Marketing
ISCO-08 2431, 1221Marketing manager, Product marketing manager, Brand manager, Digital marketing specialist, CRM manager, Marketing director
Headcount need, in FTE
Target AI skills
level 1 to 4Job skills
Growing in value
- Customer insight and segmentation strategy
- Testing and measuring campaign performance
- Brand consistency across generated content
- Marketing data and consent management
Losing value
- Writing campaign copy variants
- Producing visuals for standard formats
- Building routine performance reports
- Manual audience list building
How the job will change
Marketing teams already use AI to write campaign copy, adapt visuals to every channel and language, segment customer bases and produce performance reports. Variants that once took an agency a week are now generated in an afternoon, and campaign platforms optimise budgets and targeting on their own. Execution roles centred on producing copy, visuals and reports are the most affected.
The work moves towards strategy and judgement: understanding customers, choosing what to say and to whom, protecting the brand when content is mass-produced, and proving what really drives sales. Marketers will need solid data literacy and the discipline to test before scaling. A good marketer tomorrow knows the customer better than the tools do and can tell a generic message from a distinctive one.
- 2026-2027
- Generated copy and visual variants become standard in campaigns.
- 2028-2030
- Personalisation at scale; agents run testing and budget allocation.
- 2031+
- Smaller teams focused on strategy, brand and customer insight.
When everyone produces content with the same tools, brands start to sound alike. Losing in-house creative and customer insight skills while cutting execution roles is a lasting risk. See the seniority outlook below.
What if you hired fewer juniors?
Your 2036 seniors are the juniors you hire today.
Advanced settings modified
2026 2036
The AI Cookbook 2026
albert's guide to cut through the noise around generative AI and turn it into workforce decisions.
- What AI actually changes in jobs and skills
- Why the junior pipeline matters more than most companies realise
- How to integrate AI into workforce planning

Run these scenarios on your actual workforce
AI Impact Diagnostic: 6 to 8 weeks, your data in albert, three costed scenarios and the projected seniority mix for each job family.
How the numbers are built
Every headcount figure combines four assumptions. Three come pre-filled from public research and job family defaults. The strategic ceiling is yours to set.
Seniority outlook
A flow model with three levels of experience in the profession. Promotion and exit rates are set so that today's mix stays stable when hiring does not change: any gap you see comes from the junior hiring cut alone.
Sources
- International Labour OrganizationGenerative AI and jobs: a refined global index of occupational exposure (2025)
- ILO datasetTask-level GenAI exposure scores by ISCO-08 occupation
- AnthropicAnthropic Economic Index (June 2026 release, April and May 2026 usage data)
- Stanford Digital Economy LabCanaries in the Coal Mine? Six facts about the recent employment effects of AI