A poll of 4,000 workers in the US and the UK finds that the highest-earning and most experienced workers are adopting AI in their jobs far faster than others
Context & Ripple Effects
Workplace AI use had already been spreading faster than formal company guidance: related surveys show broader employee use rising between 2023 and 2025. This poll adds distributional detail, indicating that adoption is concentrated among workers with more experience and higher earnings rather than being evenly shared.
That matters alongside evidence that heavy AI investment is associated with faster hiring chiefly among tech companies and startups, while leaders in regulated or accuracy-sensitive work stress trust and accountability. The issue is not simply whether AI enters work, but who can turn it into an advantage under workable governance.
First-order effects
- Higher-earning, more experienced workers are likely to capture the earliest productivity and workflow benefits from workplace AI, widening the practical capability gap within organizations.
- Employers face an immediate adoption-management problem: informal use may be strongest among senior staff while less experienced workers receive less exposure, training, or confidence to use the tools.
Second-order effects
- Companies seeking broad productivity gains will be pushed to pair access with role-specific training and clear usage rules; otherwise AI benefits may remain concentrated in already advantaged teams.
- The divide may reinforce demand for AI tools that fit established professional workflows and can meet trust, accountability, and compliance expectations, rather than tools that merely make capabilities available.
Third-order effects
- If uneven adoption persists, AI could become a mechanism that amplifies existing experience and pay differences before it diffuses across the workforce, complicating claims that it delivers broadly shared productivity gains.
- Workplace AI competition is likely to shift from raw tool availability toward organizational distribution: training, governance, and trusted integration may determine whether firms broaden gains or concentrate them.
The trend: This is a data point in the shift from broad consumer-style AI availability to uneven, institutionally governed adoption inside workplaces.