More and more companies are embracing Robotic Process Automation (RPA)
In fact, it’s the fastest-growing enterprise software market, with revenue increasing 63.1% to $846 million in 2018, according to Gartner, which forecasts RPA software revenue will reach $1.3 billion in 2019.
Despite these remarkable figures, we have not yet reached the peak of where this emerging technology that has the power to transform global enterprises can take business and wider society. The key to leveraging this transformative technology however, lies in business’s ability to integrate it harmoniously within the human workforce. IDG’s Future of Work survey found that “86% of executives interviewed indicated that human work, AI systems, and robotic automation ‘must be well-integrated by 2020,’… only 12% of executives said their companies ‘do this really well today.’”
The technology must be more widely accessible and easily scalable to increase RPA adoption – this way non-technical business users can create their own function-specific software bots. It must capitalise on built-in artificial intelligence, enabling an intelligent RPA platform that’s more intuitive to use and more powerful in capability.
Crucially, RPA must be available across various delivery channels. According to CompTIA’s 2018 Trends in Cloud Computing report almost half of all businesses say 31% to 60% of their IT systems are based in the cloud. Given the cost and versatility benefits the Cloud provides, it’s no shock that “81% of companies say that the cloud has greatly enhanced or moderately enhanced their efforts around automation.” Organisations are clearly looking for ways to enhance efficencies and take full advantage of the Cloud.
When you add up all these business needs — that is, RPA enhanced by AI, available to anyone with access to the web — a single solution emerges: a cloud-native intelligent RPA platform that is simple to access, use, and to scale, and works with all applications, whether on-premises (inside the company, on the desktop or a server) or in the Cloud.
Cloud-native: built to optimise cloud technology
What exactly does “cloud-native” mean? According to the Cloud Native Computing Foundation, the term means the entire application — from the control plane to the data plane, top to bottom — is designed to take full advantage of the cloud’s capabilities.
Cloud-native applications use complete units of functionality packaged in containers (such as Kubernetes), deployed as microservices (collections of loosely coupled, independent services), on elastic cloud infrastructure through agile DevOps processes and continuous delivery workflows.
In short, cloud-native is a lot more than just virtualising your on-premises application and delivering it via the cloud. Doing it right means reengineering the design, implementation, deployment, and operation of your applications from scratch.
RPA vendors have traditionally built their applications for on-premises deployment and, in response to the demand for the cloud, have taken their on-premises software as-is and placed it in the cloud. That is what is colloquially labeled a “cloud-washed” architecture, and with it remains all the bother of deploying and maintaining traditional software and infrastructure — but none of the many benefits of a cloud-native architecture.
A little help from above
Enterprise’s affinity to cloud computing hasn’t traditionally been reflected by the RPA industry. That is, until now – with the world’s first cloud-native RPA platform, we’re bringing the advantages of cloud-native, intelligent RPA deployments to organisations worldwide.
For business users, cloud-native RPA operates as a self-service technology accessed via a web-based graphical interface from anywhere. With a single click or drag-and-drop motion, users can automate those parts of any job that don’t require human creativity, problem-solving capabilities, empathy, or judgment.
Just as with popular Software-as-a-Service (SaaS) apps, users can create what they need using an intuitive web interface within the browser. For many common bots, no coding is required. There are no large client downloads to install and manage or commands to memorise; automation and processes are exposed via drag-and-drop functionality and flow charts.
Also, because there is no software client, IT doesn’t have to get involved. Infrastructure management costs go away, significantly reducing the total cost of ownership (TCO).
From an IT perspective, the software is always up to date — there’s no need to perform intrusive upgrades on all client machines every time the vendor releases new functionality or fixes. Additionally, continuous integration, continuous delivery, and continuous deployment methodologies ensure the latest RPA technology is seamlessly deployed without disruption.
Finally, understanding the regulatory constraints that some enterprises face, an ideal RPA platform provides customers the options of being natively deployed in the Cloud, on-premises, or in a hybrid mode where the data is on-premises while the orchestration is in the Cloud.
For developers, since the same software stack is running both in the Cloud and on-premises, they don’t need to re-create their bots if they operate in a hybrid environment, as many companies are wont to do today. Thus, intelligent automation can be deployed seamlessly from on-premises to the Cloud in its entirety with no additional management cost or complexity.
Anything else is legacy
Cloud-native architecture is radically transforming the way modern organisations are thinking about developing, deploying, and managing applications. Cloud-native RPA, which executes and orchestrates processes and workflows within a company, is the next piece of the intelligent automation puzzle for enterprises that are serious about reaping the rewards of RPA.
The benefits of cloud-native architectures stretch across the board — in scalability, management, security, cost, and ease of access while providing a great experience for all users.
About the Author
Prince Kohli, CTO at Automation Anywhere. Extensive and varied experience in building products and teams for Cloud Computing, Enterprise Software, Network Transport, Systems and Security. Have founded and managed startups into high growth organizations with successful exits. Have managed extremely large and very small teams. Have played various Executive roles, both product- and operations-focused. Hold a PhD in Computer Science, specializing in Distributed Systems.
Featured image: ©Peshkova