Automation Anywhere

Your first use case shapes what happens next. Choose something easy to demonstrate and you may prove the technology. Choose work that matters and you can build the case for change. Download the Playbook to choose where to start.

A routine software request can trigger more work than the employee ever sees. Behind the scenes, checks, approvals and provisioning add time and cost before access is delivered. Download the Playbook to put a value on that operational effort and build the case for auto-resolution.

Deflection can improve the numbers without solving the problem. The conversation ends, but the employee may still be waiting for access, software or a fix. Download the Playbook to move ITSM from ticket deflection to end-to-end resolution.

Most companies already have a growing list of ideas for AI agents. The difficult part is working out which ideas are actually worth pursuing. In conversations with customers and prospects at Automation Anywhere, the challenge is rarely a shortage of ideas. It’s deciding where AI can make a meaningful difference. “Where can we use an AI agent?” sounds like a sensible question. But start there and you risk using expensive, variable technology for work that automation could already handle perfectly well. Or improving one task without changing the performance of the process around it. Before choosing the technology, there are four things I’d want to understand about the work: → The outcome matters Improving it would make a real difference to cost, revenue, risk, service or speed. → Exceptions keep changing the route The standard process works until something happens that sends it down a different path. → Decisions need context The next step depends on what has already happened, what the information means and, sometimes, a judgement call. → People are keeping the process moving They move between systems, bring information together and sort out what the standard process can’t handle. An important outcome may justify investment. It doesn’t automatically justify AI. If the work follows stable rules, automation may be enough. If the route keeps changing and decisions depend on context, that’s where AI reasoning could help. If people are carrying information between systems, the bigger need may be orchestration. And some decisions should still belong to people. Start with the whole workflow. Then choose the right approach for each part of it.

This week I had a chance to speak at the #CitiTMTConference in New York alongside technology management teams and software analysts from across the industry. Not surprisingly, AI and ROI led most conversations. Here's how I explained our positioning around it. I believe Automation Anywhere solves the biggest problem today in the AI industry: the increasing gap between AI investments and the level of autonomy AI delivers. We know from past revolutions such as electricity and the Internet that technology alone doesn’t create economic benefit. What creates the benefit is the ability to deliver autonomy, and thus change the business model. This is what we believe in. Automation Anywhere stands for Autonomous Work... work that completes itself. Historically we did this with token-less technologies like RPA, APIs, machine learning, etc. About three years ago we launched a series of AI products that are based on generative AI. That accelerated our growth. Today, customers combine our token-less and generative AI technologies both to achieve superior outcomes. About 70% of our business today is led by our AI product line. We are AI-first, but not AI only - you don't need to lead with probabilistic in every scenario. Today we have three offerings to drive Autonomous Work for the enterprise: 1. We believe we have the #1 agentic automation platform for AI agents to reason, make decisions, and execute end-to-end processes autonomously. They are governed, secure, and allow customers to build agentic solutions to orchestrate workflows, all deployable within a week. 2. On top of our agentic platform, we also have proven out-of-the-box agentic solutions for specific business critical processes in Finance, IT, HR, Support, etc. represented across large verticals like BFSI, Healthcare, Manufacturing and more. Our solutions in Finance for processes such as Procure-to-Pay and Order-to-Cash are examples that I'm excited about. 3. For those with the strongest commitment to transformation, we offer an Autonomous Enterprise approach that fundamentally transforms the operating model, using our agentic platform, solutions and FDEs to drive 50-80% autonomy for a function end-to-end. This model decouples SaaS tax from growth so you don't pay more software licenses as you scale, and also delivers 3x employee productivity. It is how true leaders get ahead of the competition. With 450M+ AI agents and automations executed annually with our customers, we know we can close the autonomy gap as quick as anyone to unleash this powerful technology to transform work and deliver meaningful ROI.

AI agents need room to act. They also need clear limits. Leaders need to define what can proceed, what needs human judgement and what must remain visible from decision to outcome. The CIO’s Guide to Orchestrating Enterprise AI shows how to build those boundaries into the operating model.