Five steps, a thousand runs. That’s five thousand tasks. You look at Zapier Pro at $19.99 a month and it covers 750. You are looking at a plan upgrade or per-task overage before the first week is out. The $19.99 number already says nothing. Make’s $9 plan covers 10,000 operations — the same 5,000 operations fit easily. n8n’s cloud at $20 counts each run as one execution, so 1,000 runs is 1,000 executions, well under the 2,500 cap. Power Automate at $15 per user seems cheap until premium connectors add fees. The sticker price does not tell you what your workflow actually costs.
This is where the niche-divergence thesis becomes useful. Zapier owns simplicity and breadth — 9,000+ integrations — but its per-task pricing punishes multi-step workflows. Make gives you visual branching that Zapier can’t touch, with 3,000+ integrations and a $9 entry. n8n hands full code control to developers; self-host it and you have no execution limits, but you need to account for server time. Gumloop embeds GPT-4 and Claude natively, no API keys needed, but it’s cloud-only and credit-based. Power Automate locks into the Microsoft ecosystem, and inside that wall it is often the cheapest per user. The choice isn’t which tool is best. It’s which niche your workflows fall into.
| Tool | Integrations | Starting price | AI approach | Best fit |
|---|---|---|---|---|
| Zapier | 9,000+ | $19.99/mo (750 tasks) | Bolted-on (Copilot) | Simple linear workflows, non-tech users |
| Make | 3,000+ | $9/mo (10K operations) | Limited (templates) | Visual branching, conditional logic |
| n8n | 1,300+ | Free self-host / $20/mo cloud (2,500 executions) | AI nodes (bring your own key) | Developers, custom code, unlimited runs |
| Gumloop | Not disclosed | $37/mo (20K+ credits) | Native GPT-4/Claude | AI-native pipelines, no API key management |
| Power Automate | Thousands (M365 ecosystem) | $15/user/mo | AI Builder (premium add-on) | Microsoft-centric enterprises |

If you want a deeper dive on Zapier, Make, n8n, and Power Automate before adding Gumloop, we have a separate four-tool comparison that covers ecosystem lock-in and cost scalability. This article adds the AI-native angle and the fifth contender.

