Now that you’re in the know about RPA and the business value it can bring, as well as RPA adoption and implementation best practices, we’re ready to get a birds-eye view of the RPA industry.  

Now the market is dominated by three top tier vendors, each one of them having different product characteristics.

One major advantage UiPath has over other vendors, is that its tools do not require many development skills, thus making it incredibly easy to use for almost everyone. While Blue Prism and Automation Anywhere require pretty advanced C# knowledge, UiPath gains competitive advantage in this chapter - it only requires basic knowledge of VB Net, C# and other wildly available programming languages. Its software robot creation platform mainly uses drag & drop actions to create a script, allowing the developer to practice their business-oriented thinking during code creation. 

RPA industry insights 

The BFS (Banking and Financial Services) sector is and will most probably continue to remain the most dynamic RPA adopter, given the struggles with revenue or profitability increase issues, new regulations or competitive disruption. But companies within this realm learn as they go and invest significant amounts of money to adopt AI and ML technologies, thus registering a more mature automation strategy compared to the other industries.  

Across these entities, ML and RPA are the most piloted and implemented solutions, with high expectations for cost savings, applied in both internal and external processes, while RPA is mainly applied for internal processes. 

Insurance companies are the top demanders for AI technology, trying to consolidate customer data and speeding up query handling, by carrying out the most aggressive cost take-out from all of the existing RPA projects and demanding faster results in terms of timeline. 

Taking a look at the healthcare industry, it seems that it is still mostly in the pilot stage. A strong focus needs to be made towards creating a smooth, interactive, engaging customer experience at the lowest cost possible.  

Having an army of software robots working 24/7 and taking away jobs from people scared some politicians (like Bill Gates, 2017), who then vehiculated the idea of taxing the implemented software robots.  

These kinds of actions are counterproductive measures for the automation transformation since, historically speaking, the technology itself never reduced the number of jobs. On the contrary: automation should be used for business growth and an increase in productivity, while human resource should be offered new opportunities for more challenging and value-adding activities. As a fact, new jobs are being created daily, in line with the latest technological advancements.

Artificial Intelligence, Machine Learning, and Neuro-linguistic programming 

Integrating AI, ML or NLP solutions within an RPA automation is neither futile, nor is it cost ineffective. After all, automation is about reducing effort and improving outcomes. To ensure, however, that this and not the opposite happens, adopting a cutting-edge IT technology should happen on a solid knowledge basis. Most AI adopters call on process experts or third-party AI consultants and/or developers to ensure the right things are developed successfully. 

AI, ML or NLP solutions can include: chatbots, voice bots, automated emails, social bots (virtual agents), IVRs or visual IVRs (phone call robots). All of these solutions can bring major benefits to the company implementing them: improved data processing, autonomous judgment calls (decision making), and continuous process improvements as the AI component will suggest. 

An article written by M. Ungur

Next up is my final article within this RPA-focused series: we’ll glimpse into the RPA industry’s future, current trends and predictions.  

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