Make.com AI Update July 2026: What Actually Changed — And What It Means for Your Business

Quick answer: Make.com didn't ship one single "July 2026 AI update." It shipped several, on a rolling weekly basis, as it always does. The two most relevant for AI-focused users this month are the July 8 Make Grid update, which added the ability to map third-party AI agents (n8n, Claude's managed agents, Relevance AI) alongside Make scenarios, and the July 10 update, which refreshed the MCP (Model Context Protocol) client and added new monday.com AI modules. Earlier in the month, Make also added support for Anthropic's Claude Sonnet 5 and Claude Fable 5 models (July 3) and opened its Databricks connector to Enterprise plans (July 2).

If you searched "make.com ai update july 2026" expecting a single headline announcement, that's the honest answer: there wasn't one big-bang release. Instead, Make is in a phase of continuous, almost weekly shipping — which is itself the story worth understanding if you're deciding whether to adopt the platform.

Below, we break down exactly what changed, what it actually means in practice, and — since we build automation and AI systems for a living — where a tool like Make.com fits next to hiring a team to build something custom.

Why This Search Term Trending?

Interest in phrases like "make.com ai update," "enterprise ai workflow automation today," and "how to use ai for business automation" has been climbing through 2026 because a specific shift is happening: companies have moved past asking whether AI is useful and are now trying to figure out which platform to build on. Make.com is one of a handful of automation platforms (alongside Zapier, n8n, and Workato) that has spent 2026 aggressively adding AI-agent and orchestration features on top of its existing no-code workflow builder — so every release naturally draws search traffic from people trying to keep up.

That said, "keeping up" with Make is genuinely difficult right now. According to Make's own release notes, the platform has shipped new features, app modules, or model integrations on at least fourteen separate dates between January and July 2026 — that's roughly one release every two weeks. Most of these are incremental (a new connector, a deprecated model swapped out, a UI improvement), but a few mark real structural changes to how the platform works.

Make.com's Actual July 2026 Release Timeline

Here's what Make.com's release notes confirm for July 2026, in order:

July 10 — New monday.com AI modules, MCP client update, and more. Make refreshed its MCP client and shipped improvements across several existing app connectors, including Discord, GitHub, and Reddit, alongside new AI-specific modules for monday.com.

July 8 — Content search in Make Grid. Make Grid (the platform's dependency-mapping and workflow-visibility layer) can now scan every configuration in an account — modules, field IDs, URLs, notes, and AI prompts — to help teams find things faster across large numbers of scenarios.

July 8 — Third-party automation and AI agents in Make Grid. This is arguably the most significant change of the month. Make Grid now supports mapping n8n workflows, Claude's managed agents, and Relevance AI agents alongside native Make scenarios, giving teams a single visual map of automation and AI dependencies that span multiple tools — not just Make's own.

July 3 — Team edit permission removed from the Team Member role. A governance change: team members in public environments can no longer rename teams unless they're assigned the Admin role.

July 3 — Claude Fable 5 and Claude Sonnet 5 available in Make. Anthropic's newest model releases became available as selectable models inside Make scenarios and AI agents, aimed at use cases needing long context, image analysis, and lower-cost reasoning.

July 2 — Databricks app now available (Enterprise plans). Enterprise customers can now run SQL queries, manage jobs and pipelines, and upload files to Unity Catalog volumes directly from a Make scenario.

July 2 — User roles visibility. Organization and team admins got a new page to view all system roles and permissions across their Make account.

None of these, individually, is a platform-redefining announcement. Together, they show a platform investing heavily in two directions at once: deeper AI model access (more LLMs, faster swap-in when models are deprecated) and better governance and visibility as automations get more complex and higher-stakes.

