Automation Anywhere Reviews

I have been using Automation Anywhere for about two years, mainly for automating repetitive workflows and exploring how RPA can streamline routing business processes.

My main use case for Automation Anywhere involves automating repetitive optional tasks. For example, I work on a process where data comes in through Excel files and normally someone had to manually validate it and enter it on internal systems and generate a report. With Automation Anywhere, we automate most of the workflows by reading the Excel data, validating the required fields, updating the systems, and generating the report fields. It reduces a lot of repetitive manual work and also helps us to avoid basic data entry errors.

Apart from the Excel data entry workflow, I use Automation Anywhere for report generation, moving data between different systems, and automating repetitive validation tasks. One thing I found useful is that you can combine multiple small manual steps into a single end-to-end workflow. Instead of someone consistently switching between Excel, internal applications, and a report, the bot can handle most of the process and only involves a person when something actually needs attention.

The best features Automation Anywhere offers for me include a visual workflow builder, reusable bots and components, and the way it integrates with common business tools including Excel, web applications, and internal systems. I also appreciate the central Control Room because it makes it easier to manage bots, monitor execution, and handle failures. Another useful part is data, document, and AI-related automations, especially when a process involves extraction and validation of data from semi-structured documents.

The flexibility of Automation Anywhere's truly universal orchestration is one of its strongest points. We are not limited to automating with just one application; we can orchestrate workflows across web applications, APIs, databases, documents, and other enterprise systems. I also appreciate that the orchestration layer does not force everything to depend on AI models. Different models or AI services can be incorporated depending on the use case, while Automation Anywhere manages the broader workflow. In our experience, this is useful for combining traditional rule-based automation with AI-driven steps while still keeping monitoring, validation, and human approval in the same end-to-end processes.

One area that Automation Anywhere can improve is the debugging experience. When you have a long workflow with multiple bots and integrations, finding the exact cause of a failure can sometimes take longer than expected because step-by-step debugging and clear errors would help. I would also appreciate seeing some of the more advanced features become easier to configure. The platform is powerful, but there can be a learning curve when you move from basic automation to complex workflows. Improving that would make development and maintainability faster.

I think visual management and collaborative work can also be smoother, especially when multiple developers are working on the same automation for a longer project. Comparing changes and managing different versions can become a little cumbersome. I would say improving the overall performance of the development environment for bigger workflows as automation becomes more complex, keeping the interface fast, and making dependencies easier to manage would improve the development experience quite a bit.

I have been working with Automation Anywhere for two years.

Automation Anywhere is pretty stable in my perspective because we do not see many problems. Most problems we encounter arise from changes in external applications, UI elements, credentials, or input data rather than Automation Anywhere itself.

The scalability of Automation Anywhere has been good for us. As the number of workflows and bots executing increases, we are able to manage them centrally through the Control Room without needing to redesign the whole setup. The cloud-based model also makes it easy to add more bots, capability, and capacity as demand grows. Our considerations around experiences and maintainability usually center on licensing, infrastructure planning, and ensuring workflows are designed efficiently rather than being limited by the platform itself.

The customer support from Automation Anywhere has been very good overall. Whenever we need help with configuration or troubleshooting, the team has been responsive and generally provides useful guidance. For more complex technical issues, resolution sometimes takes longer because there are investigations involved, but overall, I rate the support experience positively at eight out of ten.

We did not use any full RPA platform before Automation Anywhere. Most processes were either handled manually or through small scripts and application-specific automations.

My experience with Automation Anywhere's pricing, setup cost, and licensing is pretty positive. The pricing is more on the enterprise side, so I would not consider it a low-cost solution, especially once you scale to many bots and users. However, for a process with enough volume, the time saving and reduction in manual effort can justify the cost. Initial setup took some planning, particularly around bot configuration and integration, but after that, it becomes fairly manageable. Licensing can be a little complex because the cost depends on the capabilities and scale you need.

We have seen a positive return on investment with Automation Anywhere mainly through the time saving and reducing manual efforts. For some repetitive workflows, tasks that previously required one or more hours of manual work can now be completed much faster and with minimal human involvement. Document processes have reduced the time spent on extracting, validating, and entering data. I do not have an exact professional financial ROI percentage because I am not directly involved in the financial reporting, but from an operational perspective, the reduction in manual hours and errors has been worthwhile for us.

My experience with Automation Anywhere's pricing, setup cost, and licensing is pretty positive. The pricing is more on the enterprise side, so I would not consider it a low-cost solution, especially once you scale to many bots and users. However, for a process with enough volume, the time saving and reduction in manual effort can justify the cost.

We were looking at a few alternatives before choosing Automation Anywhere, mainly UiPath and Microsoft Power Automate. We compared them around ease of development, integration capabilities, centralized management and scale, and overall enterprise governance. Automation Anywhere stood out for us because of its cloud-based approach, central Control Room, and capability to manage large end-to-end automation workflows; those other solutions were not able to do it.

My impression of Automation Anywhere's AI governance features is positive. They give us better control over how AI is used within our automation, especially around access to sensitive data and traceability. Role-based permissions and audit trails are important because we can control who is building, modifying, or running particular automation and have visibility into what happened. For data integration, we use validation rules and human review for sensitive and low-confidence cases, rather than relying completely on AI output. I see the governance features as a strong foundation, but they work best when combined with the organization's own compliance and data handling policies.

The biggest challenges with agentic AI for me are governance and security, reliability, and maintaining control over what an AI agent is allowed to do. Unlike traditional rule-based automation, an AI agent can make dynamic decisions, and we need to be confident about its output, data access, and what happens when it comes to making a mistake. Automation Anywhere helps by combining AI capabilities with more controlled automation. Workflows can handle access control, maintain auditability, and include validation rules and human approval for sensitive steps. I think this combination is important because we want the flexibility of agentic AI without sacrificing governance and predictability that we already maintained with traditional automation.

The main objective with agentic process automation was to move beyond automating only fixed repetitive tasks. We want the automation to handle situations where there are expected changes in input or some level of decision-making involved. For example, in document processing, instead of just extracting predefined fields, the goal is to understand the outcome of the information, validate it, decide what should happen next, and route exceptions to the right person. Agentic process automation helps us connect these fields into more intelligent end-to-end workflows while keeping human oversight for critical decisions.

My impression of the data advantage provided by Automation Anywhere's process reasoning engine is that it really excels because it is designed around enterprise workflows rather than just general-purpose AI tasks. This gives us a more useful understanding of how different steps, applications, data, and business rules fit together in a process. Whenever I use it, the most valuable aspect is in reducing the amount of context we have to provide manually and helping the system make better decisions around the next steps in the workflow. I still validate a decision for critical processes, but overall, enterprise process context makes agentic automation particularly relevant for real business use cases.

My advice would be to start with processes that are repetitive, high-volume, and have clear rules rather than trying to automate everything at once. Pick a few workflows where you can clearly measure the time saving and then expand from there. I would also recommend putting proper exception handling, logging, governance, and monitoring in place from the beginning. For AI-based automation, keep human validation for sensitive, low-confidence decisions. Automation Anywhere is very capable, but the quality of the results still depends heavily on how well you design and govern the automation. I gave this review an overall rating of nine out of ten.

We focus on multiple use cases, but primarily in the banking and finance vertical. We leverage Automation Anywhere's platform extensively. For one of our leading customers, we have transformed most use cases with respect to collection, reconciliation, validating possible fraudulent activities, and proper audit of cases. Many use cases which are very time consuming have been solved with the help of automation.

