One in four South Carolina managers say they'd replace workers with AI
AI won't replace your team on its own. Managers will. A new survey of 3,005 U.S. managers from Trio.dev shows how leaders are weighing cost, pressure, and ethics when considering AI in headcount decisions.
The headline: In South Carolina, 24% of managers say they'd replace staff with AI without guilt, above the 21% national average.
The numbers that matter
- Managers with zero guilt replacing staff with AI (national): 21%
- Highest "no guilt" states: Maine 67%, California 53%, Colorado 47%, Hawaii 43%, Maryland 38%
- Lowest: Idaho 8%
- South Carolina: 24%
What pushes managers to pull the trigger
- Pressure from executives/shareholders: 36%
- Productivity gains: 31%
- Cost savings: 27%
- Industry trends/competitors: 6%
Translation: boardroom pressure beats tech fascination. The business case is often made top-down, not tool-first.
Where managers draw the ethical line
- Most replaceable (ethically): coding/design (~1 in 3)
- Customer service: 25%
- Clerical: 16%
- Creative roles: 15%
- Least replaceable: sales at 11%
Even "human" work isn't immune. Sales stays insulated, likely due to relationships, context, and negotiation.
The money threshold
- 15% of managers would replace an employee for a 5% savings
- 50% say they'd switch only at a 50% savings
Set your own floor now, or you'll inherit someone else's. Document the ROI trigger that justifies automation in your unit.
AI vs. offshoring: what feels "acceptable"
- More unease with replacing via AI: 57%
- Less unease with replacing via overseas employees: 43%
Leaders feel AI cuts deeper than outsourcing, even if the end result for the role is similar.
The transparency gap
- 46% would inform staff ahead of AI replacements
- 54% would wait until change is unavoidable
If you don't control the message early, fear controls the narrative. Silence erodes trust and performance long before any cut.
What this means for your decisions
- Define a clear ROI policy: Set written thresholds for AI-driven role changes (e.g., cost, quality, speed). Apply consistently across teams.
- Run "human-in-the-loop" pilots: Start with process steps, not whole roles. Measure error rates, cycle time, and customer impact.
- Audit for legal and bias risk: Review ADA, Title VII, and EEOC guidance on automated decision tools. See the EEOC's resources here.
- Create a transparency standard: Decide what you'll share, when, and how. Offer timelines, affected workflows, and support options.
- Build a redeploy/upskill path: Convert savings into capability. Fund training for AI-assisted workflows and move people into higher-leverage work.
- Set a replacement review board: Require cross-functional signoff (finance, HR, legal, line owner) before any role elimination tied to AI.
Practical reskilling for managers and teams
If you're upgrading roles instead of cutting them, give people a plan. Map key workflows, pick the right tools, and train for prompt quality, oversight, and KPIs.
Useful starting points: curated AI learning paths by job function here and an applied certification for AI automation here.
State hotspots at a glance
Willingness to replace workers with AI is highest in Maine (67%), California (53%), and Colorado (47%). South Carolina sits at 24%, while Idaho is lowest at 8%.
For a full state-by-state view, see the online infographic referenced in the study.
Bottom line for managers
AI replacement isn't a tech story. It's a leadership decision under budget pressure.
Decide your ROI floor, protect trust with clear communication, and invest the gains into skill and process quality. That's how you grow throughput without burning culture.
Source: Survey of 3,005 U.S. managers provided by Trio.dev.
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