We are currently running all RPAs now. So robotic automation is the key for us now, and we are moving to the next generation of automation, which is agentic processing. We need a helping hand to make sure that our company strategy and the goal can be achieved with this agentic automation.

With APA in particular, some use cases involve taking complex processes that could have large decision trees, and instead of dedicating time and resources towards fleshing out all those if/then statements or pushing exceptions to human middle processing, we aim to lower that scope and allow for quicker delivery time.

The main challenge with agentic process automation that we are trying to solve is the whole implementation of artificial intelligence within our company, which is crucial because everything that has to do with security and all our databases requires us to be super careful. We are currently facing the issue of ensuring careful implementation while realizing the opportunities for implementing these agentic solutions within our company, which I expect will happen in the next couple of years. In the age of agentic AI, understanding what all the things that agentic AI can provide for our company means focusing on translating AI technology into actual use cases. The challenge lies in prioritizing and making the link between actual use cases and the tools available, especially since AI technology presents many options but can leave us uncertain about which to tackle first.

I am just on the RPA. I have not had a chance to try out the AI agent studio feature of Automation Anywhere yet.

Agentic AI can be used today out of the box with minimal configuration, and it now solves end-to-end processes compared to the standalone jobs that RPA could do previously. Consequently, we have faster, better solutions that we can deliver to our businesses. In the age of agentic AI, there are two key challenges we face. One is on the delivery side within our CoE, where there is a bit of a learning curve for upskilling our development team so they understand what this technology has to offer and how to best use it.

Automation Anywhere has been promising a lot in the last three years, and the roadmap they laid out on APA is definitely going to help businesses. A lot of work has gone into it, and the latest APA-related releases are very good.

I have never tried AI agentic process automation, however, I recently completed my API training and I'm excited to try this new API. My main goal is to learn about any new features implemented at this event and to try to implement those in the future. Automation Anywhere will address these AI Gen AI challenges. As of now, we have not tried AI, however, we know that with AI, we can see many improvements for the bots.

Traditional RPA is no longer sufficient; it has become outdated in this regard. In my opinion, RPA has been essentially irrelevant for the last two to three years. What we are seeing now is hyperautomation, particularly intelligent automations that have evolved into what I refer to as Agentic Process Automation (APA). With Agentic Process Automation, we can manage end-to-end processes, particularly where human intervention is necessary. We can streamline these processes by integrating API tasks and obtaining responses from various sources, such as OpenAI. This integration leads to a higher level of accuracy in our systems.

Automation Anywhere has evolved significantly and upgraded itself to provide agentic AI and AI-based automation solutions for document automation. The product has matured considerably over time.

Automation Anywhere continues evolving with a focus on business services. They need to conduct better research on document reading and improve the accuracy of agentic and GenAI automations to differentiate their product in the market.