Artificial Intelligence vs. Human Creativity in Marketing

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Every industry will be dramatically disrupted by artificial intelligence (AI) applications in the very near future—if they haven’t already been. By 2020, businesses that use AI to uncover new insights will take $1.2 trillion each year from competitors that don’t, according to Forrester.

For digital marketers, AI brings many advantages, including help in understanding data more quickly and acting more immediately to improve customer personalization.

But, AI and machine-learning (ML) on their own are not panaceas.

Although these revolutionary technologies have already disrupted digital marketing and advertising, and will continue to do so, it’s still vital to maintain the human touch in order to sustain creativity and fully understand the nuances of human behavior.


Understanding the ‘Explore vs. Exploit’ Dynamic

In the AI world, there’s the notion of exploring versus exploiting: To explore is to delve into the unknown, trying to find the general boundaries and developing initial definitions; to exploit is to refine and drill down, making the most of known resources.

Though AI and ML are ideal for exploiting, humans are much better suited for exploring.

Ad creative is a great example of how this dynamic plays out. Although AI, through things like computer vision and dynamic creative optimization, can help you exploit existing assets and make them more powerful through personalization, it’s not great at coming up with initial ideas that really resonate.

Consider this AI-created ad for Lexus. It’s fine, but it doesn’t hold a candle to truly memorable (human-created) creative. Ultimately, you still need humans to explore and come up with fantastically resonant ad creative.

How AI and ML Are Dramatically Reshaping Digital Marketing


In mobile advertising, we have decades of experience in exploring new campaign angles and developing truly amazing creative. The exploiting side of the equation is still nascent in comparison.

By adding unprecedented levels of intelligence to every aspect of digital advertising and marketing, AI is improving campaign results and reducing stress for mobile marketers in the following key ways:

  • Improving ad campaign performance at the creative level. AI-powered advances in computer vision improve the effectiveness of ad creative. By analyzing previous campaigns, this kind of AI can determine how a particular creative will perform for a given audience—before the creative is pushed live.
  • Providing more nuanced portraits of target customers. Through AI, marketers can create detailed, precise portraits of user groups without having to rely on or turn to personally identifiable information such as names and contact information. By analyzing behaviors, AI can spot surprising connections between disparate variables, such as previous click behaviors, anonymized location information, and frequency of app use.
  • Guaranteeing brand safety. Alongside fraud, brand safety is another major concern for mobile marketers. In fact, it’s been a problem noted by 75% of marketers. But preventing it from occurring entirely in programmatic media buying is not always straightforward. After all, what’s safe for one brand could be unsafe for another, and blanket bans unnecessarily limit reach. AI can help by quickly determining in real-time whether a placement is appropriate or not at the brand or campaign level.
  • More effectively fighting fraud. As the mobile advertising industry has grown, fraudsters have unfortunately followed the money by targeting this space with greater ferocity. Between 2017 and 2018, mobile ad fraud close to doubled; but, now, AI is here to help in the fight. Through AI, we can more accurately predict when ad fraud is most likely to occur, and take pre-emptive action so it never crops up in the first place.

AI algorithms help marketers better understand their prospects while still respecting their privacy.

Limitations to a Tech-First Approach

Though AI and ML will continue to positively disrupt mobile marketing and digital advertising, they’re hardly foolproof. In many instances, AI purports to be faster and more accurate than humans but fails to execute properly and effectively.

Consider voice as an example. AI-powered voice recognition technologies like Siri, Alexa, etc. have proven incredibly adept so far, but they’re not perfect. The recent viral video sensation of a little girl trying to get Alexa to pay “Baby Shark” is adorable, but it also shows how voice recognition isn’t yet adept at recognizing a wide range of human voices. Well-trained human ears can hear what she is trying to do here, but machines aren’t quite there yet.

Of course, even the most intelligent systems can fail to predict the future. Many AI applications use some sort of predictive analytics-based ML algorithm in which many previous outcomes are analyzed to help predict future behaviors and actions. This method has proven to be enormously accurate, but it’s also not foolproof. Just because something happened in the past doesn’t mean it’s bound to happen in the future.

Benefits of Combining Artificial and Human Intelligence

So, what’s the way forward? How can marketers and advertisers gain the benefits of AI and ML while also avoiding its pitfalls? The key is to strategically and cohesively marry human and machine intelligence.

The key is to know and fully understand the strengths and weaknesses of each. Where does AI really excel, and where is human intelligence better?

Rote, data-heavy tasks are perfect for computers, whereas human intelligence is best for more creative and off-the-wall pursuits. In addition, it’s often ideal to let AI do the heavy lifting of analysis, but then to let humans serve as the final check.

Forrester is right to predict AI’s ascendance. But AI won’t be a force for good across the marketing space unless it’s married with human intelligence and insights.

What’s the right balance between explore and exploit? That all depends on an organization’s current needs and gaps in its marketing strategy. For the benefits of creativity and hard ROI to be fully combined, ultimately both the human and the computer will need to be present and working together.



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