3-year TCO by scale, same per-process shape
Same license/implementation/maintenance assumptions, scaling only the number of processes.
| Processes | RPA 3-yr | AI agent 3-yr | Соотношение |
|---|
The license floor vs the usage curve
Traditional RPA licenses a robot, not a result — UiPath and Automation Anywhere charge a fixed annual seat fee per bot (roughly $1,500-2,000/year attended, $6,000-9,000/year unattended at list price) whether that robot processes 100 transactions or 100,000. On top of the license sits an implementation cost per process, because each RPA workflow is built against a specific UI, and then an ongoing maintenance bill that independent analyses put at 20-30% of the original build cost every year — the direct consequence of bots breaking whenever a vendor changes a screen layout, button ID, or HTML element the recording relied on.
AI agents flip both cost shapes. There's no per-seat license: you pay per API call, so the bill tracks actual transaction volume instead of robot count. Implementation is typically lower because there's no brittle UI recording to build, and maintenance runs roughly half of RPA's — 10-15%/year — since an agent interpreting intent from a natural-language instruction doesn't silently break when a vendor redesigns a page. That combination is why organizations migrating from RPA to AI agents have reported around 40% lower total cost of ownership within 24 months. The one place the math can flip back toward RPA is very high, stable transaction volume against a legacy system with no API and no interface drift — see the FAQ below. If you're separately estimating what the AI agent's own model calls will cost at scale, pair this with the Калькулятор стоимости AI-агента.
Калькулятор стоимости стека APIОценщик стоимости приложения AIКалькулятор стоимости LLM ObservabilityКалькулятор лимита ставки
Как работает этот калькулятор
- AI Agent vs RPA Cost Calculator models the full 3-year total cost of ownership for automating a set of business processes two different ways. For traditional RPA, it charges a one-time implementation cost per process, a recurring annual per-robot license fee, and an annual maintenance cost expressed as a percentage of the implementation cost — reflecting how RPA bots need re-work whenever the underlying application's interface changes. For AI agents, it charges its own (typically lower) implementation cost per process, its own (typically lower) maintenance percentage, and a per-transaction API cost that scales directly with your entered monthly volume instead of a fixed seat fee.
Year 1 includes the one-time implementation spend for both approaches; years 2 and 3 carry only the recurring license/maintenance/API costs. The comparison table below scales the same per-process assumptions across a range of automation counts, from a 10% pilot up to 10x your entered process count, so you can see whether the crossover point changes with scale.
Часто задаваемые вопросы
Why is AI agent TCO usually lower than traditional RPA?
Two structural differences compound over time. First, RPA bots break whenever a vendor changes a screen layout or HTML element they rely on for navigation, so RPA maintenance typically runs 20-30% of the original build cost every year just to keep bots working. AI agents interpret intent rather than fixed coordinates, so maintenance is usually 10-15% of build cost. Second, RPA charges a per-robot license fee (roughly $1,500-2,000/year for an attended robot, $6,000-9,000/year unattended at list price) whether or not that robot is fully utilized, while AI agents bill per API call, so cost tracks actual usage instead of seat count. Enterprises that migrated from RPA to AI agents have reported roughly 40% lower total cost of ownership within 24 months.
What exactly counts as an RPA license cost vs an AI agent API cost?
An RPA license is a fixed annual seat fee per robot (attended or unattended) charged by the vendor regardless of how many transactions that robot actually processes in a given month — you pay the same license whether the robot runs 100 times or 100,000 times. An AI agent has no per-seat license; instead you pay per API call/token consumed, so the bill scales directly with transaction volume. This calculator applies the RPA license as a fixed per-process annual cost and the AI agent cost as a per-transaction rate multiplied by your entered monthly volume.
Are these exact UiPath and Automation Anywhere prices?
The defaults are representative 2026 list-price ranges from public pricing trackers and vendor comparison sites, not a live price feed from either vendor — actual enterprise contracts are individually negotiated and often heavily discounted from list price, and both companies revise packaging periodically. Every field is editable: plug in your own quoted per-robot license, implementation, and maintenance figures for an exact number.
Why does RPA maintenance cost more than AI agent maintenance?
Traditional RPA bots automate by recording and replaying fixed UI interactions — specific screen coordinates, element IDs, or HTML selectors. When the underlying application updates its interface, which happens routinely with SaaS tools, the bot's recorded steps silently stop matching and the automation breaks until a developer re-records it. AI agents work from natural-language instructions and can adapt to a changed layout without being explicitly reprogrammed, which is why independent analyses put RPA's annual maintenance burden at roughly double an AI agent's for a comparable process.
When does traditional RPA still make sense over AI agents?
RPA remains a reasonable choice for high-volume, rule-based, rarely-changing processes on legacy systems with no API — think overnight batch reconciliation against a 20-year-old mainframe screen that never gets a UI refresh. In that scenario the fixed license cost gets amortized across enormous transaction volume and there's little interface drift to trigger re-work, which narrows or reverses the AI-agent TCO advantage modeled here. The calculator's per-transaction AI cost field lets you test that break-even point directly by raising volume until the two lines cross.