A deepening skills gap between early AI adopters and the rest of the workforce is creating significant competitive advantages for those who have mastered AI tools, according to Anthropic's fifth economic impact report, presented at the Axios AI Summit in Washington, D.C. on March 25, 2026.
The research finds that while widespread AI-driven job losses have not yet materialized, the conditions for rapid displacement are building - and the window for workers to adapt is narrowing.
The Widening Gap
The core finding is that the skills gap between long-time AI users and new entrants is not closing. It is widening.
Workers who began using AI tools like Claude early have developed sophisticated workflows, learned to craft effective prompts, and integrated AI into complex professional tasks. New users, by contrast, tend to use AI for simple, superficial applications - if they use it at all.
This creates a compounding advantage. Experienced AI users:
- Complete tasks faster with AI-augmented workflows
- Produce higher-quality output by using AI for research, analysis, and refinement
- Take on more complex work that was previously beyond their capacity
- Automate routine elements of their jobs, freeing time for higher-value activities
The result is a two-tier workforce emerging within organizations: AI-proficient workers who are becoming dramatically more productive, and AI-novice workers whose relative value is declining.
The Capability-Usage Gap
Peter McCrory, a researcher at Anthropic, highlighted a critical paradox: AI models can theoretically perform the majority of tasks in many white-collar occupations, but most users are only scratching the surface of those capabilities.
"While these models can theoretically do almost anything a computer can do, in practice people and companies are bringing only a small subset of tasks into these systems," McCrory noted.
This gap serves as both protection and warning:
Protection: The low adoption rate means AI is not yet displacing workers at the scale its capabilities would suggest. Most jobs that AI could theoretically perform are still being done by humans because organizations have not implemented the necessary integrations, workflows, and change management.
Warning: Once organizations solve the adoption barriers, displacement could accelerate rapidly. McCrory warned that "displacement effects could materialize very quickly" - suggesting that the current buffer period may be shorter than most workers assume.
Who Are the Power Users?
Based on the report's findings and broader industry data, AI power users share several characteristics:
| Characteristic | Power Users | Average Users |
|---|---|---|
| Usage frequency | Daily, integrated into workflows | Occasional, task-specific |
| Prompt sophistication | Complex, multi-step instructions | Simple, single queries |
| Tool integration | Connected to existing systems | Standalone use only |
| Task complexity | Strategic analysis, content creation, coding | Basic search, simple writing |
| Productivity gain | 40-60% estimated | 10-15% estimated |
The productivity differential between power users and average users is significant enough to reshape career trajectories and hiring decisions. Employers increasingly value AI proficiency as a core skill rather than a nice-to-have.
No Mass Displacement Yet - But the Clock Is Ticking
The report's most reassuring finding is also its most concerning: there are no real signs of AI-related mass job loss yet. But the conditions for rapid displacement exist, and the early warning signs - slowing young-worker hiring, employment drops in AI-exposed industries, the widening skills gap itself - suggest the transition is underway.
The 37% of business leaders who anticipate replacing human workers with AI by the end of 2026 represent a significant share of the economy. If even half follow through, the impact would be measurable in employment data within months.
Industry Implications
For employers
The skills gap creates an immediate strategic decision: invest in upskilling existing workers, or hire AI-proficient replacements? Companies that choose the latter risk losing institutional knowledge while gaining AI capability. Those that invest in training retain both.
For workers
The message is clear: AI proficiency is no longer optional for knowledge workers. The gap between power users and non-users will continue to widen, and workers who do not adapt risk being on the wrong side of eventual displacement.
For outsourcing and VA providers
The AI skills gap creates both risk and opportunity for professional virtual assistants:
Risk: VA providers whose teams do not develop AI proficiency will lose competitive ground to providers whose teams use AI to deliver faster, higher-quality results.
Opportunity: VAs who become AI power users can handle more complex work, serve more clients, and command higher rates. The skills gap among VAs mirrors the broader workforce gap - and the providers who close it first gain a significant market advantage.
Training as differentiation. VA companies that invest in AI training for their teams can market AI-augmented services as a premium offering. In a market where most workers barely use AI, a VA team that uses it expertly is a genuine competitive advantage.
The AI skills gap is not just a workforce trend. It is a sorting mechanism that will determine which workers, companies, and service providers thrive in an AI-augmented economy - and which get left behind.