How to Make Playable Ads With AI: A Step-by-Step Guide (2026)

A year ago "AI playable ads" mostly meant generating the art for a playable a developer would then build. That has changed: several tools now take a sentence or a store listing and return a working HTML5 playable. When PocketGamer.biz covered one such launch on 1 October 2026, it described a single custom playable as traditionally taking between one and three weeks of specialised development and costing thousands of dollars per iteration. Cutting that to a session is the promise. Whether you actually get there depends on what you give the AI, which way it builds the game, and how carefully you check the result.

This guide is the practical version: the steps, in order, and what to look for at each one. It uses our own AI Playable Maker for the concrete examples, but every step applies to any generator you try.

What an AI playable ad generator actually does

Strip away the marketing and a generator has to do five jobs. It has to understand what the game is and how it plays. It has to design an ad around that: a hook, a short interaction, a payoff and an offer. It has to build something interactive that runs inside an ad container. It has to produce an end card. And it has to package the result in the exact format each network accepts, under each network's size cap, with the right store-exit call.

The first two are where AI is strong: reading a description or a store page and proposing a sensible ad is a language-and-judgement task. The last one is where it is weakest, because it is exact work governed by third-party rules, which is the argument made at length in AI in playable ad production. The best tools put the AI in charge of the first two and hand the last one to a deterministic exporter that does the same thing every time.

Step 1: write a brief the AI can act on

The single biggest lever on quality is the brief. A model will happily invent a game from "make a fun puzzle ad", and it will be generic. What it needs is the same thing a human designer needs:

• The core action, in one verb. Sort, merge, aim, drag, tap in time, connect. If you can name the gesture, the AI can build around it.
• What the player sees in the first second. A half-solved board, a character in trouble, a pile of coins about to topple. This is your hook.
• How it ends. A clear win the viewer reaches in a few moves, and what the reward looks like.
• The goal of the campaign. Installs, engagement, awareness or winning back lapsed players pull the design in different directions.
• The look. Hyper-casual, premium, cartoon, realistic, minimal: the visual register should match the game you are selling.

In the AI Playable Maker this is the Create tab. You can type the brief, or skip most of it with three taps (a goal, a look and an optional audience) which the AI writes into its design with the pacing a playable needs: the hook in the first couple of seconds, then the interaction, the reward and the call to action. If you have no idea yet, "Suggest 3 ideas" returns three concepts to pick from before anything is built. A reference screenshot on its own is also a valid brief.

Step 2: let the AI pick the route, and understand the trade-off

There are three fundamentally different ways an AI can turn a design into a playable, and the difference matters more than which model is behind it.

Route A: re-theme a proven template

If an existing, finished playable already expresses the mechanic (a match-3, a water sort, a merge) the safest build is a themed variation of it: new words, colours and pictures on a game whose layout, difficulty, HUD and result cards were already tuned by hand. It is the cheapest route and the most reliable, because the game logic is not new. Our design step looks at our prebuilt playable templates first for exactly this reason.

Route B: compose it from editor blocks

When no template fits, the next option is to have the AI write a composition (scenes, objects, motion, events, variables, a genre and its settings) that the editor then builds through its own checked factories. Nothing the AI writes can produce an object the editor does not have, so the result opens in the editor as an ordinary project you can change by hand.

Route C: write new game code

Only for a mechanic nothing in the library can express does it make sense to have the model write game code. That is the most flexible route and the riskiest, which is why ours runs that code in a locked-down sandbox on a small game kit of our own engines (physics, effects, tweening, UI) rather than letting it write everything from nothing, and why it is checked and playtested before you see it.

When you evaluate any AI playable tool, ask which of these it is doing. A tool that always writes fresh code from a prompt will impress on a demo and vary wildly in production; a tool that can only re-skin templates will be reliable and limited. Being able to do all three, and choosing per brief, is the useful property.

Step 3: check the price and the design before the build

A design you can read before anything is built saves the most time in the whole process. You see what the AI intends to make (the mechanic, the hook, the end card) and can correct it in words while it is still cheap to change. In the AI Playable Maker every build also shows a price range up front, and charges only what the job really used; a failure on our side costs nothing. Credits come with every paid plan each month and can be topped up: current amounts are on the pricing page.

Step 4: playtest it, automatically and then yourself

A generated playable can look finished and be unwinnable, trivially easy, or stuck after the second tap. Two checks catch most of this:

1. An automated playtest. For a new game, ours has a bot play it in your browser, in the same sandbox it ships in. A game that cannot be won, crashes, or is won in a couple of moves goes back for a repair before you are asked to look at it.
2. A visual review. The real export is rendered in both orientations and the game and end card are photographed onto one sheet, which the AI then judges against our house design standard and returns a short list of concrete fixes you can apply in one click.

Then play it yourself, as a stranger would. The difficulty and win-rate guide explains why almost everyone who engages should win, and the first three seconds guide what the opening has to do.

Step 5: read the score, then change things by chat

Every AI project carries a Playable Score in its Check tab: one number made of six categories (gameplay, first seconds, call to action, design, network compliance and asset weight) with the issues written out and one-click fixes for the common ones (a call to action that arrives too late, text that does not stand out from what is behind it, a picture that can be compressed). It reads the same checks the export relies on, against the networks you said you are targeting.

For everything else there is the chat beside the canvas. Ask for a different hook, a harder board, a darker palette or a new background picture; each change becomes a restore point, so trying an idea and going back costs nothing but the change itself. And because the result is an ordinary project, you can also just select an object and edit it in the properties panel: the AI is a way in, not a place you are stuck.

Step 6: export to the networks you buy media on

The export is where a generated playable becomes a deliverable, and it should not involve the AI at all. Ours builds every AI project through the same exporter as a hand-built one, for all 13 supported ad networks, with each network's packaging and store-exit call. See exporting for IronSource, AppLovin and Mintegral for what differs between them. Before uploading, check the file against each network's size limit; the size limits by network are listed in one place.

What still needs a human

• Truth in advertising. The AI designs from the game, but only you know whether the ad shows something the game really has. A playable that misrepresents the product is a policy problem and a retention problem. See misleading creative and what gets you banned.
• Brand and IP. Generated pictures should be checked against your style guide and for resemblance to anyone else's work.
• The decision about what to test. AI makes variants cheap; it does not tell you which variable matters. AI ad variations for A/B testing covers that.
• Device QA. Play the exported file on a real phone before scaling spend: how to test a playable on devices.

Try it

The quickest way to judge AI playables is to play some. The AI examples page has real results you can play and remix without an account. When you want to make your own, open the AI Playable Maker; for a post-video card on its own, the AI End Card Maker.