Most AI research studies large enterprises. We focused on the mid-market. We surveyed 200 senior brand marketers at US companies between $5M and $249M in revenue, all moving AI from experiment into production. Adoption, it turns out, is largely handled. The harder problem is making AI hold up as you scale it.
Three findings
The most advanced teams break first. Scaling AI surfaces operational strain rather than relieving it. The teams with AI most embedded across their operation report the highest rate of breakage, not the lowest.
Measurement is the weakest link. Only 41% can cleanly measure which AI-produced variants are working. Most teams are scaling output they cannot yet read, and performance measurement is the function most likely to break first when volume doubles.
The constraint is people, not tools. Talent and competency is the leading barrier, ahead of tools, budget, and governance, and the demand for AI fluency is climbing fast.
Explore it yourselfWe built the findings as an interactive research tool rather than a static report. Filter the data by revenue, maturity, and industry, see where your peers are breaking, and get the full playbook of moves behind a single registration.
Wave 1 of an ongoing series. 200 quality-screened respondents, fielded May 20 to May 30, 2026 via the Cint Exchange panel. Margin of error plus or minus 6.9% at 95% confidence. Want the cut for your industry or a briefing for your team? Email us at info@coastalviewadvisory.com.