Contract management presents two challenges. One is understanding contracts, which are unstructured in nature. With AI, we can now read and analyze those contracts. The second challenge is processing invoices based on the contract terms, which is deterministic and rule-based in nature. Once I understand the contract, I can apply the appropriate terms and conditions and process the numbers accordingly. The blend of cognitive capability and deterministic capability together solves this problem.

Process reasoning, which we call process mining, serves the underlying purpose of monitoring what is happening and identifying improvement opportunities. Audit logs recorded by the system are analyzed to provide insights on how we can improve further, where deviations are happening, and what the improvement areas are. This complementary capability is powerful for larger enterprises to evolve to the next level, not only for what we have delivered now but for how we can graduate to the next level.

One thing I appreciate about Automation Anywhere is that we do not need to run around with multiple platforms. Automation Anywhere provides an end-to-end solution.

The platform has many features I value, but what has helped me most is not having to run around for multiple platforms. Automation Anywhere integrates very well with the underlying ecosystem. If I want to leverage document processing, the platform has very strong capability in that. If I want to leverage AI, I can easily embed AI from other parties within the same platform. If I want to take their services out of their platform into some other platform, they provide all that exposure through APIs. Automation Anywhere is very flexible and at the same time very cohesive, allowing us to solve all problems within the same platform without needing to run around.

As an organization, it is very easy to govern the process. If we had multiple platforms, we would need parallel governance and then one common governance on top of that. Automation Anywhere uses a non-monolithic design where multiple agents have different purposes, but at the same time there is a common orchestration layer. We can track the complete journey in an auditable form within the same platform, which helps us know what happened in each particular case. This provides a very seamless experience for anyone embracing the platform.

Automation Anywhere is a fantastic platform, but I rate it nine because I see one scope of improvement. They can leverage AI to accelerate their SDLC journey. AI for process recording, having that process recording fed directly into the engine, from engine to having the bots ready, and then governing those bots while preempting failures and having auto healing is where they need to immediately lead because that is where the competitors are converging towards.

We have our own IX suite as Concentrix, but that is more on the conversational side because we are very much focused on the CX stack as a business. We have invested in voice bots, chat bots, and other conversational capabilities which are part of our customer service. Where it comes to the back office where we need to get the job done, in the definition of agents—more execution agents—we are highly relying on platforms like Automation Anywhere.

Building our own product is always an aspiration every company has. We as a company invested a lot on the conversational side, and that is what we have in our IX suite. Automation Anywhere and platforms like it are complementary to each other, where our suite is more focused on front office conversational side with voice bots and chat bots. Behind the scene, when those dispositions land into execution with the back-office system, we rely on Automation Anywhere to close the gap. It is complementary.

Initially, there were some hiccups because of poor Java or JRE issues. Now that the platform is a cloud platform, they have migrated themselves into the cloud. They are taking all proactive measures in having patches updated and binaries updated with the latest versions and whatever threats they are seeing. I am not experiencing much downtime. In the last one year, I have not experienced any downtime driven by the platform. Downtime has happened because of other reasons not in the platform's control. For example, the underlying application is down, or there are network level disruptions happening which are not in their hands. From platform originated disruption, there is not much.

Automation Anywhere has an edge over other platforms in this area. They are really very proactive and believe in relationship. When we raise a ticket and share a concern, we hear back from them in a very short time. Given the way their business is going, they have created their own support model where we can have priority support. We need to pay a little premium for that, but by paying that premium, we can get priority support. For critical customers, we go for that option. When we have something we can solve ourselves, because this competency is like ten years old within our organization, we only disturb them when we see that we need to take platform advice. Otherwise, our architects and developers are solving most issues. I rate this aspect ten out of ten with no complaints.

The answer is yes. Given that we do not always have a choice to decide the technology, we step back and say we are not the pharma person, we are the doctor. We are not selling medicine, we are selling solutions. Sometimes we need to prescribe medicine by seeing the problem statement or something where a client has already invested. There are parallel products of Automation Anywhere. I do not want to name them now, but we all know. Because we do not have a choice and the client is already having a parallel relationship with them, we continue solving their problem using those platforms.

If we think about peer products like UIPath, Blue Prism, Microsoft Power Platform, and Workato, they are peer products where we have parallel competency the way we have in Automation Anywhere. At the same time, most of the hyperscalers are also coming with their own automation platform, like Microsoft Foundry which is in the space of APA, and Google and AWS are all bringing their own platforms. We are leveraging their platforms as well.

I was trying to recollect when the most challenging experience I had was when deploying Automation Anywhere. One thing which is part of the design is that we can easily have a different environment with a clear-cut checklist defined for the development team. Some of these experiences can be avoided. We do have a staging environment where we do all kind of checks and balances before we move things into production. The consistency of the environment is very important because sometimes the version we have in development versus in production are not the same for the base platform, because of which our bot is not able to recognize some of the screen elements and that is where it fails. That is where the retake happens. I think if we had some checklist handy, these things could be avoided. I do not think these are platform limitations. This is more with respect to the way we use that platform. If we are using this tool perfectly, we will hardly experience this.

Typically, in the past when we talked about ROI, we were more focused on KPIs and SLA of the contact center side, where we said we were able to reduce efficiency or drive accuracy. What I am seeing now in terms of ROI is that we are trying to gauge it at a larger perspective. The equation is more at the enterprise level where our metrics are getting aligned with business metrics of the customer. That is where the ROI is very disruptive now. With the power of AI, the demand is very high. Customers are asking for more and more impact on their bottom line. By saying that, we have to be very creative in our ideas and how to give them back.

By design, from the beginning, Automation Anywhere was designed for enterprise solution. From RPA to APA, if we see the graduation, what we see as a consumer is that earlier we were having a bot, now we have a bot with a brain. The orchestration and the journey is now amplified with other use cases which were not part of the scope before, which were very decision-making, reasoning, and some contextual background that we need to answer those things which we are parking for human. Now, the agentic part has that reasoning also ready. For high-risk profile, when someone as a human is doing that validation, they do not need to use brain for reasoning. They just need to proofread the reasoning and see that there is a logic for that and approve it. That is where we see from RPA to APA, and with the same platform, we do not need to disturb the platform. The only thing is the brain is also added in that platform. That is how more activities which are part of the human job are now part of the bot job or the agent job.

Three years back when everyone started talking about APA, the first thing we did is we stopped calling our internal advisors agents, because until that time, customer service agents were what we addressed them as. We said "You are the game changers and now technology is the agent." With that change in culture, we started embracing APA very extensively by saying that the rule of the game is the same whether we outsource this work to human or to agent. The discipline is the same, the governance is the same, the guardrails are the same, and security norms are the same because someone is trusting us with giving data. Data misuse is very common. The kind of role-based access control that we plan for human agent, the security guardrails for all the layers of the infrastructure, from the access, where things can go wrong because it is an agent with a very powerful LLM running behind, how to control and avoid any kind of side attacks that can happen on these things. We need to prevent and ensure that our customer data is safe irrespective of the situation. Some of those disciplines continued, and that is how we are graduating into APA. Rather than just calling agent, we have started calling them digital worker and the new hybrid setup of a human bot agent delivering customer problems together.

We are getting into this hybrid setup of human, bot, and agent, all part of the ecosystem in addressing one journey of the customer. In any use case journey, we will have some activities done by the bot, which is very deterministic in nature. We do not want to pay for AI in that situation. Some of the cognitive capabilities will have agent and agentic capability of AI, and then at the end of the day, we need someone to approve it, which is where human comes. The complete journey has to be tracked so that if any customer query is coming about why we gave them a certain amount for a claim, just thinking of claim processing as one example where sometimes customers bounce back and say that this was not the right claim settlement happened. In that case, we really need the traceability. We need to know how we processed it. Traceability in the journey cannot go and say that this is done by the agent and this is done by the human. The complete journey should be auditable. That is where the central governance which was mentioned is very important. Everything should be part of the central governance or the orchestration layer so that whether it is a human or agent, everything should be stitched with the same thread.

