Opal: Google’s No-Code AI App Builder Now Available in 160+ Countries

Google has expanded Opal to 160+ countries, enabling anyone to build AI apps without writing code. This article explains what Opal is, how it works and what it means for automation strategy.

Opal No-Code AI App
Opal No-Code AI App

Google has officially expanded Opal, its no-code AI app builder, to more than 160 countries. Opal allows anyone to create AI mini-apps using natural language, without writing code, and turns ideas into working AI applications in minutes. It is the strongest signal yet that Google is moving AI development away from traditional software engineering and toward a new category: no-code AI creation.

Where existing tools focus on automating workflows or generating content, Opal is positioned as a way to build AI apps entirely through text commands and visual blocks. You describe what you want, Opal generates the logic, and the result becomes a reusable AI mini-app that can be shared, remixed or deployed instantly.

This takes AI from “prompting a chatbot” to “building a tool,” without needing a developer, a backend, or an API integration.

Also see: Google Opal vs n8n

What Opal Actually Is

Opal is a no-code AI app builder inside Google Labs that lets users create AI-powered mini-apps by typing a goal in natural language. Opal translates that request into structured logic, connects the right Gemini models and tools, and outputs a complete working app.

Opal is not:

  • a ChatGPT clone
  • a Zapier-style automation tool
  • a low-code developer platform
  • a prompt playground

Instead, it is positioned as AI app creation without code, built directly on top of Google’s own foundation models.


Key Benefits Google Highlights

Google frames Opal around three core capabilities:

1. Automating the hard stuff

Apps that automate complex research, extract insights from files, analyse findings or summarise multi-source information.

2. Creating custom content

Apps that generate brand-specific marketing assets, video scripts, quizzes, learning paths or storyboards.

3. Going from idea to MVP in minutes

Apps that turn a single idea into a working product: campaign builder, quiz generator, research assistant, content pipeline.

The message is clear: if you can describe it, you can build it.


Why Opal Matters for the Future of AI Workflows

Until now, “AI apps” meant either:

  1. A chatbot wrapped in a UI, or
  2. A developer-built tool using APIs, or
  3. A Make/Zapier scenario tied to external APIs.

Opal removes all three requirements:

  • no prompt engineering
  • no code
  • no backend
  • no vector DB
  • no integration layer

The AI is the logic, the interface and the execution layer.

That creates a new category between automation tools and software products — AI apps that are built, deployed and iterated by non-developers.


Use Cases Google Is Already Pushing

Category Example App Built with Opal
Research “An app that analyses reports and generates a summary deck”
Marketing “An app that turns a product idea into a full campaign”
Education “An app that creates flashcards and quizzes from a document”
Product Teams “An app that builds MVPs from written requirements”
Storyboarding “An app that creates scenes, visuals and scripts”

These are not hypothetical examples. They come from Google’s own announcement page.


How Opal Fits into Google’s AI Strategy

Opal joins three other major AI pillars:

Product Role
Gemini Foundation model and reasoning engine
NotebookLM Knowledge-grounded research and summarisation
Veo + Imagen AI media generation
Opal No-code AI app builder

Opal is Google’s answer to the question: “What if anyone could build an AI tool without asking a developer?”

It positions Google against:

  • Microsoft Power Platform
  • OpenAI GPT Store
  • Bubble / Glide / Softr
  • Retool AI workflows
  • Make & Zapier AI steps

But Google has one advantage: Gemini is native, not bolted on.


Business Impact: What Companies Should Pay Attention To

  1. AI no longer needs an engineering team to go live
    Business users can build apps themselves.
  2. Internal tooling timelines collapse
    From “get a dev to build it” to “ship a first version in one hour”.
  3. Shadow AI will grow without governance
    If Opal is adopted without a policy, every team will build apps independently.
  4. The role of automation architects changes
    Less code, more orchestration, validation and risk control.
  5. The competition shifts from “who has AI” to “who can deploy AI fastest”
    Opal is built for speed, not perfection.

Where Opal Will Win First

  • Startups that don’t want to hire engineers for internal tools
  • Agencies that need fast client prototypes
  • Education platforms building interactive learning apps
  • Marketing teams producing campaign assets at scale
  • Research teams who need structured outputs, not chat logs
  • Non-technical founders building proof-of-concepts before fundraising

In other words: Opal’s first audience is the same audience that adopted no-code tools — but now with AI creation instead of UI creation.


The Risks You Should Not Ignore

Risk Why it matters
No central governance Anyone can build and deploy apps
Unknown data handling Not yet enterprise-grade compliance
Vendor dependency Apps run on Google’s infrastructure
Shadow AI workflows IT may not know which apps exist
No RBAC layer yet Access control depends on the user, not the app

The biggest failure mode is not technical it’s organisational.


Scalevise Perspective

Opal is not the end of software development. It is the beginning of AI-first micro-applications that sit between chatbots, dashboards, automation tools and full platforms.

Where Gemini changes how information is retrieved, Opal changes who can build the workflows around it.

Companies that benefit from Opal will be the ones that:

  • treat AI apps as part of their architecture
  • add governance before rollout
  • design roles around AI creation, not just AI usage
  • integrate Opal outputs into existing systems, not in isolation

The value is not in “building an Opal app.”
The value is in turning Opal into a repeatable layer of business capability.


If you want help deciding where Opal fits into your automation stack, and how to deploy no-code AI apps without losing control, you can schedule a session through the agenda widget below.