AI ad spend is soaring even as audiences grow weary of look‑alike content, according to early findings from a forthcoming Billion Dollar Boy report summarized by eMarketer. Marketers see AI as a growth engine, but consumers are increasingly tuning out generic, unlabeled output—signaling a pivotal moment for brands to rethink how they deploy machine-made media.
What marketers are doing
– Nearly 8 in 10 marketers increased their AI investment over the past year.
– In the next 12 months, 77 percent plan to shift more budget from creator-led campaigns to AI-driven initiatives.
– Close to three-quarters view AI as a driver of ad spend growth by 2026, not merely a way to cut costs.
– Still, 81 percent say AI improves cost control, and 73 percent claim AI-assisted content outperforms human-only work.
What audiences are feeling
– Consumer enthusiasm has slid sharply: about 60 percent were excited about AI content in 2023, but only 26 percent feel that way now.
– The main turnoffs are “AI slop”—uninspired, repetitive, and unlabeled content that erodes authenticity and trust.
– Even so, 38 percent of consumers say AI strategies can improve quality, and 41 percent credit AI with boosting diversity and representation.
– Younger audiences are more receptive: 40 percent of those aged 25–34 prefer AI-driven content.
Why the fatigue is rising
Platforms are accelerating output with tools like YouTube’s edit with AI, enabling creators to publish faster than ever. The downside is a flood of low-effort, samey videos that make feeds feel spammy. Some viewers are even using auto-generated “educational” clips—such as historical explainers—as sleep aids, inadvertently absorbing inaccuracies along the way. When volume outpaces craftsmanship and clear labeling, trust suffers.
How brands can win with AI without losing the audience
– Lead with human creativity, augment with AI: Use AI to brainstorm, version, and optimize—not to replace original ideas or storytelling.
– Set a higher bar for quality: Establish editorial standards for accuracy, narrative flow, and visual polish. Don’t publish anything that feels templated or thin.
– Label AI clearly: Transparent disclosures build trust and reduce backlash.
– Personalize with purpose: Apply AI to audience insights and segmentation so content feels relevant rather than mass-produced.
– Diversify formats and voices: Combine AI tools with a range of creators to preserve authenticity while benefiting from efficiency.
– Measure beyond cost: Track attention, completion rates, saves, shares, and sentiment to catch “slop fatigue” early.
– Iterate quickly, not blindly: A/B test creative, frequency, and messaging to find the balance between helpful automation and human touch.
The bottom line
The honeymoon phase for AI-generated content is ending, but opportunity remains for marketers who use AI as an amplifier rather than a replacement. Pair machine-scale production with human judgment, label it, keep standards high, and tailor content to audience segments—especially younger cohorts that show greater openness to AI. Done right, AI can boost quality, representation, and performance without burning out the very people you’re trying to reach.
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