Something which is always there is the pricing part, but I do not want to press on that because there is no end of it. On the platform part, certainly one thing which we really need to see is how we can accelerate developer journey. Today, if a team is taking two weeks' time to build one agent, with other parallel platforms like Claude and Co-pilot who are trying to infringe into AI SDLC, the life cycle of agent development, where they are trying to step in into all the stages of defined build and run, how we can have that as part of the platform. I learned in conference that they already have something called AA Code, not in production and not out for the consumer, but they are already thinking on that. That is something which I was missing when I entered in this conference. We certainly need to leverage what Claude is doing or what other hyperscalers are doing in the same space.

Customers are coming to us with very disruptive pricing models. From the service industry, we cannot just go by the labor arbitrage or license-based model today. We need to be more value-driven model. Today I am selling a service with X dollar per transaction and I can give it with fifty percent cost. If I can get a similar model from Automation Anywhere, then it will be a seamless calculation for me. That is where I will say true partnership will do where we are bringing services, Automation Anywhere is bringing technology, and we both are following the same equation, and we both will graduate with the same level of commitment and scalability. That is where a part of pricing will help.

Positively, there is one unique selling point what Automation Anywhere and peer RPA platforms have is UI-based automation, which was their starting point. Because most of the legacy systems do not have API level connectivity today, and that is where the hyperscalers are not able to bridge. Automation Anywhere has both things. They have API which is intrusive in nature where we can have that direct connectivity with the base platform or the system, and non-intrusive where we can leverage their UI automation capability to ensure that there is no bottleneck. We can have the complete journey done. That is where Automation Anywhere has upper hand. Hyperscalers have upper hand because they have their own proprietary model where they can drive more disruption. They have base platform access—if I talk about Microsoft, it is very for them to have seamless integration with their Office platform, SharePoint, shared drive, Active Directories, and other things and give an end-to-end solution with Co-pilot and OpenAI and other things. Hyperscalers have their own advantage. Being doctor, we go by the problem and see how to position and solve it. Sometimes we are making combination of both and solve the problem. My overall rating for this review is ten out of ten.

My use case for Automation Anywhere is primarily focused on SAP monitoring and making some business activity changes within SAP business activities.

If I compare Automation Anywhere and SAP ERP, my opinion based on my experience is that it is very specific to use cases. My use cases are very specific to SAP because I work in an SAP environment. SAP ERP is a better solution for me considering my use cases are more aligned with SAP. However, if you consider the broader market, there are multiple aspects where Automation Anywhere can be better than SAP ERP, considering its use cases for non-SAP systems.

Specifically, the development studio is very useful for me in Automation Anywhere. The second thing is the deployment, which makes it easy for deploying and using the automation with the availability of the platform.

The main benefits Automation Anywhere provides for me divide into multiple aspects. If we are talking about taking the requirement and all, there are some pre-built solutions available from the marketplace which you can use. The understanding of the tool and utilizing it for the purpose allows you to use the template directly and build your own solution. The execution or the orchestration part of it is very good. All these aspects come together when considering the benefits of the tools.

For the challenges with Automation Anywhere, I will give some examples. SAP IRPA directly has connectivity, but if I need to build the same board from Automation Anywhere, the connectivity will come as an extra additional task to be done with drivers and connections. Although Automation Anywhere has the capability to automate those things, you need to go that extra mile to cope with that for developing that automation and connecting those systems. Since it is not an in-house solution for ERP systems or CRM systems, automating those things requires additional effort. The automation can be done, but it is not directly connected. You have to build an extra connection for that. Considering those aspects, those are the difficulties I could identify, but it is not a showstopper.

Direct plugins to connect to multiple systems, if those can be added into it, would be an improvement. There are multiple ready-built plugins available, but there are still some loose points where I need to bring certain things. I do not know whether it has been added in the last seven months, but till the time I was using it, it was not there. If AI solutions such as Copilot or OpenAI solutions can be readily plugged into Automation Anywhere to build a code around it, then it will help. Those improvements can be added to the tool.

I have been working with Automation Anywhere for six years.

For stability, I could give it a nine out of ten. The plugins require that extra mile, and sometimes they might get broken considering that the solution might get broken in between.

I would give Automation Anywhere a ten out of ten for scalability and the ability to expand.

Regarding technical support for Automation Anywhere, I could give it a ten out of ten. I have not reached out to the support group at all. The tool itself is self-sufficient to fix all the things.

I was using GitHub Copilot for that, so I did not use or our organization itself was not using Automation Anywhere Copilot. The integration is with GitHub, which is why we are using a different tool.

The initial setup process for Automation Anywhere is very simple.

We do have a separate team for maintenance for Automation Anywhere. I am the only developer. There are altogether different teams who do the maintenance, the orchestration, and monitoring of the solution execution.

The answer to ROI comes with certain bracket values, meaning it is totally dependent on the use cases you use in Automation Anywhere. You need to understand the ROI of that particular automation solution when developing it. If it really values the development and the use cases, I will give an example. If it is monitoring stuff and there are five people onboarded for monitoring your systems, it is worth developing an automation on Automation Anywhere and making it automated for completing that monitoring report and sending it over email. You can remove those five resources, which counts as ROI for that. The ROI will be very high, considering ninety percent. However, when you go with any business case for which one person is deploying and that use case has been executed only once a year, there is no point. Even though you can automate, it does not consider value-for-money automation if it is executing only once a year. It totally depends on the use case. In a nutshell, if I am talking about this rate, it will be value for money considering the larger aspect and the solution available on the marketplace.

I did not purchase the license directly from Automation Anywhere. My organization handles this and took a call to obtain it for me. I am the user. I do not know whether it is through a third party or direct from Automation Anywhere, but I believe it is direct.

The main competitors in the market are two. One is UiPath. Another is SAP IRPA.

Working with Automation Anywhere is quite technical. When you have a business person who holds technical knowledge, they will find it easy. However, if there is a non-technical person who does not know anything about the technology and they are only business drivers, they will find it very difficult due to technical terms that need to be understood to operate it. I will not count this only on Automation Anywhere; I count it on any RPA tool in the market.

Automation Anywhere has its own tutorials, which you can do to help. However, when we talk about business persons, if any solution which is built on Automation Anywhere is very easy to use. However, if you are talking about using Automation Anywhere itself for business persons, it is very difficult for them considering they need to understand the technical terms. Regarding the training, it has its own tutorials and training programs in which they can participate and learn. There are multiple platforms also available. For example, on Udemy, they can get their hands dirty with some training and training systems, and they can use it.

The main benefits Automation Anywhere provides for me divide into multiple aspects. If we are talking about taking the requirement and all, there are some pre-built solutions available from the marketplace which you can use. The understanding of the tool and utilizing it for the purpose allows you to use the template directly and build your own solution. The execution or the orchestration part of it is very good. All these aspects come together when considering the benefits of the tools.

All RPA tools used in the market have similar features and aspects that can be developed. However, specifically for Automation Anywhere, the ready-to-use templates which can be used as plug and play are a great feature. You just need to build a solution around it. This is a very good feature that saves time to build a bot or build any automation to get it business-ready or go live easily considering the other automation tools. That is the major aspect I can find in Automation Anywhere. I would rate this review a nine out of ten overall.

My main use case for Automation Anywhere is to automate processes that you can automate, but sometimes, especially, you need to automate workflows, so I think that is the special case.

