Note: Today’s post was created by {grow} Community Member David DeLallo
My first interaction with ChatGPT was early last December. At the time, I was McKinsey & Company’s Executive Editor for AI. And with nearly a decade in the AI arena under my belt, I’d witnessed the tides of hype rise and fall. So, I approached ChatGPT with a healthy dose of skepticism.
Here’s how the experience unfolded:
Me (typing): Create a blog post about five ways businesses can use AI to generate new revenues in the style of McKinsey and Company.
ChatGPT: (Spits out 500 coherent and stylistically on-point words. Time elapsed: less than 10 seconds.)
Me: 
The piece had its flaws. But I’d seen worse first drafts from humans that likely took many hours to craft.
Awe and existential dread washed over me. Was this technology as revolutionary as it seemed? And what did it mean for my career?
Soon I was busy fast-tracking perspectives on generative AI and immersing myself in this new world. But fears about my future persisted. Was I going to be replaced by this thing?
Adapting to survive–and thrive
Fast forward to today. I’ve talked to dozens of writers and marketers and find we generally fall into one of three camps.
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Nope. You’ve dabbled in ChatGPT with a few basic prompts, found its responses underwhelming, and dismissed it as hype.
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Panicked. You’ve seen its power, completely freaked out, and ordered the book “What Color Is My Parachute?” to help you choose between nursing school and parlaying your woodworking hobby into a new career in carpentry.
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Adapting. You’re among the 37% of marketers who’ve adopted generative AI tools at work, but you’re still a little worried about what your future in marketing will look like.
It’s time for us all to migrate toward Adapting. Whether we want this or not, our marketing careers will change. But they will not end — as long as we embrace AI as an invaluable sidekick to amplify our skills, increase our knowledge, and accelerate our work.
I’m so confident in this perspective that I left McKinsey in June to open my own business. With generative AI by my side, I’m providing writing and content marketing services to companies looking to tell their technology stories.
Here’s why I think AI will propel my career … and yours.
A tale of two marketers
Consider the following scenario:
A tech company is launching a new AI-powered product and wants to create a comprehensive marketing campaign. It subscribes to an AI tool that can generate content, analyze data, and suggest marketing strategies.
The Novice Marketer + AI: A young marketer, let’s call him James, is excited to use the AI tool. He inputs basic information about the product and the target audience. The AI spits out a content calendar, some blog post drafts, and even a few social media post suggestions. Thrilled, James pushes the tool no further and approves them with little scrutiny.
Result? The campaign goes live. It’s…meh. The blog posts are informative but the campaign doesn’t resonate with the target audience of tech-savvy professionals, resulting in high bounce rates on posts and mediocre social engagement. The AI tool did a decent job, but it couldn’t master the nuances that come from understanding the industry and the audience.
The Expert Marketer + AI: Now, let’s consider Jen, who has 10 years of experience in tech marketing. She uses the same AI tool for the campaign and receives similar output, but iterates with the tool to get more compelling content and recommendations.
Still, as Jen reviews the AI-generated content, she immediately spots areas for improvement. The blog posts lack common tech industry terminology and includes some unnecessary genderizations. She makes several critical edits and cross-checks everything to confirm accuracy. She adds links to helpful resources she’s relied on in her career.
Jen knows the best campaigns are driven by data. She notices the AI tool’s data-crunching feature and uses it to guide the campaign strategy. She also manually adds a webinar to the content calendar since she knows it’s an effective way to engage the audience in her industry.
Result? The campaign is a smash hit. Tech professionals share the blog posts widely, the social media posts generate meaningful conversations, and the fully-booked webinar pulls valuable leads into the funnel.
The Takeaway: In both scenarios, the AI tool was the same, but the outcomes were drastically different. Jen’s expertise allowed her to use the AI as a lever and she knew where the AI’s capabilities ended and where human expertise needed to take over.
The early data says…
Support for this view goes beyond the anecdotal. It’s in the results of early research on the effects of using generative AI tools–if you dive beneath the headlines.
You may have seen social media posts touting results of studies that indicate AI “levels the playing field” by boosting the capabilities of inexperienced professionals more than experienced ones in tasks like basic business writing and creative writing.
However, it’s important to understand what’s measured and how participants interact with the tools during these experiments.
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No context needed. The researchers in the business writing study, for example, admit that the writing tasks didn’t require special knowledge on the subject participants were writing about, so “the findings might make ChatGPT look more useful than it would be in a real-world situation.” Remember, Jen had knowledge about marketing in tech. James did not.
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Tied hands. Digging into the depths of the creative writing study reveals it also presents an oversimplified conclusion that AI is the great leveler. Not only do the more inherently creative participants still perform the writing exercise better than others–with or without AI assistance–but the researchers also note that participants weren’t allowed to customize prompts or interact with the tool multiple times. Such steps have been shown to significantly improve AI outputs. And, as in the case of Jen, the inherent knowledge helps someone know what to prompt for and how to do it effectively.
I’ve yet to track down a scientific study that gauges ChatGPT-assisted marketing performance specifically. But a McKinsey study on the ways generative AI coding tools aid software developers serves as an interesting corollary since the profession requires specialized knowledge. AI enabled coders to do simple tasks in half the time, but saved them only one minute out of every 10 for more complex tasks. And some tasks took less experienced developers as much as 10 percent LONGER to do WITH generative AI tools.
Learning loops favor experienced marketers
Of course, AI will get better. The underlying technology isn’t called “machine learning” for nothing. As we feed AI tools more data, refine their algorithms, and interact with them more, they’re bound to get smarter. But so will we.
Even if AI can one day do nearly everything the experienced marketer can do, this learning loop favors the advancement and participation of humans–especially those with more career time clocked.
Leveling up. Consider what will happen over time as Jen uses the AI tool. She can ask it to challenge her thinking and increase her knowledge. When she shares her qualitative experience with it, the AI will incorporate the information and provide more nuanced suggestions. These new suggestions will spark new ideas for Jen. This loop of mutual improvement keeps spinning.
Providing moral compass. Even if we program a machine to understand ethics to some extent, the ultimate moral responsibility lies with humans. Jen ensures that the machine’s actions align with our broader ethical and social values.
Eyeing for errors. We haven’t yanked pilots from planes just because autopilot exists. Similarly, no CEO who’s poured years and capital into a business is going to let a machine run the show without human oversight. The stakes might differ, but the principle remains the same.
And how will Jen stay ahead of James?
Using Spidey sense. Jen’s years in the game give her the ability to discern good data and recommendations from bad. She knows when to trust the AI and when to question it, a skill James hasn’t mastered yet.
Structuring questions. She knows what to ask the AI and how to phrase questions to get the best answers faster. James is still learning the ins and outs of marketing, which could slow down decision-making.
Thinking big picture. Jen can synthesize AI’s insights with a broader understanding of business goals, something that comes with experience. James might focus too narrowly, missing the bigger picture.
Evoking emotional intelligence. Finally, let’s not forget about emotional intelligence, which many experts believe could remain standing as the last frontier for AI to conquer for some time, if ever. Jen’s years in the field enable her to add a layer of human understanding to the AI’s outputs that James hasn’t developed yet.
The path forward is (still) continuous learning
At a fundamental level, does AI really present us with a novel career challenge that requires a radically new solution? We’ve faced numerous technology-led paradigm shifts, like marketing digitization and programmatic ad buying, to name a few. The successful response has always been learning and adapting.
So, use the AI tools. Understand their strengths and weaknesses. Learn from them.
But also keep reading books (especially Mark’s 
As long as we keep these practices up, AI won’t end our marketing careers; it will simply propel them to new heights of interest and success.
