Every wave of technology arrives with a warning label about vanishing jobs. A new essay on MarTech argues that history tells a more useful story: tools rarely delete human expertise outright, they move it somewhere else. The example it leans on is one every martech practitioner has used — the WYSIWYG editor.
The WYSIWYG lesson
WYSIWYG (“what you see is what you get”) editors date back to at least 1974 and became standard inside content management systems. They made publishing accessible to non-coders. What they did not do was make coders redundant. Website teams still needed people fluent in HTML, CSS, PHP and JavaScript to handle everything the visual editor could not.
MarTech pairs that with a cultural footnote: MTV launched in 1981 with The Buggles’ “Video Killed the Radio Star.” Roughly 45 years later, radio is still around and audio has expanded further through podcasting and audiobooks. The format shifted; the demand did not disappear.
From writer to editor
The same pattern is playing out with vibe coding, where natural-language prompts generate working code. Programmers are still required — but increasingly as editors of machine output rather than authors of every line. That is an uncomfortable reframing for a profession long associated with security, pay and mobility.
The piece cites Varsha Banal in The Guardian, who described software engineers as “frustrated, anxious, and trying to adapt to a startling new reality in which the value of their skills is unclear” — with responses ranging from doubling down on fundamentals to considering leaving the industry entirely.
Redeployment beats redundancy
The most instructive examples for marketers are commercial, not philosophical. IKEA, as reported by Inc. columnist Stephanie Davis, studied what customers were asking for that bots could not deliver and found unmet demand for interior design help. It retrained 8,500 customer support agents into premium design advisers. That channel generated $1.7 billion in 2024 — about 3.3% of total revenue — and is projected to hit 10% by 2028.
Sangeet Paul Choudary’s book “Reshuffle” makes a similar point about Best Buy, which trains in-store associates to guide shoppers through complex electronics purchases, pulling people back into physical stores. Both companies let automation absorb the repetitive work and pushed humans up the value chain. Gartner, meanwhile, has found that many companies which carried out AI-driven layoffs later regretted them.
Why it matters for martech teams
Marketing technology roles are not exempt. AI will automate some tasks, reshape others and create categories that did not exist. The practical question for Indian and global marketers alike is where your judgment is irreplaceable — briefing quality, brand safety, measurement design, customer nuance — and where you should be handing off grunt work.
- Build the habit: pick a few small, recurring tasks and run them through employer-approved AI tools until using them becomes reflexive.
- Promote your wins: self-promotion isn’t selfish; leadership needs visible proof of the value you add post-automation.
- Solve a real problem: Snowbasin marketing director Michael Rueckert noticed AI chatbots weren’t recommending the Utah ski resort, used Claude to fix it, then launched Centium to offer AEO and GEO services to other brands.
- Keep the fundamentals: LLMs still hallucinate, and platforms themselves warn users to verify output. Someone has to know enough to catch the errors.
There is also a structural response building. Raise U.S., a nonpartisan group led by former U.S. Commerce Secretary Gina Raimondo and former Indiana Governor Eric Holcomb, is working to avoid repeating the social costs of late-20th-century manufacturing offshoring. What Will We, founded by software engineer Kaitlin Cort, supports displaced knowledge workers with a job board, layoff support, shared learning tools and a resource library, with a basic income pilot and mutual aid fund in the works as of mid-July 2026.
The takeaway for marketers: the fastest way to stay employable is to find the work AI cannot finish, and get very good at it.
Source: MarTech
