AI, Hidden Innovators & Finding Stability for the Media Holding Companies
Artificial Intelligence (AI) is reshaping the media and advertising industry, delivering measurable efficiency gains in tasks from media optimization to creative production. Yet a dominant assumption is that each percentage increase in productivity should translate directly into proportional staff reductions.
This thinking is not only flawed but potentially damaging to an industry that has already hollowed out its talent base, sacrificed quality for volume, and left itself vulnerable to commoditization. AI risks accelerating this cycle unless agencies redirect productivity gains toward higher-value strategic and creative work. Layoffs tied to AI efficiencies don’t create sustainable value—they weaken it.
I’m not anti-AI. Quite the opposite: I’ve built systems to elevate client deliverables and am developing two AI-driven media optimization products right now. My point is this: when AI is treated as an amplifier of talent rather than a replacement for it, agencies can stabilize operations, unlock growth, and strengthen their competitive position. The real dividend isn’t productivity, it’s possibility.
The Fallacy of the Productivity Dividend
The logic of “AI makes us 20% more efficient, so we can reduce staff” has gained traction across global organizations. But efficiency does not equal elimination.
Orgvue’s analysis of the Fortune 500 found that for every $1 saved through layoffs, companies incurred $1.27 in severance, disruption, and lost productivity costs. Even more striking, only 19% of firms that cut jobs in 2024 experienced revenue growth, while the majority stagnated or declined.
For agencies, where the product is intellectual capital, this erosion is even more acute. FTE roles are client-funded. Cut too deep, and you risk jeopardizing relationships by charging for resources that no longer exist or are dangerously thin.
Consider a lesson from outside the industry: IBM. After automating routine tasks, IBM reinvested savings into programming, sales, and marketing talent. The result: $3.5 billion in productivity improvements across more than 70 AI use cases, with workforce growth overall. The model is this; redeploy efficiency into higher-value roles, creating capacity for expansion rather than contraction.
Debunking the Efficiency Myth
Even the assumption that AI inherently accelerates productivity deserves scrutiny. In July 2025, research group METR conducted a randomized trial with experienced software developers using AI coding assistants. Developers predicted the tools would double their speed. Instead, those with AI support were 19% slower, spending more time validating and correcting outputs.
This study highlights a crucial reality: AI’s efficiency is highly context-dependent. Generative AI excels at routine, bounded tasks, resizing creative assets, compiling reports, drafting copy; however, its outputs still require human validation and strategic framing. In knowledge work, productivity gains are rarely linear.
Michael Farmer’s Madison Avenue Manslaughter underscores the danger. Agencies have long accepted larger scopes of work for diminishing fees, eroding margins and overworking staff. Applying AI to accelerate output without redefining value risks worsening this cycle. True efficiency comes not from replacing headcount but from redeploying human talent toward higher-order activities that AI cannot replicate.
Augmentation Over Automation
Organizations that treat AI as augmentation, not substitution, are already demonstrating stronger outcomes.
PwC reports that industries most exposed to AI adoption have seen revenue per employee grow three times faster than less-exposed industries since 2022. Employees with AI skills now command a 56% wage premium over peers. Augmentation doesn’t diminish the value of talent—it multiplies it.
Unlocking Hidden Innovators
The most overlooked opportunity lies within existing teams. Surveys show that 75% of global knowledge workers already use AI tools, with nearly half adopting them in the past six months. Yet adoption is largely grassroots. Over half of these employees report reluctance to disclose their usage to managers, fearing it may make them appear expendable.
At the same time, only 31% of workers report receiving formal AI training, while 56% feel unprepared for AI’s impact on their roles. This disconnect suggests that many organizations are sitting on a reservoir of innovation but lack the systems to surface and support it.
Agencies can gain immediate advantage by identifying and empowering these “hidden innovators.” Creating forums for experimentation, incentivizing knowledge-sharing, and aligning recognition with AI-enabled improvements can accelerate adoption and strengthen culture. Empowering internal innovators also reduces attrition risk: employees who feel valued for their AI fluency are less likely to exit for competitors—or vibe quitting in favor of their own business.
Buying Time for Growth
AI adoption presents leaders with a choice. One path is short-term: cut costs, reduce headcount, and present an immediate margin improvement. The other path is strategic: redeploy efficiency gains into higher-value roles, invest in training, and expand service offerings.
The first approach risks a downward spiral of talent erosion and commoditization. The second builds resilience by stabilizing operations, strengthening client value, and positioning organizations for long-term relevance. Evidence across industries demonstrates that AI’s greatest returns come when it is treated as an accelerator of human capability, not a replacement for it.
Conclusion
AI is not a mandate for downsizing. It is a catalyst for rethinking how agencies create value. Productivity gains should be reinvested in human talent—freeing strategists, analysts, and creatives to deliver deeper insights and more ambitious ideas.
Agencies that follow this model will avoid the trap of “doing more with less” and instead usher in a period of sustainable growth. For media and marketing leaders, the imperative is clear: treat AI as fuel for augmentation, not as a license for attrition. The real dividend isn’t productivity, it’s possibility.