Context Rankings
Automation · Head-to-Head

Zapier vs. Make for AI Automation

Two automation platforms most teams are choosing between when they want AI in the loop. We built the same workflows on both, ran them at real volume, and priced out a year of bills.

Tested by Marcus Feld · July 2, 2026 · 4 rounds
Zapier
Zapier
2rounds
83 / 100 overall
vs
Make
Make (formerly Integromat)
2rounds
86 / 100 overall
The verdict

If a non-technical person on your team is going to own the automations, or you need an integration Make doesn't have, pick Zapier. It's the easier of the two to learn, the app library is much larger, and the built-in AI surfaces (Copilot, Agents, MCP) are the most polished on the market right now. If you have someone comfortable with a visual canvas and your workflows involve branching, iteration, or a lot of AI calls, pick Make. It runs roughly three to five times cheaper at equivalent volume, its scenario builder handles complex logic more cleanly, and its November 2025 move to let paid plans bring their own OpenAI or Anthropic key makes heavy AI workflows much cheaper to run. Both platforms shipped major pricing and AI changes in the last twelve months, and both are still moving. Re-check the numbers if you're buying for a team this quarter.

Most operations, marketing, and RevOps teams are choosing between these two in 2026. Zapier and Make have converged on the same broad pitch, connect thousands of SaaS apps, add AI into any step, and orchestrate agents that can act across your stack, so the question is no longer "which one does AI" but "which one does the work you actually do, at a price that survives contact with real volume."

We rebuilt the same four automations on both platforms and ran them for three weeks against the same data: a lead-routing workflow with AI enrichment (four action steps, ~1,000 runs/month), a support-ticket triage flow with sentiment branching and an AI-drafted reply, a batch document-processing scenario iterating over 500 rows, and a Claude-powered content pipeline calling an external model directly. We scored four rounds: how each platform handles the building experience for non-technical users, how each one runs branching and AI-heavy logic, what each one actually costs at three volume tiers after the 2025–2026 pricing changes, and how mature each one's AI orchestration story is today.

Round by round

Building experience for non-technical users
WinnerZapier

How we testedWe handed both tools to a marketing operations lead with no prior automation experience and timed how long it took to build the lead-routing workflow (trigger → enrich → score → CRM update → Slack notify → email). We also had her rebuild the same workflow from scratch a week later to test what actually stuck.

Zapier's form-based, trigger-then-action model is the easier of the two to pick up cold. Our tester had a working Zap in about ninety minutes; the same workflow in Make took closer to four hours, most of it spent learning the canvas, routers, and how bundles move between modules. That tracks with what other reviewers who run both find in practice: most new users need four to eight hours to build their first complex Make scenario comfortably, versus one to two hours in Zapier. Copilot, the AI-assisted builder inside every Zap, closes even more of the gap. Describe a workflow in plain English and it stubs it out for you, and it doesn't consume tasks. Make's Maia assistant is useful but less prominent in the editor. If the person building automations is a marketing manager or ops coordinator rather than a developer, Zapier's simplicity has real operational value.

Complex logic and AI-heavy scenarios
WinnerMake

How we testedWe built the support-triage flow (webhook trigger → AI classifier → route by sentiment → auto-reply on positive, escalate on negative, log both) and the batch enrichment scenario (iterate over 500 rows, call an LLM per row, aggregate, write back) on both platforms. We graded on whether each tool could express the logic natively, how legible the finished workflow was, and how easy it was to debug when the AI step returned something unexpected.

Make is built for this and it shows. The visual scenario builder puts routers, iterators, aggregators, and error handlers directly on the canvas, and the drag-and-drop builder animates the data flow in real time so you can see exactly what each module is passing to the next. When our sentiment classifier misfired on sarcastic tickets, we found the problem in a single pass through the execution log. Zapier has closed some of the gap with Paths, Looping, Sub-Zaps, and Custom Actions, and Zapier Canvas gives you a visual map of a business process, but stacking conditionals inside a Zap still feels like fighting the interface. Make's platform-level advantages here are real: routers, filters, bundles, and iterators are first-class primitives rather than features layered on top of a linear model.

Cost at real volume
WinnerMake

How we testedWe priced out three scenarios on both platforms at current published rates: a solo user running the four-step lead workflow at 1,000 runs/month, a small team running 6,000 tasks/operations a month across three workflows, and a heavier team pushing 15,000 tasks/operations a month with an AI step in most of them. We used annual-billing prices and factored in the June 2026 Zapier AI task multipliers and the August 2025 Make credits transition.

Make is meaningfully cheaper at every tier we modeled, and the gap widens with volume. On the entry plans, Zapier's Professional plan starts at $29.99/month for 750 tasks (or $19.99/month billed annually), while Make's Core plan is $9/month for 10,000 credits and Pro is $16/month for the same allowance with priority execution. A four-step AI workflow running 1,000 times a month runs roughly $69/month on Zapier's Professional plan versus about $16/month on Make's Pro plan, and Zapier's own June 2026 change that makes Advanced-tier AI steps count as three tasks per run (Premium as five) makes AI-heavy Zaps more expensive than the plan pages suggest. The other lever is Make's November 2025 update: on any paid plan you can now connect your own OpenAI or Anthropic API key, so an HTTP-request AI call bills at one credit and you pay the model provider directly. For teams that live in AI workflows, that's the more important number.