To give you a quick specific example of a workflow I've automated using Automation Anywhere, I remember working on a project requiring process automation. For example, one workflow I automated with Automation Anywhere was the preparation and validation of test data before regression testing. The bot collected data from different internal resources, validated required fields, updated the test environments, and generated a report of any inconsistencies. This reduced repetitive manual work and allowed the QA team to start automated regression tests with cleaner and more reliable data.

Beyond test data preparations, I also use Automation Anywhere for repetitive QA support tasks, such as validating data across systems, generating execution reports, checking file outputs, and triggering follow-up steps after automated test runs. The main benefit was reducing manual effort around regression cycles and giving the QA team faster feedback when something failed or required investigation.

Automation Anywhere has a positive impact on productivity because it helps reduce repetitive manual work, improve consistency, and speed up several operational QA-related processes. It has allowed the team to focus more on higher-value activities while automated workflows handle routine validations and has also improved traceability because executions can be monitored and issues are easier to identify.

Approximately, I estimate that document automation saves around eight to ten hours per week, roughly thirty to forty hours per month. The biggest savings come from reducing manual data extraction, validation, and repetitive document processing tasks, especially when handling higher volumes.

Overall, it is very helpful, and Automation Anywhere has helped us achieve our automation goals by reducing manual effort, improving consistency, and making repetitive processes easier to scale. From a QA perspective, it has been especially useful for supporting test data preparation, validation, and reporting.

Document automation is very useful for extracting and validating information from structured and semi-structured documents. It has improved efficiency by reducing manual data entry, speeding up validations, and lowering the risk of human error.

The biggest challenges for us are reliability, governance, data privacy, and maintaining visibility into what AI agents are doing. Automation Anywhere helps by combining AI capabilities with a structured workflow and centralized governance, making it easier to put controls around AI-driven processes instead of allowing agents to operate independently.

In my opinion, the best features Automation Anywhere offers include the visual bot development, reusable components, and strong integration with APIs and enterprise applications. I also value the scheduling, credential management, and the error-handling capabilities because they make automation easier to maintain and more reliable in production.

Among those features, I find credential management especially valuable in my daily work because many automated workflows interact with APIs, test environments, and internal systems. Keeping credentials centralized and secure reduces the need to hard-code sensitive data and makes the automation easier to maintain across different environments.

The platform is strong when you need to combine reliability with maintainability, and features such as centralized bot management are reusable with components. The logging and the error handling make it easier to scale automation beyond a single script and support as part of a larger QA or enterprise workflow.

Regarding Automation Anywhere's AI capabilities, I think it has a strong approach to governance and security, especially for enterprise environments. The governance becomes even more important because you need clear controls around what data is being used, who can deploy AI-driven automation, and how decisions or outputs are audited. I would appreciate seeing even more transparency around AI model usage and data protection.

I find the AI capabilities are generally accurate and reliable, especially when the input data is structured and the workflow has clear validation rules. From a QA perspective, I treat AI output as any other system dependency: validate the response, define confidence thresholds, log exceptions, and have fallback handling when the result is uncertain.

I use Automation Anywhere AI Agent Studio mainly to evaluate how AI-driven steps can be integrated into existing automation workflows. The integration experience has been good, especially when connecting agents with APIs, business applications, and existing tools. I find most useful the ability to combine traditional rule-based automation with AI for tasks that require classification, interpretation, or decision support.

AI governance is very important in my organization because AI-driven automation can interact with sensitive data, APIs, and business-critical systems. The AI Agent Studio addresses those needs fairly well through role-based access control, centralized model governance, prompt and event logging. I especially value the visibility into model interactions because it makes troubleshooting and compliance review much easier. I would appreciate seeing governance become even more proactive with strong automated policy enforcement, easier compliance reporting, and more granular controls around sensitive data and model usage.

I have used Automation Anywhere COE, and I think its biggest value is the visibility it provides across the automation life cycle. It helps centralize information about automation opportunities and business impact. From a QA and governance perspective, that visibility is useful because it makes it easier to identify bottlenecks, track automation performance, and understand which processes are delivering value.

My impression of the AI governance features is positive overall. They help maintain compliance by providing centralized controls, and for data integrity, the most important value is having traceability around inputs, outputs, model usage, and exceptions.

I would rate the flexibility of Automation Anywhere quite highly. It integrates well with APIs and enterprise applications, allowing the orchestration of traditional bots, API-based automation, and AI-driven steps within the same process.

Overall, I think the main advantage of the process reasoning engine is that it understands enterprise workflows better than a more general AI model, recognizing common process patterns, dependencies, and exceptions, which makes the recommendations feel more relevant to real business automation.

To improve Automation Anywhere, I suggest enhancing the documentation and tutorials because sometimes they are not very clear. The platform could improve by making the debugging and troubleshooting faster, especially for complex workflows. Better visibility into execution failures, clearer error messages, and easier version control integration would help development teams. I would also appreciate more flexibility for advanced users who want to combine low-code automation with custom code and CI/CD practices.

Debugging complex bots could be easier with a step-by-step approach, clearer stack traces, and more detailed error messages that show exactly which action or variable caused a failure. Version control could be improved with better Git integration, including easier diff comparison, branching, and merge conflict handling for bot changes. Additionally, I would appreciate more flexibility for advanced users, such as easier integration of Python, JavaScript, or API-based custom logic inside low-code workflows without adding too much complexity.

One special point I see for improvements is about code integration. I think one additional improvement would be better observability for larger-scale automations, with more detailed dashboards for bot performance, execution trends, failure patterns, and resource usage, so teams can detect problems before they become production issues.

I have been using Automation Anywhere for around a couple of years, and I specialize in automation and development.

At this moment, Automation Anywhere is stable.

Scalability is good, especially once the platform is properly set up. It is fairly easy to add more bots, schedules, and workflows as demand grows, and centralized management helps keep things organized.

I did not require customer support, but I have heard that it was good.

Previously, we used custom automation tools, including Selenium or Python, which worked well for QA-specific tasks but required more maintenance and technical ownership. We moved toward Automation Anywhere because it gave us better centralized management, scheduling, credential handling, and visibility across business and QA processes.

I cannot share return on investment details because it is private.

Automation Anywhere licenses were not purchased through the AWS Marketplace. My experience with pricing, setup cost, and licensing was overall reaching out with the team. We had great meetings to talk about the prices, so it was a good impression.

I did not evaluate other options before choosing Automation Anywhere.

I recommend starting with a few clear, repetitive processes where you can easily measure the value. Do not try to automate everything at once. Also, spend some time defining the standards for logging, error handling, credentials, and bot ownership early on. That makes a big difference once you start scaling. From a QA perspective, treat bots as any other software: test them, version them, monitor failures, and have a fallback when something goes wrong. I rate Automation Anywhere an eight out of ten because it is a strong platform for enterprise automation, especially for repetitive workflows and centralized bot monitoring. I would rate it higher if the debugging, version control, and CI/CD integration were more developer-friendly.

My primary use cases for Automation Anywhere involve automating repetitive business processes, including data entry, data validation, information transfer between applications, and routine report generation. These processes often involve multiple steps that must be completed consistently, making them suitable for rule-based automation.

For example, a workflow can collect information from structured files, validate required fields, enter the data into a business application, and generate a report. Exception handling is important because missing information or unexpected application behavior may require human intervention.

I also consider scheduling, execution monitoring, and centralized bot management valuable for maintaining recurring automations. The main benefit is reducing repetitive manual work while keeping processes consistent. However, successful automation depends on selecting suitable processes, handling exceptions properly, and maintaining bots when applications or business rules change.

