Quartz 5

FS

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Bid - FS

Macro-level forces shaping talent landscape​

Productivity and role redesign

AI-exposed sectors are seeing sharp productivity gains In PwC’s Global AI Jobs Barometer measured in 2024

  • sectors most exposed to AI experienced almost 5x higher labor productivity growth
  • postings for jobs requiring AI skills grew 3.5x faster than all jobs
  • AI skills carry wage premiums up to 25% in some markets.
  • The 2025 update finds revenue per worker growing 3x faster in AI-exposed industries

References

Exposure is broad, with augmentation more common than full automation

  • ILO’s global analysis indicates the dominant effect of generative AI is to augment rather than automate jobs, with greatest impacts in high and upper-middle income countries due to the prevalence of clerical roles
  • effects are highly gendered because clerical work is a key source of female employment
  • The ILO’s 2025 index estimates one in four workers globally are in occupations with some generative AI exposure
  • 3.3% of global employment is in the highest exposure category, with exposure higher among women and in high-income economies (34% overall exposure in HICs vs 11% in LICs)
  • Conclusion: Job transformation is more likely than job elimination
  • Brookings finds >30% of workers could see at least 50% of their tasks disrupted, with exposure concentrated in “cognitive” and nonroutine work (e.g., admin/clerical, business/finance, programming, legal), and with notable implications for women due to occupational mix [21].

References

Hiring and wage dynamics reflect a premium for AI capability

  • AI job postings are rising fast—Brookings/Lightcast show AI-related postings growing ~29% annually over 15 years and >100% in the last year, with AI skill mentions linked to ~28% higher pay in postings; demand is spreading beyond tech hubs to other regions and sectors [22].
  • PwC and Microsoft/LinkedIn show strong wage premiums and career advantages for AI-skilled workers, with early-career talent expected to take on greater responsibilities in AI-enabled organizations [20][25].

Inequality and distributional impacts need attention

  • UN/ILO warn that tech progress, automation and AI can push down labor’s share of income without policy action; productivity has outpaced labor income growth globally in recent decades, and breakthroughs in generative AI could add further downward pressure absent interventions (e.g., social protection, minimum wages, collective bargaining) [11].
  • Adaptive capacity matters: Brookings identifies US pockets of high exposure with low ability to transition (6.1 million workers, largely in clerical/admin roles and predominantly women), suggesting targeted support for vulnerable groups and places [23].

Regional and sectoral differences

  • Knowledge-intensive sectors (finance, ICT, professional services) show the fastest AI uptake and skills change, but all industries are increasing AI usage—including mining and agriculture [18][20].
  • High-income countries face higher exposure overall; low- and middle-income countries face different constraints and opportunities, including informal sector considerations highlighted in OECD/GPAI work [8][12].

Implications for employers, educators, and policymakers

  • Employers: Make AI capability a core competency; redesign workflows; invest in targeted training (prompting, data literacy, critical thinking); measure ROI beyond task-time savings (quality, speed-to-value, revenue per employee) [25][18][20].
  • Educators/training providers: Emphasize transversal skills (management, collaboration, creativity, digital literacy) alongside AI tool proficiency; update curricula faster in AI-exposed fields [7][8][25].
  • Policymakers: Pair innovation with inclusion—expand social protection and active labor market policies; support reskilling for clerical/admin roles most exposed; strengthen worker voice and responsible AI deployment; monitor wage and income-share dynamics [10][11][5].

References

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