How AI is Changing Influencer Marketing

Written by Tal Melenboim, CEO of CGI influencers agency Zoe01.

Influencer marketing might seem like a recent invention, but it has always existed. In the past influencers existed as celebrities who promoted products in ads and writers who wrote about products in articles both offline and online. Slowly influencer marketing crept onto social media.

Social media influencers have been active for several years on networks like Twitter, Myspace, Facebook, etc. Influencer marketing seems like a recent invention because of the sudden growth on Instagram. Anyone can become an influencer on this network.

Influencer marketing has always been here and is constantly evolving.

The next evolution that is taking over influencer marketing and changing it is AI. Here’s how AI is affecting influencer marketing and how you can embrace this change to get the most out of it.

AI is making it easier to create viral posts:

Analytics are an important part of influencer marketing. If you know how to study your analytics you will be able to better predict what types of posts your influencers post will fare better. To gain these insights people had to earlier rely on analytical reports released by top marketing firms and the basic analytics provided by the social networks themselves.

This helped a little, but it wasn’t the perfect solution. As reports contain results from thousands of accounts which makes it hard to predict what will work for you specifically. And the analytics offered by social networks are very basic. It has improved over the years, but it isn’t the best.

Take a look at Instagram’s analytics for example. On the analytics page you can see when your followers are active…

…and their demographics

But Instagram doesn’t exactly confirm that if I post at these times, I will get more likes or followers or sales.

But fortunately, there are third part social media analytics tools like Tailwind and Quintly that will give me more details about the best times to post (and what to post) to get more likes.

Tailwind for example will use AI to study your Instagram analytics and automatically set the best times to post.

Social media analytics tools like Quintly make it easy to monitor your competitors accounts to see what posts are working for them, what times are best for them, what to avoid, etc. This form of AI makes it easy for you to replicate their strategy. You don’t have to spend hours manually going through competitor accounts to figure out what is working for them.

So, you can use AI tools like these to extract data from your competitors accounts, your own account, your influencers accounts (the ones you will be working with) and from the accounts of influencers your competitors have worked with and create sponsored posts that will definitely go viral.

Better influencer screening:

The number one concern business have with influencer marketing is the use of fake followers.

It will cost businesses over $1.3 billion this year. It is very hard to manually screen influencers. Many experts will ask you to look at ‘engagement’ instead of followers, but like followers, likes and comments can also be purchased.

This is why businesses have turned to AI for help. There are several fake follower checking tools that can analyze accounts and automatically tell you the number of fake and real followers an account has.

This makes it easy for businesses to pick the right influencers and avoid influencer fraud.

Given rise to CGI influencers:

The above two improvements in AI have also led to the rise of CGI influencers. CGI influencers are influencers who are created using CGI (computer generated imagery). Business and agency prefer them as opposed to ‘real influencers’ as they themselves own the influencers.

This lets them use analytical data to mould the exact influencer they want. As they own the influencer, they can also predict the amount of engagement and sales the influencer will generate.

This is a very effective and affordable long-term plan. As they themselves own the influencer they don’t have to pay them every time they need a post. They can also directly control what the influencer posts and avoid the controversial posts that plague a lot of influencers.

An example of a CGI influencer you should check out is Lil Miquela.

You can see from her posts that she was made to engage a specific audience type. And you can see that it is working as she has over 1.6 million followers and a good engagement rate which has helped her and her agency partner with brands like Samsung.


These are the 3 different ways AI is changing influencer marketing for the better. This will not only make influencer marketing more effective, but also more affordable.

9 thoughts on “How AI is Changing Influencer Marketing”

  1. Quite interesting post! I think modern social networks use such modern technologies like big data and AI for analysis. This provide a lot of new possibilities. You can use special chatbots and so on to provide better connection to your auditory. Also as I know with special services like from you can buy Instagram likes, comments and followers!

  2. Hello. Modern technologies are everywhere! I like to read such articles, now AI topic is interesting for me. And how about social networks? Is this affect them?

  3. Yep, I can agree, that such AI system is gonna help, especially in Instagram. I've heard and read a lot of comments and reviews from popular Instagram channels, how they were growing their followers database. Simple promoting services like here ( url: ) can help with those purposes in Instagram.

  4. So this is nothing more than a paid advertisement to market services to readers?
    Here’s why this is just non-sense. Fake Accounts. Someone tried to look me up online once and asked me how my three year old was doing. We don’t have a three year old. How good was that information? Not really. How many of those accts are out there? Hummmm…. let me see……….

  5. Generative adversarial networks have demonstrated the quality of AI systems can greatly benefit from evolutionary pressures. But, just like evolution of biological systems, a highly optimized trait might result from an overall undesirable system.

  6. They must hate folks that have half a brain and have learned to use it.

    They can shout themselves hoarse, but they can’t drag us to water or make us drink.

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  8. So, people become popular on social media, and then use their popularity to push various products and services, for a fee.

    Next people work out how to fake popularity so they can earn the fees, without actually selling more products and services.

    So AI systems are developed to help judge if it is real popularity, or just fake.

    So AI systems are developed to work out how to actually become more popular.

    So the AI systems themselves become popular and can sell products or services.

    So then the AI systems work out how to fake popularity, in a way that fools the AI popularity checkers.

    So we get a constant escalation battle between AI faking systems, AI checking systems, and AI popularity creation systems. Each of which needs more and more AI to either fool the other systems or detect fooling.

    An arms race develops as various influencer accounts, almost all established purely by AIs, gain billions of “followers” in days. Then the follower counts plumet by billions as AI checkers establish that all the followers are other software subroutines, then other AIs reveal that the checking AIs are actually fake checking systems developed by rival influencer accounts so the follower account shoots back up again.

    Meanwhile the actual advertising corporations can’t keep track of all this, so they hand their marketing purchases over to in house AIs that track the various influencer accounts and their current follower numbers, which fluctuate on a microsecond by microsecond basis.

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