Automation Anywhere can improve operational efficiency by reducing repetitive manual work and standardizing routine business processes. Automated workflows can execute predefined steps consistently, reducing opportunities for data entry errors and allowing employees to spend more time on tasks that require judgment.

Another benefit is improved process visibility. Execution logs and monitoring capabilities help teams identify failed tasks and investigate problems. The overall impact depends on how frequently a process runs, how much manual effort it previously required, and how often exceptions occur.

I have not formally measured the overall financial impact, so I would avoid assigning an unsupported percentage to productivity improvements. The key benefits to evaluate are processing time, error rates, exception handling effort, and ongoing bot maintenance.

The features I consider most valuable are visual bot development, workflow automation, scheduling, and execution monitoring. Visual development tools help organize automation steps, while reusable workflows can simplify the implementation of repetitive tasks. Scheduling allows supported processes to run at planned times, and execution logs help teams investigate failures.

Application integration is another important capability because business processes often involve moving information between multiple systems. Automation can reduce manual transfers, but reliability depends on the quality of the integration and how unexpected conditions are handled.

Intelligent document processing and AI-enabled automation can extend automation beyond straightforward, rule-based tasks. These capabilities can help with documents and less structured inputs, although results need appropriate validation. For critical workflows, exception handling, access controls, and human oversight remain important.

Automation Anywhere could improve the developer experience by making bot debugging more intuitive and providing clearer explanations of errors. When an application interface changes or an unexpected condition occurs, identifying the cause of a failed automation can require additional investigation.

More guided troubleshooting, clearer execution logs, and easier testing of exception scenarios would help developers maintain bots more efficiently. Improved visibility into bot dependencies and version changes could also reduce the risk of disruptions when workflows are updated.

Pricing transparency and easier estimation of the total cost of ownership would be helpful for organizations planning to expand their automation programs. These improvements could make automation easier to maintain and more predictable as the number of bots grows.

I have approximately two years of experience working with Automation Anywhere for robotic process automation, primarily focusing on automating repetitive tasks, improving workflow consistency, and reducing manual effort in business processes.

Automation Anywhere can run recurring workflows consistently when bots are designed, tested, and maintained properly. Reliability depends on factors such as application availability, input data quality, integration behaviour, and how exceptions are handled.

Changes to application interfaces or business rules can cause failures, so error handling, execution logs, retry limits, and monitoring are important. I would assess stability using actual execution success rates, failure patterns, and recovery effort rather than assuming that every workflow will run without issues.

Automation Anywhere can support the expansion of automation across multiple business processes, provided the organization has appropriate licensing, infrastructure, governance, and operational practices. Reusable components and standardized development practices can help teams maintain consistency as the number of automations increases.

However, scaling is not simply a matter of creating more bots. Organizations also need to manage execution capacity, bot dependencies, credentials, exceptions, and maintenance. I would recommend monitoring bot utilization and failure rates, prioritizing high-value processes, and establishing clear ownership before expanding the automation program.

I would rate Automation Anywhere’s customer support 9 out of 10 based on my experience. Support quality is important when resolving configuration problems, investigating bot failures, and understanding platform capabilities. Clear technical guidance and useful documentation can help teams resolve issues and maintain their automations more effectively.

Automation Anywhere was the first RPA platform I worked with directly, so I do not have firsthand experience migrating from another RPA solution. My evaluation is based primarily on its automation capabilities, development workflow, and suitability for repetitive business processes.

The initial setup required planning around the automation environment, application access, credentials, and workflow requirements. Building a simple bot was relatively straightforward, but testing end-to-end processes and handling exceptions required more effort. Proper testing and monitoring were important for making the automations reliable enough for regular use.

The implementation was handled internally without a separate external integrator, reseller, or consultant. This allowed the team to manage configuration and workflow requirements directly. The main effort involved developing, testing, and maintaining the automations to ensure they worked as expected.

The main return from automation comes from reducing repetitive manual work and making recurring processes more consistent. For document processing, the potential benefits include less manual data entry, fewer avoidable errors, and reduced time spent on routine validation.

Based on my estimate, document automation saves approximately 5–10 hours per week, depending on document volume and complexity. I have not formally calculated the overall financial ROI, so I would evaluate it by comparing time saved and error reduction against licensing, implementation, and maintenance costs.

Pricing and licensing are important considerations when adopting Automation Anywhere, particularly when an organization plans to expand from a few bots to a larger automation program. The overall cost should be assessed against the required automation capabilities, deployment needs, maintenance effort, and expected business value.

Initial implementation also requires time for process assessment, bot development, testing, and team training. Although automation can reduce repetitive manual work, bots still require maintenance when applications or business requirements change. I would recommend estimating the full cost of implementation and ongoing operations before expanding deployment.

I also looked into UiPath as an alternative when exploring RPA platforms. Both platforms support business process automation, but the right choice depends on development preferences, integration requirements, governance needs, and licensing costs. My direct experience is stronger with Automation Anywhere, so I would not claim a comprehensive hands-on comparison without evaluating both platforms against the same workflows.

I would rate Automation Anywhere 8 out of 10. Its automation capabilities can help standardize repetitive processes, reduce manual intervention, and support the management of recurring workflows. I would leave room for improvement in debugging, bot maintenance, and cost predictability.

My advice is to begin with a well-defined process that has clear rules, sufficient transaction volume, and measurable outcomes. Establish a baseline for processing time and error rates before implementation, then compare the results after deployment. Organizations should also plan for exception handling, access control, testing, and ongoing maintenance rather than focusing only on the initial development effort.

I am a Senior Enterprise Architect still working for a company, using Automation Anywhere myself. Mainly SAP is integrated with Automation Anywhere, where I have used SAP mostly, and Salesforce as well, but not completely. Most of the tools I have integrated and interacted with is the SAP application mainly and web apps. Desktop apps are not too many, but web apps is another area where we have used heavily along with SAP. This is my experience from working with customers.

Automation Co-pilot has improved my productivity a lot. I think it has increased by 60% in terms of the tasks that I put forth when I log in and log out, and all the tasks will be done quickly. Even the next week activities I would be completing. My productivity has increased and it is growing steadily and gradually. As of now, I see my productivity has been enhanced by 60% using the Copilot features. Automation Co-pilot has helped free up staff to work on other projects and has helped me considerably.

I love Document Understanding in Automation Anywhere, especially IQ Bot; those are very good features to work with because of the needs and there is a potential opportunity for all companies to do these sorts of document processing, document extraction, and document learning. These are very good features in automation that I love to work with. The API is another way of working. In Automation Anywhere, IQ Bot is very good, which is comparable to Documentum. Automation Anywhere also has agentic AI solutions, which are very good in terms of minimal development and no overhead on deployment. I can easily plug and play in the organization's client ecosystem and spin up these solutions quickly. I love to work with these features repeatedly.

I assess Automation Co-pilot's ability to integrate with the organization's day-to-day applications as very good. This is very much applied in our job day-to-day at work. We see how the prompts can be enhanced and how to get low-code solutions and quickly spin up the POCs. Our complete knowledge base and ontology is very good in terms of using them in Automation Co-pilot. We are planning to drive a delivery strategy for one of our customers through this Copilot, which will orchestrate the workflows, orchestrate the agents, and orchestrate the bots so that we will have a complete end-to-end autonomous automation from an operations perspective. I love to do that. This is very good, delivering things driven by automation and Copilot features.

I assess the integration of automation into my workflows, APIs, business applications, and documents as very good. There are no words, but very good in terms of integration—fantastic and one of the standards and best practices. You can easily integrate with it. The ease of use is where I have seen improvement from the developers' perspective, because I interact with the developers and they keep telling me these are all integration points that Automation Anywhere offers in its capabilities and I think they are very easy to use. The integration of automation with other products, technologies, and tools across the world industry is one of the best.

