RPA vs AI agents: what RPA software does, how agents differ, and when to use each

RPA, short for robotic process automation, is software that repeats the steps a person takes on a screen, such as copying fields from a spreadsheet into an ERP, following rules set in advance. An AI agent reads a request, such as an emailed order, and decides its own steps. RPA fits stable, high-volume tasks with structured data, an agent fits work with documents, exceptions and judgment, and the two can run together. This guide explains both in plain words, compares UiPath, Microsoft Power Automate and Automation Anywhere from their own pages, and shows when a smaller manufacturer or distributor should keep RPA, replace it or combine it with an agent.

Derik Lawlis Founder, ThriveAI

What RPA is

UiPath says robotic process automation “uses software robots to automate repetitive, rule-based tasks like data entry and system integration,” and that “it mimics human actions in digital systems” (UiPath). A software robot, or bot, is a program that clicks, types and copies on a computer the way a person would. Nothing physical moves.

A bot follows a script someone built in advance: open this screen, copy this field, paste it there, press Save. Microsoft’s Power Automate lets you build that script from prebuilt drag-and-drop actions or by recording your own steps, and its bots can work “application UI elements, images, or coordinates,” including legacy applications such as terminal emulators (Microsoft). A terminal emulator is the text-only window that some older ERP systems run in.

UiPath says RPA “excels at automating high-volume, repetitive, rule-based tasks, especially those that span multiple systems.” Automation Anywhere adds that because RPA is “inherently rules-based,” automations follow “policies and protocols exactly while generating a complete audit trail” (Automation Anywhere).

Attended and unattended bots

Automation Anywhere describes two kinds of bot. Unattended automations “use pre-programmed triggers, data inputs, and schedules to run independently, without human intervention,” usually for back-office work such as data entry. Attended automations help a person with routine tasks on demand, on that person’s own computer. Microsoft licenses the two differently, as its entry below shows.

RPA software compared

The three vendors below sell RPA, and each now sells AI agents alongside it. Each entry reports what the vendor says on its own pages as they stood on September 28, 2026.

UiPath

UiPath describes RPA as “the execution layer for agentic automation, turning the plans and reasoning of AI agents into tangible actions.” In its words, “Agents handle sophisticated problem solving and adaptation; RPA ensures reliable execution across enterprise systems; and people provide oversight and direction” (UiPath).

How UiPath charges: UiPath’s pricing page lists a free Community plan, a Basic plan priced per month and hosted in its European region, and Standard and Enterprise plans priced through its sales team. Standard can be hosted in one of UiPath’s regions or on your own premises.

Microsoft Power Automate

Microsoft calls its bots desktop flows. They “broaden the existing robotic process automation (RPA) capabilities in Power Automate,” and Microsoft’s examples include an employee who “automates data entry on an ERP system” (Microsoft). Cloud flows connect cloud apps, and desktop flows work the screens of programs on a Windows computer. For AI agents, the Power Automate pricing page lists Copilot Studio, which AI agent builder platforms covers.

How Microsoft charges: Microsoft’s pricing page sells attended desktop flows in the Premium plan, priced per user per month, and unattended desktop flows in the Process plan, priced per bot per month. A Hosted Process plan, also priced per bot, adds a virtual machine that Microsoft manages on Azure.

Automation Anywhere

Automation Anywhere calls RPA “software that automates digital tasks quickly and reliably” and sells it with what it calls agentic process automation, in which RPA “provides the execution layer agents can call on to perform tasks quickly and accurately at scale.” The same page says that without its agentic and AI tools, “RPA can only operate effectively with structured data,” and that business applications “evolve in ways that disrupt rigid, rules-based RPA.” Its answer to the second point is Automator AI, which it says builds automations “that adapt to application UI changes” (Automation Anywhere).

How Automation Anywhere charges: its editions comparison link leads to a demo request with its sales team. A free Community Edition lets students and developers build automations, and a small business may use it on no more than five machines.

How AI agents differ from RPA

OpenAI defines agents as “systems that independently accomplish tasks on your behalf,” and says they suit work “where traditional deterministic and rule-based approaches fall short” (OpenAI). Deterministic means the same input always gives the same output, which is how an RPA bot behaves. The table sets the two side by side.

An agent can also work a screen the way a bot does, through computer use, where the model reads screenshots and clicks. Anthropic’s computer use documentation warns that this “might be too slow compared to regular human-directed computer actions” and that the model “might make mistakes or hallucinate.” A bot on a stable screen is faster and repeats itself exactly.

When to keep RPA

If a bot works, rarely breaks and handles clean inputs, keep it. OpenAI’s guide says that when a job does not need an agent’s judgment, “a deterministic solution may suffice,” and Anthropic recommends “finding the simplest solution possible” (Anthropic). RPA fits when:

• The input is structured, such as a spreadsheet export or a fixed form.
• The screens rarely change.
• The steps are the same every time, with few exceptions.
• The volume is high enough that speed and identical results matter.
• An auditor needs the exact same steps on every run.

When an AI agent replaces RPA

An agent earns its place where the bot keeps handing work back to people. OpenAI’s guide points to three situations: decisions that need judgment and handle exceptions, rule sets that have grown too large to maintain, and “heavy reliance on unstructured data.” At a manufacturer or distributor, the signs are:

• Orders, invoices or requests for quote arrive as emails and PDFs in many layouts, and the bot needs a person to type them into a spreadsheet first.
• A large share of runs end in an exception queue that a person clears by hand.
• The bot’s rules keep growing, and each new customer layout means another rule.
• The screens change often enough that someone spends every month repairing scripts.

Before you retire a bot, run the agent beside it on the same set of past cases and compare the results field by field. AI evals explains how to build that test, and AI agents for business covers the guardrails an agent needs before it touches your ERP.

How RPA and AI agents combine

UiPath and Automation Anywhere both describe RPA as the layer that carries out the steps an agent decides on. Three patterns follow from that:

• The agent reads and the bot keys. The agent turns an emailed purchase order into structured fields, a person approves them, and a bot keys them into the ERP screens it already knows.
• The bot hands exceptions to the agent. When a bot hits a case its rules do not cover, the agent drafts a resolution for a person. UiPath’s own example routes a price mismatch or an out-of-stock item to a human, then resumes the automation once the issue is cleared.
• The agent works the screens where no bot exists. For an older ERP with no API and no bot, a computer use agent can read and fill the screens itself, with a person confirming each change. Legacy ERP automation explains that setup.

What this means for a smaller manufacturer or distributor

If you have no RPA today, start from the job. Pick one task, check whether the systems it touches have an API, and look at the inputs. Clean, structured inputs on a stable screen point to a bot. Emails, PDFs and exceptions point to an agent, with a person approving what it drafts. A job can use both: the agent reads, a person approves, and a bot or an API does the typing.

How to build an AI agent covers the steps and timeline for an agent, and AI agent builder platforms compares the tools, including Microsoft’s Copilot Studio.

How ThriveAI helps

ThriveAI is an AI engineering company in Ottawa. It builds private AI systems on the client’s own data for manufacturers and distributors in Ontario and Quebec, including computer use agents that work the screens an older ERP leaves over, with nothing saved until the person responsible approves it, as legacy ERP automation describes. Derik Lawlis, the founder, leads every project and stays close to the build.

The platform is designed to keep each client’s data on its own server in Canada. You choose the model: one that runs on that server, or a hosted model under a written zero data retention agreement, under which the provider keeps no copy of a request or its answer. A hosted model may process requests outside Canada, so the contract names the model. A named person at your company approves every action before anything is sent or saved. About ThriveAI covers the company.