- New Minneapolis Fed analysis finds AI will change how workers spend time, shifting wages up for some and down for others.
- Jobs made of tasks that are routine, rule-based, or predictable are most exposed to automation.
- Workers who augment their work with AI tools may capture productivity gains; others face downward wage pressure.
- Policymakers and employers must act now on training, job redesign, and safety nets to avoid widening inequality.
How much of your job could AI take over?
What the Minneapolis Fed analysis shows
The Federal Reserve Bank of Minneapolis has flagged a sweeping shift: AI isn’t just a productivity tool, it’s changing how workers allocate their time across tasks — and that reallocation matters for wages. The core argument is simple but profound: workers who spend more of their workday on tasks that AI can perform are more likely to see downward pressure on pay, while workers who use AI to amplify uniquely human tasks can see gains.
Which tasks are most exposed?
The analysis emphasizes task-level exposure rather than whole occupations. Tasks that are repetitive, rule-based, or involve predictable patterns (data entry, routine analysis, standardized reporting) are the likeliest to be automated. Conversely, tasks that require deep social intelligence, complex problem-solving, creativity, or physical dexterity in unpredictable environments remain harder to replicate.
This task-centric view explains why workers within the same occupation can experience very different outcomes: two employees with identical job titles can have divergent wage trajectories depending on how much of their day is spent on automatable tasks.
Wage and labor-market implications
Because AI changes the marginal productivity of specific tasks, the Minneapolis Fed finds uneven wage effects across the workforce. Workers whose tasks are automated may face job redesign, reduced hours on those tasks, or lower bargaining power — all of which can depress wages. At the same time, workers who adapt by shifting to tasks that complement AI — supervision, interpretation, empathetic interaction, creative oversight — can capture new value and see wage gains.
The net effect, if unaddressed, could be greater wage inequality and displacement concentrated among workers in certain industries and roles. The analysis signals that technological change will not be neutral: winners and losers will emerge depending on task composition and adaptability.
What workers, employers, and policymakers should do
- Workers: Audit your day. Identify tasks AI can replicate and prioritize skills that are complementary to AI: communication, complex problem solving, and domain-specific judgment. Seek training that shifts your task mix toward those areas.
- Employers: Redesign jobs to pair employees with AI tools, invest in reskilling, and rethink performance metrics so value from augmented tasks flows to workers.
- Policymakers: Fund retraining programs, strengthen transition supports, and encourage labor-market policies that reduce inequality risks tied to rapid automation.
The Minneapolis Fed’s task-focused framework reframes the debate: AI won’t uniformly “take jobs” so much as remap what work looks like. The policy and business response in the next few years will largely determine whether that remapping creates broader prosperity or deeper divides.
Image Referance: https://www.minneapolisfed.org/article/2026/how-much-of-your-job-will-ai-take-over