The Bigger Picture: Make's 2026 AI Roadmap So Far

To understand July in context, it helps to zoom out to what Make has built over the year:

Make AI Agents

Make's AI Agents feature, available on all paid plans, lets users build reusable, model-agnostic agents that can be deployed across multiple scenarios rather than rebuilt each time. In February 2026, Make shipped a substantially redesigned Make AI Agents (New) app aimed at making agent building, testing, and debugging more transparent. In June, that app gained support for connecting external MCP tools directly.

Model Context Protocol (MCP) support

Make has built out a full MCP layer in 2026, including a Make MCP server and, since February, MCP toolboxes — dedicated Make MCP servers that expose specific sets of scenarios as callable tools for external AI systems like Claude or ChatGPT. In March, Anthropic added Make as a built-in connector inside Claude itself, meaning Claude users can trigger Make scenarios without leaving their chat.

Maia by Make

Perhaps the most interesting (and least understood) 2026 feature is Maia, described in Make's own documentation as an "AI and automation co-worker" built into the scenario builder. Maia is not yet generally available — Make is explicit that its functionality and pricing may still change. In practice, Maia lets users describe what they want in plain language ("add a filter that only passes emails from my domain") and watches it build, modify, or debug the scenario step by step on the canvas, explaining its reasoning as it goes. Maia runs on a mix of models, including GPT-5.2 and GPT-4.1 mini, and Make states that it never uses customer data to train or fine-tune the underlying models. Access is currently metered by a weekly message limit tied to plan tier.

Make Grid

Launched earlier in the year and expanded through July, Make Grid is Make's answer to a real problem large automation teams run into: once you have hundreds of scenarios, nobody can see how they connect, what depends on what, or which ones touch AI systems versus plain data pipes. Grid gives teams a single visual map — and, as of this month, that map now extends beyond Make itself into other automation and agent tools.

Model access

Make has kept pace with nearly every major LLM release in 2026 — OpenAI's GPT-5 series (including GPT-5.5, GPT-5.4, and GPT-5.2), Anthropic's Claude line (Opus 4.6, 4.7, Sonnet 4.6, Sonnet 5, Fable 5), and Google's Gemini 3.1 and 3.5 Flash have all been added as they've released, with Make automatically swapping out deprecated models so existing scenarios don't break.

What Does This Mean in Practice?

If you're already a Make.com user: the July updates don't require you to do anything. Nothing here is a breaking change except the team-permission adjustment on July 3 — worth a quick check if you rely on team members renaming shared team spaces. The MCP and Grid updates are additive.

If you're evaluating Make.com for the first time: the direction of travel matters more than any single release. Make is positioning itself less as "a tool that connects App A to App B" and more as an orchestration layer that sits across multiple AI models, multiple automation tools, and (via Grid) even other platforms' agents. That's a meaningfully different product than it was two years ago.

If you're trying to decide between a platform and a custom build: this is where most of the search traffic around "how to use AI for business automation 2026" is really coming from, and it deserves an honest answer.

Make.com's Own Pricing Structure (What to Actually Check)

Make.com runs on a credit-based system — in 2025 it renamed its billing unit from "operations" to "credits," though the underlying idea is the same: most module executions inside a scenario consume one credit, with AI and code-execution steps typically costing more. The plan structure, from Make's own pricing page, is:

Because pricing and credit allocations change periodically, always confirm current numbers directly on Make's pricing page before budgeting — third-party estimates online vary and are often out of date within a few months.

Tool vs. Team: Where Make.com Fits (and Where It Doesn't)

We work with businesses across the UAE building AI systems, websites, and automation — so we see this question constantly, and the honest answer is: it depends on the shape of the problem, not the size of the business.

