent challenges that clients face?

DD: It’s really difficult to automate processes that are designed by humans. In order to make this approach prevalent, we have to innovate where there are current bottlenecks in adopting automation. Not in the technology itself because it’s proven to work. But enterprise-wide, it requires a much different approach.

What are some of the exciting developments coming out of UiPath that you can share?

DD: We’re developing RPA as an end-to-end platform for hyperautomation.

We’re bringing our AI Fabric product for AI drag and drop capabilities for RPA practitioners to apply into everyday workflows. We’re also investing a lot in analytics to measure and tie business outcomes to robotic operations.

We’re currently in the planning phase of bringing tools to market that can be used to discover processes. This includes tools that can allow people who are involved with different processes to use computer vision to analyze processes and then we show people the processes that are the best candidates to automate.

Our plan is to make this a priority on the C-level agenda. They have to understand the strategic nature and speed advantage of this transformation on the business.