Did You Know?
Forbes' April Edition published “21 Job Titles That Will Disappear by 2030.” The article groups vulnerable roles by the tasks that AI, robotics, and process automation are already taking over, such as data entry, routine cash handling, telemarketing, low-level tech support, and more.
Many of these titles are focused on “transactional” work (cashiers, bank tellers, payroll clerks), simple data manipulation (data-entry keyers, proof/copy typists), or narrow pattern-matching (telemarketers, fast-food order takers).
Why the urgency? MIT’s David Autor suggests that specialized AI reduces the cost of prediction and language tasks, shifting value toward judgment, creativity, and social intelligence. John Kotter’s research on change failure warns that complacency can be deadly when disruptive forces are building.
So What?
- Boards are now incorporating “technology half-life” into P&Ls. If 30-50% of current clerical or transactional staff can be automated within three budget cycles, CFOs can no longer see reskilling as optional "CAPEX" and believe me, most do.
- Porter’s Cost-Leadership idea disappears when every competitor acquires the same bot. Competitive advantage will shift toward companies that emphasize unique human skills like empathy, systems thinking, cross-domain creativity; rather than just cutting unit labor costs.
- Data-mining roles don’t disappear, they evolve. The Introduction to Data Mining reminds us that when rote ETL work declines, demand rises for “model translators,” ML-ops ethicists, and domain-fluent prompt engineers.
- Change fatigue is real. Reskilling programs stall without clear reinforcement of Desire, Knowledge, and Ability culture.
Now What?
- Map exposure to match pathways: Use an AI-enhanced skills graph (see MIT M2 Machine Learning Casebook) to connect each “at-risk” role to at least two growth roles requiring no more than 24 months of upskilling.
- Transform managers into Supermind architects: Based on Malone’s Superminds research: combine small-batch human judgment with AI prediction loops to increase team IQ. Train leaders to design these hybrid workflows.
- Implement micro-pilots with “short-term wins.": Select one declining role (e.g., AP clerk) and one growth opportunity role (e.g., cash-flow analyst). Offer curated courses plus shadowing; track and publish win metrics within 90 days.
- Embed change institutionally: Tie role evolution KPIs to promotion criteria; celebrate internal talent moves in monthly town-halls; embed peer-mentoring into OKRs.
- Adopt Flow-based funding: Release reskilling funds in two-week “learning sprints” instead of annual L&D blocks. Measure ROI via skill-utilisation delta.
Catalyst Leadership Questions
| Question | First-Probe Prompt |
|---|---|
| Which roles in our 2025 org chart map to Forbes’ “21”? | “Show me the FTE count and payroll weight per vulnerable title.” |
| What % of our margin depends on tasks AI can now do at < $1/hr? | “Run a Porter cost-driver sensitivity with 10 %–50 % automation.” |
| Where can we redeploy these humans to amplify differentiation? | “List customer-journey pain points requiring empathy & creativity.” |
| How will we measure skill-shift velocity quarter-by-quarter? | “Define a dashboard of retained, reskilled, replaced ratios.” |
| What change-management muscle are we under-investing in? | “Rate our ADKAR scores; where is Desire or Reinforcement weakest?” |
We can’t stop the calendar at 2024, and we can’t spreadsheet our way out of obsolescence. The good news? Every redundant task is an invitation to redirect human ingenuity toward work that machines still envy; context, compassion, creation. Ignore that call and you’re Blockbuster Video in a Netflix world; heed it and you’re Airbnb writing the next chapter of hospitality.