What is our primary use case?
The main use cases for Automation Anywhere involve automating manually repeated and mundane tasks. I'm currently working for a manufacturing company, and we consider use cases that can replace humans with RPA bots for automation.
We are using document automation in our current process, with two use cases for extracting data from invoices. We tried both digital copies and scanned copies, and while I initially saw hallucination data, after continually training the model, the data is now getting accurate.
What is most valuable?
Currently in RPA, I have almost eight plus years of experience, and I have worked extensively in Automation Anywhere. As a developer, I started my journey as a developer, and now I am a solution architect.
Productivity-wise, I am seeing a lot of difference; there is a huge difference in efficiency as well. We are saving almost four FTEs, and it is far better in terms of savings.
The document automation is saving almost 50% of the time.
An example of how it helped the organization involves the automated documents we implemented almost six months back. Their two use cases are in production now, and we are seeing the value generated every month, which makes us happy, and we plan to enhance it further for other suppliers as well; currently, we have it for 15 suppliers.
What needs improvement?
The main challenge I face with Agentic Process Automation is identifying a use case. This challenge arises because wherever I'm working, in the manufacturing company, we have so many legacy systems without APIs, making it impossible to automate end-to-end; only specific paths of the process can be automated through traditional automation, which needs to be addressed before moving toward agentic automation.
Currently, we are working with Automation Anywhere to overcome these challenges, but it is worth noting that even Automation Anywhere encounters the same problem. They have a tool that we can use to automate end-to-end processes, but when it comes to APIs, Automation Anywhere cannot help due to the legacy systems, which require the company to either create APIs for those systems or migrate to other enterprise systems to resolve the challenge.
We have explored the AI Agent Studio in our automation process, and we have done some POCs with a couple of use cases that created value for us. However, we have encountered some technical challenges, which is why we haven't proceeded with production yet.
When it comes to the integration experience with the features in AI Agent Studio, I have faced a couple of challenges. I tested it almost six months back, during which I encountered issues integrating with my Windows applications. By now, I believe those challenges have been rectified.
Automation Anywhere needs to focus primarily on agentic automation. They have APIs, but the effectiveness of those APIs depends on the value they create. I tested this API almost six months back but not recently, so traditional automation has reached its limits, requiring a shift to agentic automation.
For how long have I used the solution?
Currently in RPA, I have almost eight plus years of experience, and I have worked extensively in Automation Anywhere.
What do I think about the stability of the solution?
I have not seen any downtime or crashes or any problems recently. Earlier, when we had version 11.x of Automation Anywhere, we encountered a couple of issues, but after upgrading to 360, there have been no problems, and everything looks good.
What do I think about the scalability of the solution?
The main reasons I do not change tools are related to the scalability of Automation Anywhere, which I find to be the best tool with no performance-related issues. We have around 200 automations running daily without any challenges, and performance-wise, everything is good.
Which solution did I use previously and why did I switch?
I did not consider another solution before adopting Automation Anywhere, as I started my journey in RPA using Automation Anywhere from the very beginning until now.
What other advice do I have?
From my perspective, AI governance plays a key role in every organization; otherwise, it could easily get out of hand.
The compliance feature of AI Agent Studio meets our needs depending on the guardrails each organization sets up concerning compliance; it varies based on what guardrails they put in place.
My organization is completely focused on data integrity, and they are very particular about compliance, which is one reason they are taking a step-by-step approach. They first conduct POCs and test the tools from Automation Anywhere or other vendors to check what kind of compliance can be enabled before onboarding them.
I have not utilized the Autopilot capabilities or automator AI.
We have a COE Manager, and I understand it helps us understand the revenue generated across the bots we have developed. Unfortunately, we have not taken that license, but I think it is now offered free of cost within the existing licenses. However, we are not actively using it.
Currently, we are doing manual deployment, so automating that step would be more helpful.
I would rate this product 8 out of 10.
Which deployment model are you using for this solution?
On-premises
Disclosure: My company does not have a business relationship with this vendor other than being a customer.