AI Isn't Eliminating All the Jobs After All - and Marketers Need To Be Ready
- Jul 30
- 4 min read
by Scott Kabat, 621 Founder and CEO
Summary
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We’ve been hearing a lot the past few years about how AI is going to lead to mass layoffs by automating work we used to rely on humans to do. Is that prediction actually coming true?
This topic came up recently when I was talking with an engineering leader at a public tech company. His team faced the choice every leadership team is debating: use AI to do the same work with a fraction of the current staff, or keep the existing team and produce 10x the output. After considerable debate, they elected to maintain staffing and ramp up the volume and pace of shipping new products. They recognized that their competitors were likely having the same debate and that their company risked ceding their leadership position if they opted for layoffs.
A year ago, that direction would have sounded contrarian and tone-deaf to the market. Since then, the consensus has shifted notably. Recent studies recently highlighted three signs of that change: CEOs are becoming far less likely to expect AI-driven layoffs (EY-Parthenon study), companies investing most heavily in AI are hiring faster than their peers (Ramp/Revelio Labs report), and many large employers are hiring again after realizing humans are still essential alongside AI (from a WSJ article last week).
At this moment in time, the heaviest AI adopters aren't the biggest job cutters. Rather, they're among the companies whose employees are using AI to accelerate growth. While the impact of AI continues to evolve, more CEOs have figured out they have been asking the wrong question.
What Every Technology Shift Has in Common
"Will AI eliminate jobs or create them?" was always a downstream question. The upstream question is: “How can AI best help our company grow?”
So far, AI is behaving like past technological breakthroughs that fundamentally changed how work gets done. Search compressed research into a query. Mobile put market access in everyone's pocket. E-commerce collapsed the distance between wanting and buying. In each case, the winners adapted to the new customer behavior and discovered new ways to grow.
On each of these occasions we worried about jobs - but then the technology made work move faster. Some companies used that speed to cut costs, and some types of jobs did go away. The winners used it to outrun everyone else, and new types of jobs were born in the process.
Once you see AI as a speed technology rather than a substitution technology, the "cut or augment?" debate answers itself. When an innovation makes everyone faster, cutting your team and holding your current pace isn't efficiency. It's conceding the race to your competitors.
Let’s go back to that engineering team, because their choice creates a problem not enough marketing organizations are planning for.
The Ball is Coming To Marketing
If engineering ships 10x faster, the work of commercializing those new products and services lands on go-to-market organizations. Every launch needs positioning and campaigns that drive adoption, all on shorter cycles than ever.
But while product velocity can multiply, marketing budgets and headcount rarely do. No board is approving a 10x GTM team, and no company wants marketing to become the bottleneck.
At the same time, the customer journey is changing. Increasingly, a prospect's first interaction with your company happens inside ChatGPT, Claude, Gemini, or Perplexity, not on your website.
The companies pulling ahead aren't replacing marketers with AI. They're using AI to expand what their teams can accomplish – creating more campaigns, testing more ideas more quickly, and covering more of the customer lifecycle than their headcount once allowed.
Where to Start
It’s tempting to spin up a thousand changes at once, but well-intentioned transformation efforts die of ambition all the time. Start with a clear intention to build capabilities and learn:
Define your launch capacity. Work with your team to find agile, efficient ways to accommodate and/or bundle more frequent product launches, and get in sync upstream with product leadership to ensure alignment.
Pilot AI on one full workflow, not scattered tasks. Take a single campaign end to end - brief, content, variants, testing, etc. - and measure the throughput gain.
Buy judgment flexibly. Where the gap is expertise rather than capacity, leverage experienced operators for the key milestones instead of waiting on headcount. The strongest teams don't close the gap alone. They bring in resources who've run this play before, and flexible expertise for the projects that keep getting deferred.
Audit your AI visibility. Ask the LLMs about your category. What do they say about you and your competitors? Fix what's missing or wrong. It’s important to define your brand for the LLMs now, before your competitors do it for you.
Seizing the Moment
The engineering leader I spoke with wasn't really making a decision about headcount. He was making a decision about ambition.
Every leadership team will have to make the same choice. You can use AI to shrink the work, or you can use it to expand what's possible. History suggests the companies that pull ahead will choose the latter.
621 Consulting helps companies understand their AI visibility, sharpen their positioning, and build growth strategies for how customers actually buy today. Contact us to learn more.