I don't think Automation Anywhere is easy to use for business users who do not have technical skills. Though they have the feature, compared to other products, I don't see a lot of capability that Automation Anywhere has from a citizen developer's point of view or for non-technical folks. If you are very smart and you know how to use Automation Anywhere, it is all easy. But for basic folks and even non-technical users, 95% of them will be business users, and I don't see Automation Anywhere having the same capability comparatively. Power Platform, especially Power Apps, Power Automate, and Copilot Studio products and agents, are pretty good. I have seen this through my own experience and I regularly interact with business users teams for several engagements and have seen their feedback. They liked Power Platform very much compared to any other product, possibly Automation Anywhere. I have seen most of the users clinging to Power Platform in terms of ease of use, usability, and ease of doing any sort of development from their perspective.

Automation Anywhere can be improved by adding more built-in models, especially for standards across countries such as the United Kingdom, India, and Japan, regarding the way of passports, the way of invoicing, and supporting double-byte languages. More built-in models should be there instead of relying on custom models. Today, they are very good, but somehow they are not going to help or support our client engagements completely. We have to build a custom model. If we had specific models, country-specific, supporting every standard one, such as US passport or India passport, and supporting double-byte languages, more product capabilities would be exposed to the outside world and more users of Automation Anywhere bots across the world would benefit. I see this as an area where UiPath has advanced because they have good built-in models that you can train and retrain. I have seen one or two customers switching from Automation Anywhere to UiPath just because of the many built-in models available. If Automation Anywhere has this, I think the product will be very complete. I am sure the product team will be considering these facts based on customer feedback from organizations and partners.

I don't think any customer has asked for something which Automation Anywhere has not supported. I am just thinking about what could be the best improvement. Everything is there. Readymade solutions are available in the marketplace. Document understanding is there. Models are there, and you can develop and customize. Automation Anywhere also has IDP, though I think IDP needs some improvement.

I have been dealing with Automation Anywhere for almost three and a half years, almost three and a half years.

I would rate their technical support as nine out of ten. They are very quick and they go deep into troubleshooting. They come up with resolutions. I have not had to contact support more than five times in my time with Automation Anywhere, but whatever I have done or interacted with the team, I think they are very good. They consult deeply, get the logs, troubleshoot the diagnosis, use the diagnosis report, and then they are able to resolve it quickly. The support has always been good.

The deployment of Automation Anywhere is not at all complex; it is very good. We deploy bots gracefully and we do not have to take down anything. Everything is done through our DevOps. We do it without disrupting the business. It is mostly a graceful method that we have adopted and we are continuing to do this because nothing has impacted us. There are some things one or two here and there, but overall, it is very good in terms of deployment and not disturbing the business.

Automation Anywhere has helped me save time and costs. I think there is great value, especially from a developers' perspective when they are working on very strong, complex automation projects. We see how Automation Anywhere helps us in terms of spinning up the bots. The workload management is very perfect. I know this is a feature that has been around for a while, but it is helping me to manage the work because we have the multi-bot architecture concepts here where multiple bots work together. The whole thing is very helpful and quite helpful. I am very excited to use that technology everywhere in every organization wherever I am working with the client ecosystem.

I find the pricing of Automation Anywhere reasonable because of the value it brings to the table, the features, the capabilities, and how it supports the business processes, workflows, and the needs of the business and the client. I think it is worth the pricing. The features, the product capabilities, and how it benefits the customer is more important than the cost, considering the ROI. It is worth it based on its value and business value.

I would rate Automation Anywhere overall as nine out of ten. Automation Anywhere is undoubtedly the pioneer in the market. All three that I have experienced are the contenders, and in fact, the Microsoft platform also, I would rate it as nine out of ten. All of them I rate nine out of ten—not just Automation Anywhere, but all of them—because I have seen them through my own experience and I have interacted and used them in my career with several organizations and client organizations. Some people are interested in Blue Prism, some in Microsoft Power Platform, some in Automation Anywhere, and some in UiPath. It is all based on how they want to proceed and based on the business case they have done for their organization. I would rate all four of them as nine out of ten because they are supported for every need.

With my experience on RPA solutions specifically, I have completed projects on Automation Anywhere, and my enterprise company has now moved to Blue Prism; so we are currently using Blue Prism for RPA. I can provide a brief of what we accomplished with Automation Anywhere.

Our use of Automation Anywhere was to handle a test case where a ticket came in each day, possibly overnight. There was a job that we ran specifically on our Linux machines to upload the assumption files, which was a repetitive task. Although we had a script on the Linux box, someone had to come in and process the Jira workflow manually by approving the ticket. The ticket came in from the outsource party with a data set and a zip file. We created a workflow in Automation Anywhere where it would open the web page, access the vault, get access to Jira, and input the Jira credentials. If the ticket was in an approved state, it would start pulling the zip file and download it on the Windows machine. The bot would perform validation checks on the zip file and then open PuTTY on the same Windows machine to obtain the credentials, log into the system, and run the shell script for assumption load, passing the data set coming in from the Jira API. The data set was downloaded to the Linux box. After we obtained the data set, we ran the script execution on Automation Anywhere, which loaded the file on the system. If the validation was approved, it would open the browser again, use the Jira ticket, close it with specific comments that the task was complete, and send a notification to the end user. This was one test case; we had modules for Jira and Linux that consumed most tasks. Different scenarios required changing the scripts for different purposes such as loading assumptions or restarting applications. We scheduled tasks on Automation Anywhere to run daily and check the Jira API, running only if the workflow was open.

The initial deployment of Automation Anywhere is user-friendly. If you have self-learning capability, the wizards are self-explanatory, making it not very difficult to navigate. It is a very low-code environment, allowing flexibility to explore based on the project's complexity. Overall, I believe Automation Anywhere is a very user-friendly tool.

In terms of user-friendliness for non-technical users, the wizard is self-explanatory. Non-technical users, such as those involved in Excel automations or HR roles, can handle their tasks easily. Some tutorials available through YouTube can help guide them, and I find that the terminologies used in Automation Anywhere, such as Control Room, are also self-explanatory. Users can simply take an Excel file and run the rules without much difficulty.

One thing I dislike about Automation Anywhere is that our process is time-consuming. Since the bot is utilized by that machine and if a long-running task is happening, then another bot may not run and the machine is locked. We had to provision multiple machines to avoid deadlocks. This might be an issue with all RPA solutions, but it could have better handling if an existing lock allowed a second bot to provision and take requests. Because our infrastructure is idle in that case, we must bring up more infrastructure, and if there's a bottleneck, the bot is idle, waiting for the Linux process to complete. This is a challenge we faced, particularly during peak load.

Cost is another concern since we moved to Blue Prism, which is more expensive due to needing more VMs, bots, and capacity, which led us to procure more licensing. While Automation Anywhere was used efficiently and was cloud-based, software installation on Windows VMs was an overhead. Moving to the cloud for a web-based solution would allow for no software requirement on the system, which is a more modern approach compared to installing software on machines that require maintenance and consistent configuration.

One area for improvement would be the licensing, making it more cost-effective. The other issue involves security, particularly with password flags. I faced challenges in troubleshooting when providing passwords through the vault, as I could not secure a valid log to see whether the password was correct or incorrect. Log management could be enhanced, and regarding troubleshooting, since I utilized API calls with Jira and a PuTTY session, tracking failures in one of the processes was difficult. The log management needs to improve to identify the root cause of failures.

Regarding the duration it takes to train non-technical employees on using Automation Anywhere, we provided documentation and instructions. Employees reviewed them along with YouTube or external links to start automation, beginning without needing technical support from our team. There were sessions around it, but I do not believe they required much assistance apart from the provided instructions and tutorial guides.

