Most Marketers Mistakenly Equate “AI” with “Chatgpt,” which Operates with Preset Parameters
Imagine sitting down at a Formula 1 car’s cockpit.
Will you navigate the track with the precision of Lewis Hamilton or merely stall at the starting line?
The car isn’t limited by its engineering but by the skill of its driver.
This analogy highlights the core misconception in today’s AI-driven marketing landscape: the belief that AI requires no expertise to wield effectively.
A year ago, Peter Weinberg and Jon Lombardo left cushy LinkedIn jobs to explore the intersection of generative AI and marketing science.
Now, after partnering with elite marketing organisations, they’ve unveiled a game-changing blueprint for AI adoption—the “Three Laws of Leverage.”
Here’s what you need to know.
1. The Conductor’s Code: Mastering AI as an Instrument
AI is like an orchestra, with different models excelling in unique roles.
Some models perform best at low “temperatures” (providing structured, logical outputs), while others thrive in high-temperature settings (delivering creative and unexpected ideas).
The magic lies in knowing when and how to “conduct” these models to achieve marketing harmony.
Most marketers mistakenly equate “AI” with “ChatGPT,” which operates with preset parameters.
But AI offers a vast range of possibilities—if wielded by someone who’s honed their craft.
Marketers should think beyond generic outputs, leveraging AI’s diverse capabilities to achieve both computational precision and artistic brilliance.
“When someone says, ‘AI can’t do X,’ what they’re really saying is, ‘I can’t get AI to do X.’”
2. The Picasso Prophecy: Asking the Right Questions
In 1968, Pablo Picasso dismissed computers as “useless” because they “only give you answers.”
Ironically, this sentiment perfectly encapsulates the AI revolution.
The real power of AI lies not in what it can do—because it can increasingly do anything—but in the marketer’s ability to ask the right questions.
Take brand awareness versus mental availability.
Awareness tells you people know your brand exists, while mental availability reveals if your brand comes to mind during crucial buying moments.
With AI, marketers can now field 100 studies across multiple categories and markets in the time it used to take to conduct one.
But without the foundational knowledge to ask for mental availability metrics, these capabilities remain underutilised.
Key Insight: As answers become abundant, the competitive edge belongs to those who ask smarter questions.
3. The Synthetic Strategy: Tackling Marketing’s Hardest Jobs
Marketers often delegate AI to easy tasks like writing social posts.
But the real gains come from deploying AI against complex challenges like segmentation, targeting, and positioning (STP).
Traditional marketing strategy is a costly, time-consuming nightmare.
It takes months and hundreds of thousands of dollars to develop a static strategy that may quickly become obsolete.
AI flips this script. With lab-grown strategies, you can:
Rapidly test and iterate on segment definitions.
Experiment with targeting priorities in real-time.
Adapt strategies instantly to shifting market conditions.
Instead of a once-a-year exercise, strategy becomes an ongoing conversation—faster, cheaper, and infinitely more dynamic.
Takeaway: The greater the challenge, the greater the potential for AI-driven disruption.
The Bubble That’s About to Burst
The biggest misconception in marketing today isn’t that AI is overhyped; it’s that most marketers are underutilising its potential.
Treating AI as a glorified copywriting assistant instead of a strategic powerhouse limits its transformative possibilities.
“The bubble isn’t in AI—it’s in AI denial.”
For marketers ready to embrace the future, it’s time to rethink how AI fits into your workflow.
Are you orchestrating AI models like a skilled conductor?
Are you leveraging it to ask better questions?
And most importantly, are you using it to solve your hardest challenges rather than your easiest tasks?