Make.com (or a similar platform) is usually the right call when:

• The workflow connects well-supported apps that already have Make modules (CRM, forms, Slack, email, spreadsheets)
• Someone on the team can own and maintain the scenario long-term
• The logic is fundamentally "when X happens, do Y, Z, and notify someone" — even if an AI step is involved
• You want to start small, test an idea, and scale usage gradually

A custom-built solution is usually the right call when:

• The workflow needs to talk to internal or legacy systems with no existing connector
• Credit costs at your real volume start rivaling or exceeding the cost of a maintained system (this happens more often than people expect once iterators, routers, and AI steps are involved)
• The AI component needs fine-tuned behavior, proprietary data handling, or compliance guarantees that a general platform's model access can't guarantee
• You need the automation to be a defensible part of your product, not just internal plumbing

Many of our clients actually end up somewhere in between: Make.com (or n8n) handling the glue work between systems, with custom-built AI components where the business logic actually needs to live. That combination is often the fastest and most cost-effective path — you're not rebuilding a Slack connector from scratch, but you're also not trying to force complex, proprietary logic into a visual builder never designed for it.

How Businesses Are Actually Using These Features?

Search interest in "how to use AI for business automation 2026" is usually less about theory and more about "show me a real setup." If you're starting from scratch, it's worth reading our complete guide to automating your business with AI first — it covers the broader strategy of where to start. Here's how the specific July 2026 Make.com features map onto real workflows, using only capabilities the platform actually has today — not a generic automation wish list.

Customer support: MCP toolboxes + AI Agents

A support team can expose a set of internal Make scenarios (order lookup, refund status, ticket creation) as an MCP toolbox, then let an AI Agent — or an external assistant like Claude, connected through Make's built-in Claude connector — call those scenarios as tools when a customer asks a question. The AI reads the request, decides which scenario to trigger, and Make executes the actual system change. The AI never touches the database directly; it only calls a scenario Make already runs.

HR and onboarding: Maia + AI Agents

Because Maia can build and modify scenarios from a plain-language description, HR or ops staff without automation experience can prototype onboarding flows themselves — "when a new hire is added to BambooHR, create their accounts, send a welcome Slack message, and schedule a 30-day check-in" — and then hand the finished scenario to IT for review before it goes live. This is one of the more genuinely useful applications of Maia: it lowers the barrier to a first draft, without removing human review before activation.

Finance and data: Databricks + credit-aware design

With the Databricks connector now available on Enterprise plans, finance and data teams can trigger SQL queries, run pipeline jobs, or push files into Unity Catalog volumes as part of a broader scenario — for example, an invoice-processing flow that extracts data via an AI module, validates it, and writes clean records into a Databricks table for reporting. Because AI and code-execution steps consume more credits than a standard module call, this is also where credit budgeting matters most — a workflow like this is worth mapping out in Make Grid before it goes live.

Cross-tool visibility: Make Grid

For any team running automations across more than one platform — say, some scenarios in Make and some agents in n8n or Relevance AI — Grid's July 8 update means those can now sit on the same dependency map. In practice, this is most useful for larger teams trying to answer a simple but previously hard question: "if I change this field, what breaks?" — across tools, not just within Make.

Enterprise AI Workflow Automation Today: What's Actually Different

"Enterprise AI workflow automation" as a search phrase implies something more than "automation with an AI step in it." Based on what Make has actually shipped through 2026, the enterprise-specific differences are:

• Governance, not just capability. Features like the July 2 user-roles visibility page, two-factor authentication enforcement, and audit logs exist because once AI agents can take real actions (create records, send communications, move data), the question shifts from "can it do this" to "who authorized it, and can we prove that later."
• Model flexibility as a requirement, not a feature. Enterprises running AI at scale need to swap models when one is deprecated or a cheaper/better one ships — Make's rapid rollout of new OpenAI, Anthropic, and Google models throughout 2026, with automatic replacement of deprecated ones, is aimed squarely at that need.
• Cross-system data access. The Databricks connector, restricted to Enterprise plans, reflects that enterprise automation increasingly needs to reach into data warehouses and pipelines, not just SaaS apps.
• Visibility at scale. Make Grid exists specifically because an enterprise account with hundreds of scenarios and multiple AI agents becomes unmanageable without a dependency map — a problem small teams simply don't hit yet.

