The Noisiest Economy in History
Part 2 of 3: Why the attention economy just entered hyper-inflation and what it means for anyone spending money to reach a human.
My last issue AGI to AGI clearly hit a nerve & humour :) Great comments, sharp questions, a few friendly challenges. I’ll cover those in a dedicated summary post. Thank you this is exactly the conversation our industry needs. Keep stress-testing.
Now, Part 2.
Part 1 established the pattern: every tech wave web, mobile, AI monetizes through advertising. AGI (Artificial General Intelligence) became AGI (Advertising Generated Income). The $650 billion in AI capex isn’t funding the singularity. It’s funding ad infrastructure (kinda).
Part 1 didn’t address what happens when all that infrastructure comes online at once.
Every marketer & business exec can feel it: you spend more, you reach more, and somehow you get less.
The competition has changed. AI-generated content that looks exactly like yours. AI agents that bid on the same audiences while you sleep. And increasingly AI systems on the other end that screen out your messages before a human ever sees them.
That’s not a bad quarter. That’s a new economic condition.
The median SaaS company now spends $2.00 to acquire $1 of new ARR and the worst performers hit $2.82. E-commerce customer acquisition costs have risen roughly 40% since 2023. And it’s about to get worse because former SaaS companies whose software margins collapsed are pivoting to media models, entering your ad auction alongside every AI-powered competitor the market can produce.
The Attention Inflation Crisis
Attention inflation (n.): When the supply of content competing for human attention explodes but human attention stays finite. More spend to reach the same person. More noise to get the same signal. The cost of being noticed rises without appearing on any invoice.
AI made content nearly free to produce. When anyone can generate a blog post, a video ad, or an email sequence in minutes, everyone does. Supply explodes. Meanwhile, SaaS margin compression is pushing more companies toward attention-based monetization entering your ad auction, competing for the same eyeballs. More bidders. Same pool of humans.
State Street’s research team captured the paradox: over $300 billion is spent annually on online advertising, AI is reducing production costs but CPM is expected to rise, because the number of advertisers is growing faster than available human attention. Textbook inflation.
The resource isn’t growing it’s fragmenting. Facebook and Instagram capture over 20% of US digital ad revenue but only about 7% of adults’ daily media time. Americans spend 6.3 hours per day on phones up a full hour since 2023 and Activate Consulting projects 13 hours and 5 minutes daily with media and tech by 2026, more time than Americans spend working. Yet 55% of social users multitask while scrolling, 49% while watching video. CTV passed linear TV in 2025, but consumers second-screen through most of it. Attention is migrating to niche communities Reddit growing +3.7% in time spent while TikTok drops 6.9%. The humans aren’t vanishing. They’re scattering across more surfaces with less focus.
Want to feel the inflation? Target a CIO on LinkedIn:
LinkedIn B2B (US), directional benchmarks: CPM $50–$100 · C-suite CPC $5–$20 · Enterprise CPL $150–$200+ · Rising 3–8% YoY
One fintech marketer described it as “a knife fight in a phone booth.” Every vendor targeting the same 50,000 executives, and AI ad tools now let every mid-market competitor bid alongside enterprise players.
This isn’t new. Sinofsky observes every platform transition produced vastly more content, not less. The content flood isn’t a bug. It’s the feature. And it’s permanent.
The Trust Collapse
When everything looks the same, trust becomes the only filter.
AI content is converging toward a median Taryn Crouthers told Marketing Dive it’s “merging to look very, very similar.” UGC now drives 4× higher CTR than polished brand creative not because it’s better produced, but because it’s human. By some estimates, a majority of online content is now AI-generated. Proof of humanity became a purchasing signal. Except influencers monetize that trust and audiences increasingly know it. The premium on genuinely earned voice keeps rising.
The irony: AI captures attention while destroying the trust required to convert it. Convenience outweighs concern, but trust erodes faster than convenience builds. And now AI inbox agents pre-screen AI-generated emails, AI recommendation systems consume AI-generated content bots talking to bots while brands pay real money for the privilege. The dead-internet dynamic is no longer fringe it’s showing up in every funnel.
