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How generative AI is set to change the way digital and influencer marketers work

Development and integration of generative AI tools is moving at a rapid pace, changing how digital marketers work, manage data and understand their operating environment. In this interview with Kolsquare, Agence Wellcom Director Digital and AI expert Karlis Montchovi lifts the lid on how AI is set to the game for digital marketers. 

Agence Wellcom Consulting Director Digital Karlis Montchovi
Agence Wellcom Consulting Director Digital Karlis Montchovi

From large-scale, ultra-personalised communications to influencer selection based on editorial affinity rather than reach, Agence Wellcom Director Digital, and AI expert, Karlis Montchovi lifts the lid on how AI is set to the game for digital and influencer marketers. 

How much of the hype around AI is justified? Is it a real revolution? 

It isn’t a revolution in the way electricity was a revolution. It's a major evolution. Today, you don’t do things with AI that you couldn't do before; you just do them faster. If you have time and dedication, you can achieve what AI does, just slower. I temper the term revolution because AI is a super accelerator in our digital society. The difference isn't the same as going from a 56k internet connection to fibre. Faster connections didn't completely change usage, but in the digital and communication spheres, AI does. It changes how we work, understand the world, manage data, and communicate on a large scale. For example, with machine learning, you can create personalised messages for millions of people quickly, which was impossible before. It changes the game for large-scale personalisation.

That’s a major challenge in digital marketing: large-scale personalisation. We can no longer use a single message for everyone because communication paradigms have changed. Now, everyone can be the messenger. Brands must understand their audiences deeply, find the right communication codes, and distribute messages on various channels. Automation, often mistaken for AI, helps companies communicate better. Distinguishing between automation and AI is crucial. Often, what is called AI in processes is just automation using scripts for repetitive tasks.

What are the limits to AI? 

There are two aspects. When I train colleagues, the initial feedback is that it’s magical and can do everything, even potentially take their jobs. But after using it, they realise it’s flawed and requires guidance. They understand that AI isn’t automatic or magical; it needs briefing and training. Once trained, AI becomes powerful. The limit is us, but if we don’t train it well, it won’t correct our limitations. 

However, machines can work 24/7, moderating social media automatically, which is magical in its own way. There are physical limits; it won't help you drive a car, but intelligently applied, AI can make tedious tasks less burdensome.

AI can revolutionise research. Instead of manually browsing multiple articles to gather information, you can instruct AI to synchronise and analyse numerous sources quickly. This was previously impossible.

Social networks are rapidly integrating AI tools into the platforms; what impact will that have on the user experience? 

It’s already here. Facebook's algorithm decides what content appears in your feed based on its understanding of you. It’s not necessarily better but works based on your interactions. Back when I first used Facebook, you saw 100% of your friends' posts, which was great. Now, algorithms prioritise content for engagement and revenue. An ideal social network would allow users to reset and customise their feed based on current interests, filtering out unwanted content. TikTok tries this, but not perfectly. Hyper-personalisation is great, but users should have control over the content they see.

And conversely, what you see now on social media is that when you make a post, you're told to use AI to write the post, generate the visual, make videos, titles, etc. That’s where I see a big bias because these AIs are trained using the content from social platforms, and if the person isn't careful, they'll replicate what's already been done. We’ll end up in a kind of algorithmic bubble where it’s very difficult to stand out. What we used to love about social media was discovering accounts that had a personal touch, which made us want to subscribe and see more. Once you decide your editorial line on LinkedIn or Facebook—be it humour or something else—if it's automated, it won't be the same. 

What worries me is that the generated content could be conditioned by the context and rules defined by the social platforms. If I want to publish content that might be deemed offensive by the platform, I won't be able to. However, there is a great advantage: at least there won't be content with orthographic and grammatical errors. I see a huge benefit in having AI on social media. It will spare us from seeing content that hurts the eyes!

Many talk about the idea of Synthetic Social Networks, where we’ll interact as much with bots and AI-generated content as we do with real people; what’s your view? 

It’s complex. If the content entertains, its origin might not matter. But the issue is when fake content is presented as real. Like scripted reality TV, where reactions are staged, it’s misleading. This doesn’t bother me much, but for younger audiences, distinguishing fake from real content is crucial. AI-generated educational content must be accurate to avoid misinformation.

I worry more about Artificial General Intelligence (AGI), which can learn and adapt autonomously, posing significant risks. Basically an AGI is a system of multiple AIs that can understand, make decisions, control solutions, and continue to learn without being controlled. On this, I side more with the pessimists, there is a huge risk here. 

In relation to electoral manipulation, the question isn’t so much about producing content, it’s about whether the platforms have a responsibility in distributing this content. 

Scientists have been talking about AGI for more than 50 years, how close is it to becoming a reality? 

ChatGPT’s advancements hint that AGI might be closer, potentially within two years, but we need safeguards before public release. 

It's a question of which player is going to be able to bring out an AGI that can feed on accessible data and also be able to put in place safeguards. 

When OpenAI presented SORA, their hyper-realistic video generation tool, they said: "This is great, we have the most advanced solution on the market." But, very soon afterwards, they announced that they would not be giving access to the general public for the time being, as they didn't know what people could do with it and what purpose they might misuse it for. Cynicism or a protective measure in case things get out of hand?

What impact will generative AI have on creativity?

Creativity will evolve. While AI can generate art and text, the core of creativity—ideas and perspectives—remain human initiatives. AI can’t yet question or challenge ideas, a critical part of creative processes. Agencies and creators might use AI for production, but the essence of creativity lies in human ideation. The unique human touch in conceptualising and executing ideas is irreplaceable.

AI accelerates content creation but doesn't make one inherently more creative. It’s a tool, not a creator. For instance, an AI might generate visually stunning graphics, but the conceptual spark behind a campaign still needs human input.

How should influencer marketers be thinking about AI?

In influence marketing, AI aids data processing, tagging content, and identifying suitable influencers by editorial affinity rather than just profile reach. The ability to analyse vast amounts of data and tailor content accordingly is a significant advantage for modern marketers. Automation makes it possible to crawl all the engagements, all the content, thematise it, label and afterwards to summarise it. This approach will evolve, potentially changing agency models. Our customers, our advertisers, may be more intelligent because they'll have access to data and platforms, and may once again integrate platforms that produce their own content, perhaps generated by an AI. 

This interview was conducted in French, transcribed using AI transcription tool Amberscript, translated and edited by ChatGPT, and edited manually by Sophie Douez

About Kolsquare

Kolsquare is Europe’s leading Influencer Marketing platform, a data-driven solution that allows brands to scale their KOL Marketing strategies and implement authentic partnerships with KOLs (Key Opinion Leaders). Kolsquare’s technology enables marketing professionals to easily identify the best Content Creators profiles by filtering their content and audience, and to build and manage their campaigns from A to Z, including measuring results and benchmarking performance against competitors. Kolsquare has built the largest community of influencer marketing experts in the world, and offers hundreds of customers (Coca-Cola, Netflix, Sony Music, Publicis, Sézane, Sephora, El Corte Inglés, Lacoste, …) the latest Big Data, AI and Machine Learning technologies to drive inspiring partnerships, tapping into an exhaustive network covering 100% of  KOLs with more than 5,000 followers in 180 countries on Instagram, TikTok, Twitter, Facebook and YouTube. As a Benefit Company, Kolsquare has been pioneering Responsible Influence by championing transparency, ethical practices, and meaningful collaborations to inspire change.

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