I have used Automation Anywhere on projects throughout my experience with RPA solutions.

Concerning stability, while I have not seen substantial lagging, crashing, or downtime, performance could be an issue, especially since our jobs take longer. It might be a performance issue on our system or possibly Automation Anywhere not being lightweight. I do not believe the tool itself is heavy; it primarily acts as an orchestrator while the actual jobs run on the machines. However, the tool does block the VM, hindering the utilization of CPU and memory when the bot runs a job. If another job tries to come in at the same time, it complicates the situation.

Automation Anywhere should be resilient enough to provide automation at scale. I know there is an AI bot that we have not leveraged yet, but it should be efficient for capacity jobs. For example, if I receive multiple tickets for loading assumptions simultaneously, I would not want a single bot to complete the task in six hours. The AI bot could recognize multiple pending jobs and scale up the bots to execute them efficiently in parallel.

One thing I dislike about Automation Anywhere is that our process is time-consuming. Since the bot is utilized by that machine and if a long-running task is happening, then another bot may not run and the machine is locked. We had to provision multiple machines to avoid deadlocks. This might be an issue with all RPA solutions, but it could have better handling if an existing lock allowed a second bot to provision and take requests. Because our infrastructure is idle in that case, we must bring up more infrastructure, and if there is a bottleneck, the bot is idle, waiting for the Linux process to complete. This is a challenge we faced, particularly during peak load.

I have not had to contact technical support personally, as we managed to handle most things independently. Although we experienced Jira API issues, it was not related to the tool itself; we utilized a different token authentication and did not face significant issues.

I have used Blue Prism as one of the major RPA giants and an alternative to Automation Anywhere.

When comparing them, I find that Blue Prism has more complexities. It depends on the use case; for a very complex architecture or hardcore coding, Blue Prism is preferable. Otherwise, in a low-coding environment where a developer is not needed, I prefer Automation Anywhere because it enables non-IT users to leverage it effectively.

The initial deployment of Automation Anywhere is user-friendly. If you have self-learning capability, the wizards are self-explanatory, making it not very difficult to navigate. It is a very low-code environment, allowing flexibility to explore based on the project's complexity. Overall, I believe Automation Anywhere is a very user-friendly tool.

Cost is a concern since we moved to Blue Prism, which is more expensive due to needing more VMs, bots, and capacity, which led us to procure more licensing.

I have used Blue Prism as one of the major RPA giants and an alternative to Automation Anywhere.

When comparing them, I find that Blue Prism has more complexities. It depends on the use case; for a very complex architecture or hardcore coding, Blue Prism is preferable. Otherwise, in a low-coding environment where a developer is not needed, I prefer Automation Anywhere because it enables non-IT users to leverage it effectively.

As for the overall learning curve for Automation Anywhere, I think it is not difficult. However, when adding more complexity, there is a limitation. In a low-code environment, if you need to incorporate more complex logic, you require a coding environment to run some code against it.

I have not used what is called Automation Co-Pilot, previously known as ARI. However, I have utilized GitHub Co-Pilot and I assume that the Co-Pilot would be a self-learning AI bot. It would learn from inputs and make better decisions with each learning curve, similar to how we use GitHub Co-Pilot, which prompts based on our codebase.

Overall, I would give Automation Anywhere a score of eight. I find that an eight is a fair representation of the experience.

My main use case for Automation Anywhere includes automating disputes, due diligence, anti-money laundering, mainframes, all kinds of customer information, mainframe, Excel, Outlook, SQL, web interface, and various other processes.

One specific example of a process I have automated with Automation Anywhere is when we receive a bunch of disputes that need to be recorded in the system. I check the mainframe, take some screenshots, update the screenshots in the system, go to the Visa website to make sure these transactions exist, take the transaction history of it, upload it to the same system, and log these cases, ensuring the dispute cases are logged, recorded, and reported.

We utilize document automation in our current processes and it has positively impacted our efficiency and productivity. We really like using it because it is efficient.

The best features Automation Anywhere offers include good support, a lot of good tools, many features and functionalities, document processing, and various other capabilities.

The document processing feature has helped my team by ensuring that when documents are clear, sanitized, and structured, it is able to pick up all the information and put it in the format that we are looking for. However, if documents are scanned and not clear, the accuracy is not up to the mark. We cannot use GenAI because we are not on the cloud yet, but other than that, document processing is a really useful tool.

Automation Anywhere has positively impacted my organization by saving millions of dollars over the past several years since we implemented it, along with saving a lot of hours, achieving a lot of ROI, realizing a lot of value, and significantly reducing urgency and stress. People can now focus on meaningful work rather than sitting and doing repetitive, mundane tasks.

I believe that per year, we save at least 50,000 hours.

One way Automation Anywhere can be improved is that transitioning from on-premises to cloud presents a challenge, so we are trying to work with security and integrate our security with Automation Anywhere security. Those parts need to be vetted out, thus requiring the right people and obtaining more information about the security piece to take things forward.

I have been using Automation Anywhere specifically for almost 11 to 12 years.

Automation Anywhere is stable.

The scalability of Automation Anywhere is good because we build our bots keeping scalability in mind and create a lot of reusables.

The customer support provided by Automation Anywhere is excellent.

I would rate the customer support a 10 on a scale of 1 to 10.

Based on my overall experience so far, I would rate their customer support a 10 on a scale of 1 to 10.

I previously used a different solution, which was manual.

I have seen a return on investment with Automation Anywhere, including money saved, time saved, and overall satisfaction. People are happy and things are working as expected, doing what they are supposed to do while creating less headache, less monitoring, and less heartache.

My experience with pricing, setup cost, and licensing is good. We were able to work out a great deal with our account managers and I am happy with what we got.

I evaluated other options before choosing Automation Anywhere.

The other option I evaluated before selecting Automation Anywhere was UiPath.

Automation Anywhere is deployed in my organization on-premises.

Automation Anywhere has helped me achieve my automation goals by allowing us to automate a bunch of different business processes and leverage a variety of features it offers. I have been able to automate Excel, mainframe, web-based applications, and in-house applications without needing to do anything outside of Automation Anywhere.

We use Automation Anywhere's Center of Excellence partly, as we have our own version of it. We can break everything out between dev, test, and prod, and we have Jenkins, Jira, and ServiceNow all tied together and integrated.

I rate Automation Anywhere a 10 because it has always provided great support and we have always received valuable information. Whenever we are stuck, we reach out to Automation Anywhere and they always provide us with the right direction and guidance, always helping us out even in tough situations, allowing us to figure out and resolve most of our automated processes. We have not encountered anything so far that was not automatable, or we have utilized hybrid automation methods like APIs, .NET code, JavaScript, or Python, enabling us to handle most of our use cases without seeking out a different vendor.

My overall rating for this review is 10 out of 10. The advice I would give to others looking into using Automation Anywhere is to go for it.

The use cases are majorly insurance-related or finance-related. I work for a finance-based company, and the use cases are primarily money movement use cases involving financial and insurance-related operations.

Since business users are only running the automations, it is not very difficult for them. For a few users, I had to explain how to get inside the machine and how to trigger the automation in the case of attended execution, where they were running the automations by themselves. Apart from that, there were no major things that needed to be handled by the end-users, so those were pretty easy for them.

In the user's case, as they do not have many things in their hands, I would say the learning curve is pretty flat. They were only running the automation and did not learn anything apart from just triggering the bot. There was not much to learn in the user's case.

In most of the use cases, both time and cost are being saved. That is the reason they are using these automations.