The practical takeaway: if your organization is small enough that one person can hold the whole automation setup in their head, most of this "enterprise" tooling won't matter to you yet. It starts mattering the moment more than a few people are building, or the automation starts taking actions with real financial or compliance consequences.

AI Automation Adoption in the UAE and GCC

The UAE has positioned AI adoption as a national priority for several years, and that context shapes how automation platforms like Make.com get used locally. In our own work with businesses across Dubai and the wider UAE, the most common starting points for AI-assisted automation tend to be:

• Customer-facing operations — WhatsApp-based inquiry handling and booking flows, common in retail, real estate, and hospitality
• Back-office processes — HR onboarding, invoice handling, and CRM data entry for SMEs replacing manual spreadsheet work
• Multilingual support — Arabic/English handling in customer communication, an area where model choice (and Make's growing library of selectable LLMs) genuinely matters
• Real estate and hospitality workflows — lead routing, inquiry qualification, and booking coordination, both busy with high inbound volume and repetitive structure

A platform like Make.com can cover a meaningful share of this out of the box. Where UAE businesses most often need custom work on top of it is compliance-sensitive data handling and integrations with regional systems (local payment gateways, government-linked platforms, industry-specific software) that don't have off-the-shelf Make connectors.

Frequently Asked Questions

What is the latest Make.com AI update in July 2026?

There isn't a single flagship update. The most notable changes are the July 8 Make Grid update (which now maps third-party AI agents like n8n and Claude's managed agents alongside Make scenarios) and the July 10 MCP client refresh with new monday.com AI modules. Make also added Claude Sonnet 5 and Claude Fable 5 as available models on July 3.

What is MCP, and why does Make.com support it?

The Model Context Protocol (MCP) is a standard that lets AI systems like Claude or ChatGPT call external tools and data sources in a consistent way. Make supports MCP in two directions: it can act as an MCP client (letting Make agents call outside tools) and expose its own scenarios as MCP servers via "MCP toolboxes," so external AI assistants can trigger Make workflows as tools.

What is Maia by Make?

Maia is Make's built-in AI assistant for building automations conversationally — you describe a change in plain language and it edits the scenario on the canvas. It's still in limited availability, not yet a general-release feature, and usage is capped by a weekly message limit based on plan tier.

Is Make.com's AI good enough for enterprise use?

Make now offers Enterprise-specific features (SSO, audit logs, Databricks connectivity, custom credit allocation) alongside its AI Agents and MCP toolset, so it's positioned for enterprise adoption. Whether it's "enough" depends on your compliance requirements and how deeply the automation needs to integrate with proprietary internal systems — areas where a custom build often still wins.

Should a small business use Make.com or hire an automation agency?

If your automation needs map cleanly onto Make's existing app library and someone in-house can maintain it, Make.com alone is usually the more cost-effective starting point. If the workflow touches internal systems, needs custom AI behavior, or is meant to become a real product feature rather than internal plumbing, working with a team that can build and maintain a tailored solution tends to pay off faster.

The Bottom Line

Make.com's July 2026 activity isn't a single dramatic AI launch — it's a continuation of a steady, months-long push to make the platform a control layer for AI agents and models, not just app-to-app automation. The additions worth actually paying attention to are the Make Grid expansion to third-party AI agents and the ongoing MCP investment, because they signal where Make is trying to position itself: as the visual map sitting on top of an increasingly fragmented AI-agent landscape, rather than just another automation tool competing on app-connector count.

For businesses trying to decide what to do with that information, the practical move isn't to chase every release — it's to get clear on which parts of your operations are simple enough for a platform like Make to own, and which parts need something built specifically around how your business actually works.

Need help implementing AI automation?

BitMasters helps organizations across the UAE design custom AI workflows, automation systems, and enterprise integrations tailored to their business requirements — including the parts a platform like Make.com can't cover out of the box.