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  • Sean Dougherty
    Written by Sean Dougherty

    A copywriter at Funnel, Sean has more than 15 years of experience working in branding and advertising (both agency and client side). He's also a professional voice actor.

The recent emergence of generative artificial intelligence tools has shaken the marketing industry to its core. In fact, according to recent Funnel research, 64% of marketers are concerned that AI may replace their jobs within the next five years.

But how concerned should you actually be? After all, AI (in some form) has existed for decades. Siri and Alexa are two perfectly imperfect examples of this. Plus, tools like Grammarly can help non-writers better put their thoughts into words while checking their spelling and grammar. 

So what’s different now? 

A quantum leap in capability

The real paradigm shift occurred in the second half of 2022. That’s when generative AI tools like MidJourney and ChatGPT were launched to the public. For years, AI researchers hinted at the promise of these sorts of tools — and the potential disorientation they might cause to markets. 

It wasn’t until the general public got their hands on these tools that marketers really started to pay attention. Almost overnight, it seemed, anyone interested in graphic arts could suddenly become a designer. All it took was to prompt MidJourney or DAHL-E with a few words. 

At the same time, the entire world became enamored with the speed and ease that ChatGPT could write poetry, recipes, and even code.

Marketers, who once thought they were impervious to technology-driven upheaval, suddenly felt their careers in the cross hairs. 

How can marketers keep up? 

In order to keep pace with technological change, marketers everywhere need to refine, update, and evolve their skillset. When we spoke with marketers, 85% said they wanted to update their capabilities. 

Additionally, 58% of marketers said that improving data analysis skills was at the top of their list. 

Why data skills? It’s quite simple actually. Despite the illusion that these AI systems are digital humans, they are just machines that have ingested and interpreted huge amounts of data. Their outputs (be it text or imagery) are the result of predictive models based on said data. 

To leverage and build proprietary AI solutions for your business or marketing team, you too will need to have solid data skills in order to effectively use these machines. 

How powerful is current-state AI?

The key point to consider when thinking about new AI-powered technologies is to avoid panic. Our performance marketer Tommy Albrecht encapsulated this thought perfectly.

“Feeling uncertain, or even nervous, about how AI will change you and your team is natural,” said Tommy, “but the important thing is to focus on productive worry. What pivots and planning do you need to complete to stay goal-oriented and relevant?”

In fact, if you ask experts in the creative fields what they think of new generative AI tools, many are impressed but not blown away. 

You see, while it’s impressive that these tools can create new works from a few words in a prompt, the general quality and innovative capacity of these machines still isn’t really evident. Instead, these tools are more like remixing engines. 

Plus, any copywriter worth their salt can tell you that nearly every copy-focused AI tends to create work at the level of a student. It’s often redundant and lacks any real viewpoint. 

So, let’s breathe a sigh of relief and redirect our energies in a more productive direction. 

It all comes back to data

As mentioned above, solid data skills are required to build and manipulate your own AI tools. Beyond building a proprietary tool, though, strong data analysis skills still provide a highly competitive angle for humans to exploit.

While AI tools can help automate, organize, and expedite the collection of your data (a godsend for marketers), they have difficulty contextualizing. For instance, while advanced AI may be able to spot trends and key insights, it can’t tell you what that means to you business. 

Say you’re running a pre-IPO tech scale-up based in Europe and expanding to Australia. Your AI may be able to identify that your big bet targeting this new market may be paying off — thanks to a strong increase in conversions. The AI may see that customer acquisition cost in Australia is lower than for the European market. 

What AI can’t tell you, though, is how to balance further investment into this new market against the opinions of investors who may want to stabilize the balance sheet for the upcoming IPO. This sort of real-world impact analysis still has to be evaluated by a human being. 

After improving data skills, what’s next? 

As you probably guessed, improving your data analysis skills is only one facet of the multi-pronged upgrade you will have to put yourself through. Luckily, we’ve encapsulated the best moves for you. 

All you need to do is head over to our Marketing Data State of Play 2024. There, you’ll find  the highlights from our latest industry research, along with the top six moves to make if you want to stay ahead of the AI revolution. 

Contributors Dropdown icon
  • Sean Dougherty
    Written by Sean Dougherty

    A copywriter at Funnel, Sean has more than 15 years of experience working in branding and advertising (both agency and client side). He's also a professional voice actor.