Between a booming economy and AI tools rapidly changing entry-level roles, marketing jobs — and much more — can feel unstable.
There is a silver lining for those willing and able to seek it.
In marketing, it’s this: professionals who can adapt, think critically, and thoughtfully integrate AI into their work can accelerate workflow, sharpen strategy and targeting, and spend more time on programs that drive meaningful impact.
It’s still early in the AI era, but more than a decade as a marketing leader has made some clear patterns.
Across my team and the internal teams we work with, some PPC marketers are better positioned than others to succeed as AI reshapes the role.
You can never keep up with the volume of new AI tools entering the market.
What you can do, and what you should do, is to understand which tools you should check out and why.
Testing for the sake of testing is an end in itself.
If you can’t clearly define the outcome you hope to achieve, there is little benefit in understanding how the tool works on its own.
Choosing the right tools to test is only the first step.
It’s equally important to define how you’ll measure results and, if your output shows promise, how the system fits into your broader mix of martech channels and tools.
I have already seen many examples of AI tools being enthusiastically adopted, only to remain unused or create unintended consequences after being quickly integrated and without considering the existing architecture.
Successful marketers in the age of AI are not just users of tools. They are strategists of tools.
They objectively evaluate, objectively measure, and understand how each system fits into the broader marketing mix.
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2. Be a stubborn critical thinker
Many AI tools can deliver information or output. But then what?
Almost every marketing leader has seen examples of outputs being accepted and used without hesitation.
The best sellers are ahead. They question assumptions, interpret results, and grasp the reasons for anything unexpected.
Critical thinking also depends on understanding how ad platforms and algorithms evolve over time.
Marketers who have lived through multiple iterations of Google Ads or Meta ad delivery systems understand how dynamic changes can be in terms of performance.
But new marketers can build that same depth by digging into:
- What’s going on under the hood.
- What platforms do they actually prepare for.
- What data can they feed into AI training systems.
3. Balance curiosity with discipline
Curiosity fuels learning, exploration, and creative problem solving.
But in the age of AI, curiosity must be paired with discipline.
With so many tools and ideas competing for attention, and without a strategy to harness the power of AI, things can move quickly.
Another early defense is learning to distinguish between what’s interesting and what really impacts clearly defined business outcomes, like driving pipelines or improving retention.
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4. Look at the whole picture
AI excels at optimizing:
- Finding patterns in data.
- Personalize the experience.
- Automated responses.
The harder it is, the more marketers can separate themselves from their tools and their peers.
For example, AI might recommend a bid strategy or a new ad format, but it won’t explain how that choice fits into a company’s broader media mix, product strategy, or customer journey.
Successful marketers learn to reverse the image.
They interpret AI results through the lens of business goals, product strategy, and audience behavior, not tool bells and whistles.
5. Develop technical depth (not just superficial skills)
AI can automate campaigns, but it cannot replace deep technical understanding.
On my team, the people who make the most rapid gains in clients go beyond discussing KPIs and can diagnose the reasons for their progress, or lack thereof.
Successful marketers in the age of AI bring both art and science to the table. They can:
- Explore and interpret data at a granular level.
- Understand how ad platforms deliver impressions and conversions, a few layers deeper than what the tools show at the top.
- Resolve confusing problems or unexpected results.
- Point out when an “intelligent” algorithm decision is illegal.
This level of technical fluency builds trust and helps ensure that if the AI makes a mistake, you have the knowledge and ability to catch it.
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6. Always doubt yourself automatically
One of the biggest dangers in marketing is overconfidence in automation, whether it’s new features, performance reports, or AI-generated content.
That doubt is not mistrust. It’s about stewardship.
Just because an AI tool can do something doesn’t mean it should.
Smart marketers put up guardrails to test the limits of automation, validate output, and keep AI in a role that supports human judgment rather than replacing it.
Dig deeper: 4 times PPC automation still needs a human touch
7. Take ownership and accountability
One thing AI can do is take responsibility.
Whatever you put in front of the client, whether it comes directly from AI or not, is up to you.
That concept is important.
In an era where marketers are using AI for everything from campaign planning to content creation, accountability is what separates the pros from the newbies.
Before sending any AI-assisted work out into the world, marketers should ask: Is this accurate? On the product? Ethics? Do you have an understanding?
If any of those answers sound shaky, think twice before putting it out there and putting your reputation on the line.
8. Champion AI management and product safety
AI dominance is emerging as a core competency for modern marketers.
Tools from platforms like HubSpot, Meta, and Google now offer AI-assisted features for targeting, optimization, and reporting.
With those capabilities come real risks in terms of privacy, permissions, and product security.
Marketers need to act as stewards of their brand reputation by setting clear guidelines for how AI is used internally and externally.
That includes:
- Updates data sources.
- Establishes approval procedures.
- Ensuring that AI-generated content is consistent with brand voice and legal standards.
Teams that leave management entirely to IT, if they commit to IT support, are taking a huge risk that can easily be reversed.
9. Measure what matters
AI can measure everything, but that doesn’t mean everything is important.
Leading marketers focus on metrics that connect directly to business results.
That often means going beyond click-through rates and A/B testing to evaluate full funnel performance.
In our work with clients across a wide range of verticals and maturity levels, I’ve seen many cases where letting go of what appears to be “working” at a high level, such as lowering a lead’s CPA, leads to stronger results with more advanced strategies, such as adopting a higher lead CPA to significantly improve lead quality.
AI does not change this fact, but it does mean that you will go faster where you choose.
Make sure targeting is tied to real business results, not fancy marketing metrics.
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10. Sharpen your soft skills
When AI helps level the technology playing field – and it does – human skills become the difference.
In the automated world, it is very difficult to prove that different pitch strategies are different.
Emotional intelligence, strategic thinking, storytelling, communication, and good judgment cannot be replaced by bots.
Marketers who develop these skills will always be limited.
They are the ones who can translate AI capabilities into product value, lead teams through change, and maintain the human touch in an increasingly automated world.
It’s a mix that defines great marketers
AI is reshaping what it means to be a great marketer.
The most successful marketers in this new era will be those who combine technical fluency with a willingness to adapt, think critically, be accountable, and be creative.
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