Considering the current era where people are moving towards APM and Agentic automation, I see other rival tools are launching more and more products. If you talk about UiPath, they have Test Suite or UiPath has lots of AI-related models. I would say considering the current scenario, there is scope to improve for Automation Anywhere.

When it comes to integration with AI models, I have been on a maternity break, so I am not currently very much in touch with the models of UiPath or Automation Anywhere. What I have been seeing on LinkedIn or listening to people say is that UiPath has more of the AI or APM-related tools with more integration and inbuilt integration with AI, whereas Automation Anywhere has just started launching this. There is room for improvement in this area.

I would rate the room for improvement as eight. The only scope of improvement I see right now is when it comes to APM or integration with AI. Apart from that, it has been the best for me so far, and it is easy to learn and pretty self-explanatory.

I have been working with Automation Anywhere for almost eight plus years now, since 2017.

We did face some issues last year when there was an upgrade in Automation Anywhere control room, and at that time our web application automations were failing. We had to downgrade the version to the previous version. That was the only issue I faced when it comes to stability. Apart from that, I have not seen any major issues. There were a few during migration, but overall, it is pretty stable.

The problem was fixed when we reported the issue to Automation Anywhere team. They fixed the issue within two or three days. Meanwhile, we had to downgrade our software version, and then it was working. Once the issue was fixed, we upgraded it to the correct patch.

I would say it is pretty good. Since I have been working with Automation Anywhere from version 10x, and now we are at A360, I have seen Automation Anywhere evolving. There were lots of limitations with version 11 before when we had a desktop version. Now we have multiple things integrated. When it comes to SAP, you do not need to use Metabots or external things. You have everything inbuilt. It is pretty scalable. You do not really need to rely on external components. You have everything inbuilt whether you are talking about Salesforce or anything else. I would say it is pretty helpful in building scalable solutions.

I would rate Automation Anywhere customer service ten out of ten because whenever I have reached out to Automation Anywhere, I have always been supported by those people. No matter if the issue was on their side or our side, the support team has been the best so far.

Positive

I started my career with RPA and then Automation Anywhere. Apart from Automation Anywhere, I have worked with other RPA tools as well, such as Power Automate or UiPath. I have also used Python for a few automations. However, it has been majorly Automation Anywhere for me.

The initial setup is pretty straightforward. From Automation Anywhere, I did not really face any issues. Whatever issues there were, those were majorly application-based, such as changing the environment or things of that nature. From Automation Anywhere side, the deployment was pretty easy. From the tool end, I have not really faced any issues. I have worked on the V11 to A360 migration as well. There were no major issues. Whatever issues we face during deployment are mostly from the system perspective, such as environment perspective or system perspective.

The implementation team consisted of more than 100 people.

I am not really sure about the ROI because that is being handled more on the business side. I am more of a developer, and these things are being taken care of mostly by a business analyst or product owners, so we do not really have access to that information. If it comes to time, for one use case, if they were taking 48 hours for 20 transactions, now that is being done in two to three hours by automating that operation. When it comes to ROI, I am not really sure about that since it is being handled at a high level.

In my organization, we are not really using Automation Co-pilot. We are using simple automations for now.

In my system, mostly those are inbuilt tools only and inbuilt applications. If I talk about generic tools, those are Excel, a web application, or Salesforce, and then SAP is there. Mainframe is there as well. Apart from that, whatever tools are company-built or private to the company are being used.

My overall review rating for this product is eight out of ten.

As an engineering company, we face several challenges in supply chain management, particularly from order processing to delivery, and that's where we would like to automate different operations that human users are manually doing.

We are exploring more agentic solutions to address these problems.

I appreciate Process Composer the most with Automation Anywhere, and now we have an enhanced version called Mozart Orchestrator, which I am glad to see represented in the Imagine session today, along with our product leaders discussing this powerful orchestration capability.

In general, the benefits of Automation Anywhere's automation are diverse. It is not just about saving time or reducing FTEs, as our customers benefit from structuring and formalizing their processes, while others gain compliance through automation.

The flexibility of Automation Anywhere's truly universal orchestration in integrating with different systems and models is assessed by the capabilities offered in the Orchestrator, whether it be Mozart Orchestrator or the previous version, as its ability to connect to various ERP applications and manage different data types ultimately provides us with the benefits.

In thinking about what improvements I would suggest for Automation Anywhere, I appreciate their vision and remain interested in their product roadmap. I wish to see more adaptation to trending technologies that we currently have.

I work as the Automation Service Manager in Bangalore, where we have been using Automation Anywhere for eight years.

To assess the stability and reliability of Automation Anywhere, we measure success through captured insights, which we collect after deploying automations, typically via an external dashboard or the bot insight dashboard that provides information for continuous improvement.

In our organization, we have used Automation Anywhere for eight years, and we have experienced notable growth in terms of production solutions and ROI, demonstrating excellent scalability to meet different functions and units within our business.

My experience with Automation Anywhere's customer service and technical support is notably positive. I have closely interacted with their support team over the years, especially since we were early users of product document automation. I appreciate the timely support and improvements made to the product since then, leading me to give a rating of nine out of ten.

I started my career with Automation Anywhere and have not used another solution for similar needs.

In deploying Automation Anywhere solutions, I have experienced significant evolution over the past eight years. Initially, it was a client-server model that made deployment challenging, but now we benefit from the first ever cloud-based RPA platform, which has greatly enhanced our flexibility in solution deployment.

I can confirm that we have seen a return on investment with Automation Anywhere. At our organization, we deal with various business units and functions, deriving different benefits and business value, although I cannot disclose specific numbers.

Regarding my experience with the pricing, setup cost, and licensing of Automation Anywhere, I have some concerns about the product licensing model.

As one of the MVPs, I recently discussed the rigidity of the licensing model which has been packaged without the necessary flexibility for customers who can fund certain products but not the enterprise platform license.

We have evaluated other solutions besides Automation Anywhere in the past, but it was about four to five years ago. Although the tool's evolution has been significant, Automation Anywhere consistently came out on top during our assessments.

In my evaluation process of Automation Anywhere compared to other options, I focus heavily on cost, flexibility, and capabilities. From a cost perspective, Automation Anywhere wins, and at the time of assessment, we were awaiting additional capabilities that have since been addressed.

Regarding Automation Anywhere's deterministic and agentic blended execution feature, I do not believe this applies to our current needs.

To prevent infinite loops and retries in Automation Anywhere's deployment, we have different methods in place, including technical logics in if conditions and a powerful error handler that allows us to implement those logics.

Assessing the capabilities of Automation Anywhere's Automation Process Architecture (APA) in improving orchestration for AI projects involves considering factors such as flexibility, the outcomes we achieve, and the different types of integrations the Orchestrator supports that can benefit various businesses.

The option to buy, build, or bring your own tools and models significantly influences our organization's automation strategy. We have certain restrictions due to varying organizational alignments regarding model usage, especially since we are in the AI era with numerous LLMs emerging, and it is crucial to have flexibility in products such as Automation Anywhere's buy your own model.

Centralized governance across agents and systems enhances consistency in operations by prioritizing security, particularly for PII and PHI data. Having centralized governance aids in consolidating sensitive data onto one platform, enabling useful reporting and making it easier to convince the leadership team with the insights we capture.

I rate Automation Anywhere an eight out of ten because while I appreciate the platform, I expect more flexibility in capabilities and licensing models.

I strongly recommend Automation Anywhere as a compelling platform for RPA needs. I particularly value their university and open courses that enable even freshers without technical backgrounds to grasp the technology easily, which I find lacking in other tools in the market. Once learning is accomplished, Automation Anywhere demonstrates strong capabilities for current market integration and adoption.