How artificial intelligence is creating the super employee and redefining work

Professionals who need to prepare presentations, analyze data, write reports, and review documents are now turning to AI tools to speed up these tasks and free up time for strategic decision-making. This phenomenon has been dubbed the “super employee,” a term coined by analyst Josh Bersin to describe individuals who leverage AI to boost productivity, creativity, and execution capabilities.

What it means to be a super employee

Being a super employee doesn’t mean one person is literally doing the work of three employees. Instead, AI enhances individual capacity, enabling more tasks to be completed in the same amount of time. For example, a marketing professional can use AI to research information, organize data, draft text, and evaluate campaigns. Similarly, a financial analyst can use AI tools to structure spreadsheets, summarize documents, and identify patterns.

How AI is changing the way we work

In practice, artificial intelligence takes over time-consuming tasks such as text production and review, information analysis, presentation creation, programming, research, and document organization. The benefits go beyond speed, as professionals can now take on new tasks that were previously neglected due to time constraints.

A study conducted by Anthropic involving 132 engineers and researchers highlights this trend. Participants reported using Claude for about 59% of their work and experienced an average productivity increase of 50%. The study also found that 27% of tasks completed with AI assistance would not have been done without it.

The limits of AI-driven productivity

The relationship between AI and productivity cannot be simplified to a fixed multiplier. There’s no rule that an employee using AI is equivalent to three employees. Results vary depending on the profession, task, user’s level of expertise, and the tool being used.

In another study, Anthropic analyzed 100,000 real conversations with Claude and estimated that tasks performed with AI assistance would take an average of 90 minutes without the tool, representing an 80% reduction in execution time. However, this calculation doesn’t fully account for the time professionals spend verifying information, correcting AI-generated answers, or validating results. Therefore, the estimated productivity gain should not be seen as an automatic increase in productivity across all professions.

The need for human adaptation

The concept of super employees goes beyond learning how to write effective prompts. Workers must identify which parts of a task can be delegated to AI and which require human knowledge, context, and judgment.

At Anthropic, engineers reported working in areas outside their original expertise. The company also observed an increase in the complexity of tasks performed by Claude Code and a reduction in the number of human interventions required for certain activities. This marks a significant shift: professionals now act less as executors of individual steps and more as supervisors responsible for guiding, reviewing, and integrating AI-generated work.

Factors that determine success

Using AI tools alone doesn’t guarantee the same results for everyone. Knowledge of one’s own work, the ability to provide clear instructions, mastery of available tools, and skill in verifying information all influence outcomes. It’s also crucial to know which tasks are suitable for automation and which require human involvement. Even answers quickly generated by AI need to be checked when they involve information critical to professional decisions.

A 2026 Gallup survey found that 65% of employees in organizations that have implemented AI say the technology has positively impacted their productivity and efficiency. However, only 14% believe AI has significantly transformed how work is done in their organization. This suggests that for many professionals, AI still serves primarily as a tool to enhance existing workflows rather than completely replace them.

Impact on careers and businesses

The rise of super employees is also changing the skills companies value. As AI accelerates certain execution tasks, skills such as analysis, decision-making, communication, business knowledge, and system supervision are becoming more important.

Bersin’s concept aligns with this shift: instead of focusing solely on automating jobs, companies can redesign roles to combine human professionals with AI systems. For workers, this means learning to use AI involves more than just mastering a specific tool. The challenge is to understand where the technology creates real value, how to verify its results, and how to integrate it into existing professional activities.

Available studies show significant productivity gains, but they also indicate that “doing the work of three” is a metaphor, not a universal standard. The impact of artificial intelligence depends on the task, the professional, and how the technology is integrated into daily routines.