Automation is a cool tool that allows you to speed up your work many times over and reduce the human factor. Automated campaign launches free us of routine, neural networks help with creatives and analytics. But without understanding how it works and what the limitations are, it can easily turn into a whole new source of problems.

In this article, we’ll talk about how to implement the correct tools so that they actually bring results.

Why automation has become a must have

Over the past two years, several key changes have come to the niche of nutra:

Advertising accounts have faced more rigorous moderation – even relatively safe-to-advertise creatives can be rejected.

The cost of traffic has increased – each extra test without a nice result hits the ROI.

The lifespan of ad campaign approaches has decreased – a successful campaign can burn out in 2-3 days.

Previously, automation was a privilege of large teams with their own developers. Today, there are affordable SaaS solutions and ready-made scripts for automated campaign launching, and neural networks allow you not to spend days preparing creatives.

Automated campaign launching: what is it and how it is used

Automated campaign launching is the mass creation and launch of advertising campaigns using scripts, API or specialized software. It can be:

Fully automated – the system itself creates campaigns, uploads creatives, sets targeting and budgets.

Semi-automated – the buyer launches ready-made templates and only makes minimal edits.

How is it used:

Meta (Facebook, Instagram) – mass launching of campaigns via API, bypassing the limited functionality of the interface.

TikTok Ads – especially for GEOs with rapid burnout of creatives.

Google Ads – automatic launching of search and contextual media campaigns.

Teaser and push notification networks – mass testing of creatives with automatic disabling of weak ones.

AI today is not just ChatGPT or Midjourney. Affiliate marketing uses neural networks that can generate unique creatives for each launch, do automatic translation and localization for different GEOs, create adapted landing pages for an offer, and even optimize campaigns in real time.

Another important advantage is automated A/B generation: your neural network creates several versions of one creative at once, and the automated campaign launching system distributes them between campaigns.

Limitations and risks of automation

Despite such tempting advantages, automated campaign launching also has a dark side:

Bans for automatic actions. Meta and TikTok actively identify suspicious mass launches via API. Algorithms analyze the frequency and similarity of your actions across ad accounts.

Decrease in traffic quality. If the system launches everything back-to-back, you can quickly burn out the audience or get into the wrong target. With too wide a target, AI can drive clicks, but with a low CR.

Technical failures. API updates can break the automated launch scenario, and a bug in the code can accidentally drain the budget.

Here’s how to avoid this

1. Use different proxies and browser fingerprints.

2. Split the launching into parts (do not launch everything at once).

3. Add manual actions so that there is no full automation.

4. Set up clear filters and funnels.

5. Set up budget limits at the campaign and account level (but even this does not always help).

How to implement automated campaign launching and AI in 2025

The first thing to start with is the technical base. Any automated campaign launch will be tied to the API of advertising platforms. The cleaner and more reliable the setup, the lower the risk of blocking. In 2025, this is already the standard: stable proxies, correctly configured anti-detect browsers and well-thought-out fingerprints. Many teams in 2025 work not with one, but with several anti-detection tools in parallel to diversify risks.

Next is the choice of software for automated campaign launching. There are two ways:

–   Ready-made SaaS services that provide a user-friendly interface and minimize technical tasks;

–   Custom scripts tailored to a specific team or offer.

The first option is easier to launch, but more expensive in the long term, and you depend on an external service. The second requires a developer or your own skills, but gives more flexibility and the ability to adjust the process to any platform updates.

The next layer is AI integration. At this stage, it is important not just to generate images with Midjourney, but to build a reliable chain: AI designs creatives → the system selects targeting and formats → automated campaign launching sets up campaigns with different variations. More advanced teams go even further – they connect AI to analyze statistics in trackers and automatically disable unprofitable campaigns.

But there is a drawback to stay mindful of, automation should not completely remove humans from the process. Even in 2025, the hybrid approach remains the most effective – AI and software work in conjunction with a buyer who controls key points: checking creatives, choosing offers, and making final decisions on scaling.

For example, you can set up the system so that it uploads new creatives every day, filters out those that have decreased in CTR, and launches the next tests itself. The buyer only has to look at the reports and adjust the strategy.

Implementing automation is an investment not only in speed, but also in sustainability. With proper configuration, automated campaign setups and AI allow for scaling to be implemented several times faster than competitors, and in case of failure, quickly restore campaigns and accounts.

The main thing is not to try to automate everything at once, but to introduce the system gradually: first automated launches, then AI for creatives, then AI optimization. This way, you will avoid sudden failures and will be able to understand what really works for your offers.

To conclude,

In 2025, automation has ceased to be an experiment for those tech-savvy but has become a working tool even for small teams. Automated campaign setups decrease routine, neural networks save hours on designing creatives, and the combination of these technologies allows you to respond to market changes in real time.

But the main effect is not in speed or volume – it is in the fact that the media buyer gets the opportunity to spend more time on strategy, analytics, and searching for strong offers.