Automation Anywhere is one of the three dominant legacy RPA vendors alongside UiPath and Blue Prism. They've been in the market since 2003, they're publicly traded, and they've invested heavily in adding AI capabilities to their platform over the past two years.

So why are operations teams that already use Automation Anywhere (or are evaluating it) increasingly looking at AI-native alternatives?

This comparison breaks down the real differences. Not feature checklists. The structural decisions that determine whether your automation program succeeds at scale or gets stuck in a maintenance loop.

Architecture: the fundamental difference

Automation Anywhere's platform was built on selector-based execution. Bots interact with applications by identifying UI elements through their HTML properties, accessibility attributes, or object model. AI features (IQ Bot for documents, automation co-pilot) are layered on top of this foundation.

Automat was built from the ground up around AI computer use. Bots interact with applications visually using vision language models that see and understand screens the same way a human does. There is no selector layer. The AI is the execution engine. For a deeper look at this architectural shift, see AI RPA vs traditional RPA.

This architectural difference affects everything downstream: what you can automate, how fast you can deploy, and what maintenance looks like.

What you can automate

Automation Anywhere handles web applications and standard desktop apps well through its Bot Agent technology. For legacy systems like Citrix, SAP GUI, and mainframe terminals, it offers specialized connectors and an image recognition engine.

In practice, these connectors have limitations. SAP automation requires scripting to be enabled server-side. Citrix image recognition is fragile and breaks when resolutions or themes change. Mainframe automation depends on terminal emulator APIs that vary by vendor.

Automat's vision-based approach handles all of these environments through the same mechanism: looking at the screen and interacting with what it sees. SAP, Citrix, web portals, government websites with CAPTCHAs, desktop applications. The platform doesn't need a specialized connector for each environment because visual interaction is universal. (Read more about automating SAP and Citrix without APIs.)

Deployment speed

Automation Anywhere provides a development environment (Automation 360) where developers build bots using a drag-and-drop interface or code editor. A typical enterprise workflow takes 2-4 months from process discovery through production deployment.

The development cycle involves: process analysis, bot development in the AA studio, testing in staging, user acceptance testing, and production rollout. This requires trained AA developers or certified partners.

Automat compresses this to days or weeks. You share a screen recording or SOP. Forward-deployed engineers (Automat's team, not yours) build and deploy the automation. There's no development environment for your team to learn. No certification required.

Maintenance and total cost

Automation Anywhere's licensing runs $750+ per bot per month, with additional costs for IQ Bot (document processing), process discovery, and enterprise features. But licensing is only part of the cost.

The real expense is the team. Most AA deployments require:

• 2-5 certified RPA developers ($130K-$170K each)
• A Center of Excellence lead
• Ongoing infrastructure management (Bot Runners, Control Room)
• External consultants for complex workflows

Maintenance typically consumes 50-60% of total program effort because selector-based bots break when target applications change.

Automat operates as a managed service. There is no Center of Excellence to build. No developers to hire. No infrastructure to manage. The platform self-heals when UIs change, and Automat's engineers handle production reliability. The total cost of ownership is typically 5-10x lower than a comparable AA deployment.

Document processing

Automation Anywhere offers IQ Bot for intelligent document processing. It's a capable tool but it's a separate product with separate licensing, a separate training interface, and a separate integration layer. Building a workflow that combines UI automation with document extraction requires wiring two products together. (For more on this challenge, see our comparison of Automat vs ABBYY.)

Automat handles document processing natively. The same vision models that navigate screens also read and extract data from documents. PDFs, scanned images, handwritten text, mixed-format packages. It's a single platform, single workflow, single deployment.

When Automation Anywhere makes more sense

Automation Anywhere is a strong choice if:

• You already have a mature AA Center of Excellence with trained developers
• Your automations are primarily web-based with stable UIs
• You need deep integration with the AA ecosystem (process discovery, analytics)
• Your organization requires an on-premise deployment and AA's infrastructure model fits

If your challenge is legacy systems without APIs, document-heavy workflows, maintenance overhead, or you don't want to build an internal RPA team, the AI-native approach addresses those problems structurally rather than through additional features and consultants.

Frequently asked questions

Can I migrate existing Automation Anywhere bots to Automat?

The bots themselves don't transfer (they're built in AA's proprietary format), but the process knowledge does. Automat rebuilds workflows from recordings or SOPs in days rather than the months the original AA development took.

Is Automat as secure as Automation Anywhere?

Yes. Automat is SOC 2, HIPAA, GDPR, and ISO 27001 certified. Both platforms meet enterprise security requirements. Automat also offers on-premise deployment for organizations that require it.

Does Automat have a process discovery tool like AA?

Automat takes a different approach. Rather than mining event logs to discover processes, you share what you want automated (recordings, SOPs, descriptions) and Automat's engineers build it. This is often faster than running a multi-week discovery phase.