Stop overestimating AI and get the most out of your creative efforts

GenAI has quickly become the go-to tactical tool to boost digital marketing efficiencies, with half of recently surveyed companies saying they used it to create content, and a further 45% saying they used AI to brainstorm content concepts and ideas. However, far too many marketing leaders are using AI simply to speed up a mediocre process – missing out on the opportunity to move from reactive optimisation to a quality, proactive orchestration, and a much more profitable output.
Vanessa Bolosier, global creative strategy director at Incubeta
Vanessa Bolosier, global creative strategy director at Incubeta

How are brands getting it wrong?

The number of misconceptions about AI grows on an almost daily basis. Many digital marketing leaders see AI as a simple, cheap solution that can directly replace human talent. There is also an industry-wide belief that AI is primarily about doing tasks faster and at a lower cost, without understanding its deeper potential to enhance and amplify creative processes.

“Efficiency is great, but if you’re only using AI to produce more content, not crafting better ideas, you’re just scaling mediocrity. The value lies in using AI as a creative partner, to surface insight, guide decision-making before production even starts. It allows teams to craft their storytelling at scale with a level of nuance and precision that would not otherwise be humanly possible,” explains Vanessa Bolosier, Global Creative Strategy Director at Incubeta.

Bolosier elaborates, saying brands tend to see AI as a straightforward replacement technology rather than a collaborative tool that can empower creative teams to focus on more emotionally intelligent and strategic work. This narrow view prevents them from recognising AI's true value in areas like predictive insights, real-time optimisation, and creating more personalised, nuanced storytelling experiences.

Bring AI into the strategy process

While AI can boost efficiencies - often by orders of magnitude - it is not a plug-and-play technology that can be immediately integrated into existing workflows. It requires significant restructuring of processes and thinking. However, once implemented it can be put to work helping creative departments turbo-charge their strategic decision making.

“The smartest creative teams are using AI like a superpowered intern: fast, insightful and tireless. But it still needs human vision, taste and courage,” Bolosier says. “AI can surface patterns that humans miss. That’s when you shift from reactive optimisation to quality, proactive orchestration,” she says.

Transformative optimisation

If given the chance, AI can also play a transformative role in optimisation by leveraging machine learning algorithms to understand and predict audience engagement patterns and creative asset performance. It enables real-time iteration and adjustment of creative content, allowing teams to refine storytelling based on immediate feedback.

“By analysing large data sets, AI can test strategic ideas with synthetic audiences, providing insights before actual market deployment, which significantly reduces research time and risk. The technology allows for faster storyboarding and content creation, reducing processes that traditionally took days to just hours, thereby freeing creative professionals to focus on more emotionally intelligent aspects of their work,” Bolosier shares, adding that teams can now also use AI to test how creative will impact media performance before it goes live, minimise creative wastage, and develop predictive models for clients that want more measurable creative impact.

Don’t overthink things

While forward-thinking marketing leaders are pushing the boundaries of how AI can lend a more strategic hand in delivery, there is a risk that teams can become bogged down.

“One of the biggest traps is to use AI to scale bad ideas or poor quality creative faster. If your base creative is weak, no amount of machine learning will save it. Also, over-testing tiny iterations can kill momentum. You end up busy, not better. And when that happens the efficiency gains vanish,” Bolosier warns.

Bolosier recommends starting with tight, focused testing frameworks and then incrementally scaling up, if necessary.

“Teams should ensure their testing is anchored in what they're truly trying to achieve, maintaining a balance between data-driven insights and creative intuition. The human element remains crucial in interpreting and applying AI-generated insights effectively,” she explains.

And this is the nub of the problem. Bolosier says too many brands see AI as a tool that is tacked on to the traditional processes.

“The real magic happens when AI helps to inform the brief, and enriches its execution. That’s how you get smarter ideas from the beginning, and how you can turbo-charge the real value and creativity of your team,” she sums up.

 
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