AI Advantage Assessment

AI for every day marketing analytics is not yet a popular use cases for marketers. That may be the biggest AI adoption opportunity for leaders to drive actual RESULTS from their department (and in the career perception of individual marketers).

Look at how much more popular AI as a tool for individual contributor tasks like writing  and summarizing are than for analysis.  

Analysis isn’t in every marketer’s job description, but the size of the gap is still strange. 40% of respondents said they were using AI for First Draft Content All the time;  literally no one said they were using AI for Pipeline Analysis or Predictive Analytics that way. There is a 4X difference in marketers using AI for first drafts of content v. basic analysis.

	Increasingly + All the time	All the time
1st draft – marketing content	80%	39%
1st draft – analysis & visualization	41%	9%

AI for analytics should be more popular. Marketing has been shifting that way for a long time (e.g. analytics in marketing education, growing marketing use cases where quantitative skills are needed). And AI’s quantitative strength (ability search broadly, easy data upload, unlimited calculations) is clear.

Why this matters for marketing leaders

Analytics adoption is about leadership visibility and credibility.

• For departments: AI can uncover copy that truly converts, identify weak-performing segments, and surface programs that aren’t delivering.
• For individuals: Those who can interpret data with AI support become the most valuable voices in the room, connecting qualitative concepts with quantifiable outcomes.

Suggestions

• Add “AI for analytics” to your 2026 enablement plan. Treat it as a separate competency from writing use cases.
• Pilot a quantitative use case in every team. Start small — a pipeline analysis, audience segmentation, or creative performance review using AI tools.
• Normalize comfort with data. Encourage your team to “ask AI the question they’d normally send to an analyst.”

Leaders who make this shift now will position their departments as leaders.

Next up: I’ll break down how AI analytics adoption differs across marketing disciplines — from product marketing to demand gen, advertising, and PR.

Sources – https://www.linkedin.com/in/dr-justina-setkute/; https://www.linkedin.com/in/simonekurtzke/; https://aiadvantageassessment.com/