AI Literacy Was Marketing's Top Skill in 2025. A Year Later It Is Just the Cost of Entry.

On January 22, 2026, Indeed’s Hiring Lab published a labor-market update with a number most marketers skipped past. Over 2025, the share of US marketing job postings that mention AI climbed from 8.4% to 14.9%. In twelve months, the odds that a marketing job ad asked for AI nearly doubled.

Rewind one year for the other half. In LinkedIn’s 2025 ranking of the fastest-growing marketing skills, AI literacy sat at number one. In the 2026 ranking, published in November, it slipped to number two, behind performance analysis. LinkedIn’s own read was blunt: AI literacy had become less of a differentiator and more of a baseline expectation.

The marketing job description is being rewritten while marketers are still doing the job.

The skills that got someone hired in 2022 are quietly moving into the column labeled automated. Lightcast, a labor-market analytics firm, read more than 1.3 billion job postings for its July 2025 report and found that ads asking for AI skills advertise 28% higher salaries, close to $18,000 more a year, than comparable roles that do not. Cole Napper, the firm’s VP of research and insights, framed the stakes for employers:

“Companies that continue treating AI as a niche technical skill will find themselves competing for talent with organizations that have embedded AI literacy across their entire workforce.”

Marketing is not a bystander in that shift. Lightcast found that 51% of postings demanding AI skills now sit outside IT and computer science, and marketing and public relations ranked second among all sectors for AI-skill demand, behind only tech itself.

The split inside the function is visible in the ads. LinkedIn’s 2026 marketing list reads like a map of what survives: performance analysis at the top, then AI literacy, then performance marketing, go-to-market strategy, and operational efficiency. What is absent tells the rest. Lightcast estimates roughly 10% of all posted jobs are exposed to automated writing tools, and its analysts note that marketing specialists now need more training in picking topics and writing prompts than in producing the copy itself.

The premium is landing on judgment, not output. Christina Inge, founder of the AI marketing consultancy Thoughtlight, told Fortune that the workers pulling ahead are the ones who pair AI fluency with a human read on the result:

“That combination of human judgment and AI fluency is hard to find and well worth the extra pay.”

PwC’s 2025 Global AI Jobs Barometer, built on nearly a billion job ads, put the top of that premium at 56%, more than double the 25% it measured in 2023.

The mechanism is plain once the postings are read as a budget. A first draft of copy, a stock layout, a routine campaign report: each is now something a mid-level marketer produces in an afternoon with a model, so the ad stops paying for the person who used to produce it. What it pays for instead is the part the model cannot close on its own, which is deciding what to make, judging whether the output is any good, and tying it to a number. Indeed’s AI at Work report, which scored 2,884 skills across 53.5 million US postings, found 26% of jobs could be highly changed by generative AI and another 54% moderately changed, while fewer than 1% of work skills can currently be done with no human involved. The tasks get automated. The accountability does not.

For anyone whose resume is a list of things they can produce, the read is uncomfortable. Production is the exposed layer, and the entry-level rungs built on it are thinning. The World Economic Forum’s 2025 Future of Jobs report already lists graphic designers among the roles in decline as AI reshapes demand, and 41% of the employers it surveyed said they expect to cut headcount where AI can automate the work. It is the same reallocation showing up as quiet team shrinkage across B2B that this publication’s jobs coverage keeps returning to. The change shows up in the job ad before it shows up in the layoff.

Three moves follow for anyone whose title has marketing in it. Learn the tools well enough that using them is assumed, because the postings already assume it. Build the skill the ads are paying up for, which is reading a model’s output with judgment and connecting it to a business number, the reason performance analysis, not production, now tops the list. And treat every task you can hand off to a model in full as a task that has left your job description. On the evidence of the postings, it already has.