Content Strategy In The AI Age
Oh, how the world of content strategy has grown up so fast… Just 3-4 years ago, we were optimizing blog headlines and A/B testing email subject lines. Today, we’re on the chopping block to design content architectures where AI and human creativity work in concert to create multiplication effects across channels. The transformation has been swift, profound, and largely misunderstood.
And yet, many content strategy leaders either haven’t identified this change or refuse to adapt accordingly. Most are using AI simply as a productivity tool—a faster way to generate more of what they were already creating. But this approach misses the fundamental shift happening beneath our feet. AI hasn't only changed how we create content, it's changed what content strategy means entirely. Let’s talk about it.
The Great Leveling
Hyperbolic as it might sound, AI has democratized content creation in ways that make the printing press look incremental. A content generalist can now create agency-level ad images with ChatGPT, produce tightly edited videos with AI-powered tools, and generate high-converting sales copy using custom GPTs. The bar for basic content creation has been lowered to nearly ground level.
This creates what I call "the great leveling"—when everyone has access to the same powerful tools, previous competitive advantages evaporate overnight. Scale, which was once a moat, is now table stakes. Quality, which used to require specialized talent, is increasingly accessible to anyone with the right prompts and artistic taste.
But here's what most strategists are missing: When the floor rises, the ceiling disappears.
The companies and creators who will dominate aren't those who use AI to create more content faster. They're the ones who understand that AI has fundamentally changed the game being played.
Beyond Productivity: Architectural Thinking
While others optimize for efficiency, the most successful content strategists are rebuilding their entire approach around what I call the "Human Touch Advantage."
When AI can generate decent blog posts for everyone, the strategic question becomes: Where can you invest human expertise that competitors aren't willing to match? The answer isn't in the content itself—it's in the strategy, curation, and connection of ideas that AI can't replicate.
Now that anyone can generate decent SEO articles with a few clicks, the question becomes what can you do that your competitors aren’t willing to do? Maybe it’s dusting off your camera and mics and filming “person on the street” style interviews asking passersby questions your ICPs (Ideal Customer Profiles) would find interesting. Maybe it’s investing in an original podcast series with industry leaders in your space. Whatever it is, one through-line remains: it’s hard. Great content IS hard to create—no matter how many AI tools you have on your desktop.
The New ‘Creative Director’ Role
The most successful content professionals I know have evolved from creators to creative directors. They're not writing as much as they used to, but they're thinking more strategically about what should be written and why.
This shift requires what I call "taste at scale"—the ability to articulate creative vision clearly enough to direct both AI tools and human collaborators. When I tell an AI "create this in the style of early Malcolm Gladwell" or "structure this like a Pixar story arc," I'm exercising judgment built through years of studying craft.
The content strategists who will thrive are those who can:
Identify patterns across successful content that AI tools can replicate
Recognize opportunities where human insight creates unbridgeable advantages
Design systems where AI handles execution while humans focus on strategy
From Assets to Ecosystems
The biggest shift I've made in the AI era is moving from managing content assets to architecting content ecosystems. Instead of asking "How can AI help me create more blog posts?", I now ask "How can AI help me create a self-improving content system?"
Here's what this looks like in practice—please excuse the nerdiness:
Pattern Recognition at Scale
I feed performance data into AI systems that identify correlations humans might miss—which topics perform best at what times, which formats drive the most engagement across different audience segments, which content pieces should be connected to maximize user journeys.
Content Relationship Mapping
AI helps me identify gaps in our content ecosystem—where we have high-performing pieces that aren't properly connected, where user behavior suggests content relationships that don't currently exist, where topics are performing well but lack supporting content.
Quality Amplification Systems
Rather than just using AI to generate content, I use it to analyze and improve content before publication. AI reviews drafts against our highest-performing pieces, suggesting structural improvements and identifying opportunities to strengthen key messages.
The result is a content system that learns and improves with each piece we publish, rather than a collection of individual assets that require constant manual optimization.
The Three Pillars of AI-Era Strategy
Through my work across education, media, and technology, I've identified three principles that separate successful AI-era content strategies from those stuck in productivity mode:
1. Identify Your Human Touch Advantage
Look for opportunities where competitors aren't willing to invest human effort despite proven effectiveness. YouTube is displacing blogs as the new “SEO battleground” precisely because fewer brands commit to high-quality video production than publish AI-generated articles.
2. Design for Multiplication, Not Production
Create frameworks where each piece of content strengthens the whole system. Build content relationships that compound value over time rather than optimizing individual pieces in isolation.
3. Know That Taste Is The New Talent
Develop the ability to articulate creative vision clearly enough to direct AI tools effectively. The most valuable skill isn't creation—it's curation and direction of AI-assisted creation.
The Coming Bifurcation
I believe we're heading toward a content bifurcation that will separate our industry into two distinct categories:
The Commodity Content Layer: AI-generated content that serves functional needs—basic product descriptions, routine social posts, templated email sequences. This will be fast, cheap, and largely indistinguishable between competitors.
The Strategic Content Layer: Human-directed content that creates genuine differentiation—thought leadership that changes minds, community-building content that creates loyalty, educational content that solves complex problems. This will be slower, more expensive, and exponentially more valuable.
The companies that win will excel in both layers, using AI for efficiency in commodity content while investing human expertise where differentiation matters most.
The Long View
We're still in the early innings of the AI content revolution. The tools we have today will seem primitive compared to what's coming. But the fundamental shift—from content creation to content strategy, from managing assets to architecting systems—represents a permanent change in how this discipline works.
The content strategists who adapt will find themselves with unprecedented leverage. AI doesn't threaten strategic thinking—it amplifies it. The question isn't whether AI will change content strategy, but whether content strategists will change fast enough to harness its potential.
Those who make this transition will discover something remarkable: AI doesn't make content strategy less human. It makes the human elements—judgment, creativity, strategic thinking—exponentially more valuable.
The future belongs to those who can dance with machines, not compete against them.