And it’s not just content trust that’s broken. It’s data trust.
The Privacy Paradox: Trust’s Unfinished Business
88% of Gen Z willingly share data for better experiences, yet 81% are concerned about how it’s used and only 14% trust platforms to handle it responsibly. The privacy paradox: consumers trade data for convenience while distrusting the companies collecting it.
The brands that win aren’t collecting the most data they’re collecting the right data with explicit consent. Zero-party data preferences, intentions, feedback customers proactively share is the only privacy-compliant path to personalization at scale. 99% of marketing executives say privacy concerns have impacted their personalization plans. The fix isn’t less personalization it’s making personalization something people actually opt into.
The consumer side of this paradox is clear. The infrastructure side is where it breaks down. Retail media networks have a structural advantage first-party purchase data, not inferred behavior. 66% of organizations use data clean rooms, 70% plan to increase RMN budgets. But TrustArc found retail ranks 12th of 17 sectors in privacy maturity (54% vs 61% global average), and only 39% say privacy permeates everyday decisions — while citing “earning brand trust” as their #1 privacy benefit. The gap between aspiration and execution is the opportunity.
The privacy comeback won’t be a regulation story. It’ll be a competitive advantage story. Brands that treat zero-party data as a trust product will own loyalty. Everyone else will keep buying attention they can’t convert.
Attention Without Outcomes Is Just Spend
The IAB’s 2026 Outlook projects 9.5% ad spend growth. Social up 14.6%, CTV up 13.8%, commerce media up 12.1%. Cross-platform measurement is now the #1 advertiser priority 72%, up from 64%. But most orgs still can’t answer the only question that matters:
“We spent $500K on this audience last quarter what did we learn, and what changed this quarter as a result?”
That’s not a data gap. That’s a decision gap. If you’re the CIO or data leader, this is your problem now. Every unconnected surface is decision debt. Every campaign without a feedback loop is an experiment you can never learn from.
Agents Without Direction = Faster Noise
The paradox of agentic AI adoption: two-thirds of advertisers are deploying agentic AI for ad buying, and Gartner predicts 40% of current agentic AI projects will be canceled by 2027. The gap: only about 130 of thousands of vendors offer genuine capabilities. The rest is “agent washing“ the industrial-scale production of agent slop that clutters the funnel without closing the loop.
The industry is automating execution while ignoring decisions. An agent that can bid on 50 surfaces simultaneously is only valuable if something can answer “should we be on those surfaces, for that audience, with that message, and what did we learn last time?” Without that closed loop, agents don’t reduce noise. They multiply it. At machine speed. With your budget.
Five Truths for the Noisiest Economy in History
1. The noise is structural, not cyclical. The bidders in the attention auction will keep growing. This is the new baseline.
2. Trust is the new scarcity. The brands that win won’t be the loudest. They’ll be the most precise.
3. Privacy is the trust product. Zero-party data isn’t a compliance requirement. It’s a competitive moat.
4. Attention without learning is waste. The question isn’t how much attention you can buy. It’s whether that learning compounds into better decisions.
5. Follow the human, not the channel. 72% of CMOs say audience-centric planning is their top priority — but most still plan by channel. The real question isn’t “what’s our TikTok strategy?” It’s: who is our audience, why do they care, where do they move, and what did we learn last time? That’s audience portability carrying insight about a human across every surface they touch. Without it, every channel resets to zero. With it, every surface compounds.
Coming Up in Part 3: “Compound Decisions, Not Campaigns”
The brands that treat every interaction as a chance to learn about a human will compound their “audience context” advantage while everyone else resets with every campaign. What does a decision system look like when the unit of strategy is the audience, not the surface and agents execute smarter because they know what worked last time?
Part 3 will lay it out.
Thanks for reading Data to Decision Activation.
Author’s note: An LLM helped with research, citations, and light proofreading without changing content. All ideas, arguments, voice, and em dashes are mine. :)