Once you understand the pricing, the next question is what your workflows actually look like. Each tool has a sweet spot, and a single disqualifier often saves more time than any feature list.
Zapier is the fastest path for simple linear automations. A lead capture that creates a row in Google Sheets and sends a Slack notification? Three steps, 10 seconds to set up, no learning curve. But if your workflows regularly run more than three steps or exceed 1,000 runs a month, the per-task pricing penalty will eat your budget. That’s the disqualifier.
Make shines when your logic has branches. An approval workflow that routes to different managers based on dollar amount, department, and region — Make’s visual editor handles that without code. Its $9/month entry for 10,000 operations is hard to beat for mid-complexity workflows. But if your workflows are dead simple linear, Make’s visual branching is overkill. Zapier would be faster and cheaper.
n8n is for when you need to go beyond what a UI can offer. An ETL pipeline that calls a custom API, transforms the response with JavaScript, and inserts it into a database — that’s a day’s work in n8n. Self-host it and you have no execution limits. Cloud plans start at $20/month for 2,500 executions. The trade-off is that you or someone on your team needs to understand JSON, APIs, and code. If no one can read JavaScript or JSON, n8n is not for you. Self-hosting adds operational overhead that many underestimate. Our TCO analysis shows when it saves money and when it costs more.
Gumloop is the newest niche: workflows that depend on LLM calls. A document summarization pipeline that reads PDFs, generates summaries via GPT-4, and saves them to a database — Gumloop handles the AI part out of the box, no API keys needed. But its pricing is credit-based: $37/month for 20,000+ credits, and each step in a workflow consumes credits. I note that its own blog sometimes quotes $37/mo and other sources $30 — likely different plan definitions. Check the official page with your usage. It’s cloud-only, so no on-premise. If your workflows don’t involve LLM calls, Gumloop is the wrong tool.
Power Automate is the enterprise pick if you already live in Microsoft 365. An approval chain that starts in SharePoint, moves to Teams, and logs in Dynamics — all native connectors. The $15/user/month base price can be deceptive because premium connectors (Salesforce, Workday, etc.) cost extra. For a team of ten, that’s $1,800/year before connector fees. If only one person builds automations, a single Zapier Pro seat may actually be cheaper. Our Power Automate pricing breakdown walks through the hidden costs.
The AI difference: native intelligence vs bolted-on prompts
Every tool now says it has AI. I treat that claim the same way I treat pricing: show me what it actually does in a workflow, not what it could do someday. The distinction that matters is whether AI is native to the engine or bolted on as an extra feature.
| Tool | AI integration | Native or bolted-on | What it means |
|---|---|---|---|
| Gumloop | Built-in GPT-4/Claude | Native | AI runs as part of the workflow; no API keys, no separate billing for LLM calls (beyond credits) |
| n8n | OpenAI / AI nodes | Modular (native via nodes) | You connect your own model; flexible but you manage tokens and API costs |
| Power Automate | AI Builder | Bolted-on (premium add-on) | Document processing, sentiment analysis; requires extra licenses and may be overkill for simple tasks |
| Zapier | Copilot | Bolted-on | Suggests steps and automations; doesn't run AI within the workflow logic |
| Make | Template suggestions | Bolted-on | AI is limited to helping you build templates; no LLM integration in workflow execution |
A McKinsey 2025 study found that 88% of companies now use AI in at least one business function. I do not buy this figure as proof that AI automation is effective. It measures adoption, not results. Prevalence ≠ impact. The real signal is whether the AI changes how you design workflows. Gumloop’s native integration does: you can chain GPT-4 calls as steps without leaving the platform. That is fundamentally different from Zapier Copilot, which suggests steps but does not execute AI inside the flow. When you see ‘AI-powered’, ask: is it native or bolted on? That distinction will save you more than any feature list.

So which one? A decision framework for 2026
By now you have the data. The decision framework is simple: answer these five questions, then map your answers to the table.
- How many steps in your average workflow? (1–3 → Zapier, 4–10 → Make, 10+ → n8n or custom)
- How many runs per month? (Under 1,000 → any, 1,000–10,000 → watch per-task pricing, over 10,000 → n8n self-host or Power Automate if M365)
- What's your team size and tech skill? (Non-technical individual → Zapier, small tech-savvy team → Make or n8n, large enterprise → Power Automate)
- Do you need AI in the workflow itself? (Yes, and no API key management → Gumloop, yes but flexible → n8n with AI nodes, no → Zapier or Make)
- Are you primarily a Microsoft house? (Yes → Power Automate likely cheapest, No → Zapier or Make for broadest integration)
Let me give you three quick personas:
- Solo marketer: Runs simple lead capture, email sequences, social posting. Under 1,000 runs/month. Pick Zapier. Per-task pricing won't sting at that volume.
- Ops lead in a mid-size company: Manages approval workflows, data syncs, and occasional API integrations. 1,000–5,000 runs/month, moderate complexity. Pick Make or n8n cloud. Make if you want visual control, n8n if you have a developer to set up custom nodes.
- IT manager in a large enterprise: Already on M365, needs governance, compliance, and high-volume processing. Pick Power Automate. The ecosystem integration reduces risk more than the per-user cost matters.
The market for workflow automation tools is projected to reach $26.01 billion in 2026, growing at 9.41% CAGR. That figure is context, not a buying signal. Do the math on your own usage, not the vendor’s example. The most expensive tool on paper can be the cheapest in reality if your workflows are simple or you already have the ecosystem. And when you see ‘AI-powered’, ask: is it native or bolted on? That distinction will save you more than any feature list.
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