AI orchestration and agents
WinnerZapier

How we testedWe tested each platform's agent story end to end: standing up an AI teammate that watches a shared inbox, decides when to act, and takes actions across three connected apps. We also tested each platform's Model Context Protocol (MCP) surface for letting an external Claude or ChatGPT client act on our stack.

Zapier's AI layer is the more mature and the more coherent. AI by Zapier lets you drop an AI step into any Zap with tool calling, looping, and web search built in, so agent-style behavior lives inside the structured workflows you already trust. Zapier Agents (at agents.zapier.com) is a separate product for standing up autonomous teammates and is available on a free tier before you commit. Zapier MCP is available on all plans and connects an AI client to Zapier's 9,000+ integrations through a single auth layer, with each MCP tool call counting as two tasks. Make's answer is credible. Make AI Agents (in beta since spring 2025) can be inserted into any scenario and reason across apps, and the platform has an MCP server and 350+ AI app integrations. But the agent product is newer and less polished, and the per-token credit consumption for native AI modules makes cost harder to predict. If your buying reason is "we want AI agents acting on our apps," Zapier is the safer pick today.

Most operations and RevOps teams are choosing between these two in 2026. Zapier and Make have spent the last twelve months converging on the same pitch, connect thousands of apps, add AI anywhere, orchestrate agents on top, and both shipped pricing changes that make the old head-to-heads out of date.

Where Zapier wins

Zapier wins on breadth, on ease, and on the AI layer sitting above the workflow builder. It has the most integrations at 7,000+, more than any other platform in this category, and its trigger-action model lets a non-technical user set up a working automation in minutes. For a team whose automations are owned by a marketing lead rather than an engineer, that gap is the whole ballgame.

The AI story is the other half of it. Zapier’s agentic capabilities, tool calling, looping, and web search, are built directly into AI by Zapier steps, so you get agent-level flexibility inside the structured workflows you already trust, without a separate AI subscription. On top of that, Zapier’s MCP server connects AI clients to its 9,000-app ecosystem, is available on all plans, and each MCP tool call uses two tasks from your plan’s quota. If your buying reason is “we want Claude or ChatGPT to act on our apps safely,” Zapier is the more finished product.

The catch is price, and the June 2026 change makes it steeper for AI-heavy work. Starting June 15, 2026, AI by Zapier steps are priced per model tier: Standard is 1x task per run, Advanced is 3x (the new default), and Premium is 5x for more sophisticated reasoning. An Advanced-tier AI step running 1,000 times a month consumes 3,000 tasks, not 1,000, before any other action in the Zap runs.

Where Make wins

Make wins on cost and on complex logic. It’s a visual automation platform that lets you build scenarios by connecting modules on a canvas: drag-and-drop steps, connect 3,000+ apps, add routers, filters, and custom logic, and even run JavaScript or Python via the Make Code app, with AI agents and an AI toolkit layered in. If your workflow branches, iterates, or has to recover from a bad AI response, the canvas is the right shape for the problem.

On price, the gap is real. Make.com costs $9/month on the Core plan, $16/month on Pro, and $29/month on Teams, and the Core plan at $9/month includes 10,000 credits, versus Zapier’s equivalent Starter plan at $19.99/month for 750 tasks. On per-operation cost, Make is roughly 80% cheaper at most volumes. The 2025 billing change is worth understanding, though. On August 27, 2025, Make migrated from an operations model to a credits model. For standard executions the math is the same, one module execution costs one credit, but Make Code runs cost two credits per second of execution time, and AI-native modules can consume credits at variable rates depending on the feature, model, and token usage.

The escape hatch that changed the AI math is BYOK. As of November 6, 2025, custom AI provider connections are available on all paid plans, which in practice means you can drop an HTTP Request module against your own OpenAI or Anthropic key and pay the model provider directly for tokens while Make only charges one credit for the request itself. For a team running an AI step in most of its workflows, that’s a meaningful monthly bill.

Who should pick which

Pick Zapier if a non-technical person owns automations, if the specific SaaS you need to connect is niche enough that only Zapier supports it, or if your reason for buying is native AI agents and MCP. The plan pages are more expensive on paper, but you get there faster and you spend less engineering time keeping it running.

Pick Make if your workflows branch and iterate, if cost matters at scale, or if you plan to call an LLM in most of your scenarios and want to bring your own API key. Budget for the learning curve. Make’s visual canvas is powerful but has a steeper learning curve than Zapier, and most new users need four to eight hours to build their first complex scenario comfortably, versus one to two hours in Zapier. Be honest about whether the person owning the automations is up for it.

One thing worth watching: both platforms are still moving. Zapier’s June 2026 AI task multipliers and Make’s August 2025 credits transition both landed inside the window we tested, and both companies are shipping agent features on a monthly cadence. If you’re buying for a team this quarter, ask each vendor for a real usage report from a comparable customer before you commit, and re-check the numbers in the fall.

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