Ad Age has published a report asking a blunt question of chief marketing officers: where is AI actually working, and where is it still falling short? The publication's answer, based on its reporting on CMO sentiment, is that success exists — but it sits in narrow pockets, while broad gaps remain between what marketing leaders want from AI and what they can currently deliver.

That framing matters because marketing remains one of the most heavily hyped categories in enterprise AI. Vendors promise automated campaigns, generated creative and always-on personalization. CMOs, according to the Ad Age piece, are finding real wins in some of those areas. The report does not claim the wins are universal.

Where are CMOs finding AI success?

The Ad Age reporting indicates that marketing leaders point to gains in the routine, high-volume work that dominates marketing operations: content production, campaign iteration and the analytical tasks that previously consumed staff hours.

This tracks with what trade coverage has shown across the industry. AI tools perform best where the task is repetitive, the output is checkable and the cost of a mistake is low. Ad copy drafts, subject-line variants, audience segmentation queries — these are the jobs CMOs most often cite as proven ground for the technology.

Success, in other words, appears concentrated where AI assists existing workflows rather than replacing them. That is a more modest claim than the one vendors make, and the Ad Age report reflects that restraint.

What gaps remain?

The second half of the report's finding is the one marketing leaders should read twice. Gaps remain — and the title of the piece puts them on equal footing with the successes, which is itself a signal.

What the headline does not specify is which gaps. The piece does not, in the summary now circulating, name the exact functions where CMOs say AI underperforms, quantify how many leaders were surveyed, or attach dollar figures to either the savings or the shortfalls. Readers looking for a measured adoption rate or a budget breakdown will not find one in the headline reporting.

That absence is consistent with the pattern this publication has tracked before. When AI success stories come without numbers attached, the gaps usually involve some combination of the following:

• Data quality and integration problems inside legacy marketing stacks
• Difficulty measuring whether AI-assisted work outperforms the human baseline
• Talent shortfalls — teams that can operate the tools but not audit them
• Brand-safety and accuracy risk in generated content

Those are industry-standard failure points. The Ad Age report points at the gap; it does not itemize it in the material now available.

Why the honest split matters

A report that says "success and gaps" in the same breath does more service to operators than another round of triumphal case studies. Marketing AI has spent two years in the pilot phase across much of the industry, and CMOs face direct pressure from boards to show returns. A finding that credits the wins while naming the shortfalls gives buyers a more usable picture.

The caveat writes itself: success reported by CMOs is success as CMOs define it. Without published methodology in the available summary — sample size, sectors, respondent roles — the reader cannot tell whether these leaders speak for the Fortune 500, the mid-market, or a self-selected group already invested in AI tools.

What buyers should take from it

For marketing teams weighing further AI spending, the report supports a simple discipline. Claim the wins in high-volume content and analysis, where the evidence is strongest. Hold vendors to measured outcomes before expanding into harder territory. And treat any AI pitch that cannot name its own limitations with the skepticism it has earned.

The gaps, not the successes, are where the next year of marketing budgets will be decided.