How AI Is Changing the Nature of Work: Less Execution, More Verification and Judgment
By Pedro Sonda, dooop
AI is changing the nature of work in four directions: people spend less time executing tasks and more time verifying what AI produces; value shifts from memorized knowledge to judgment; work is organized into flows combining people and systems; and each professional coordinates tools and agents, not just their own schedule. Available data indicate more transformation of roles than mass elimination, but the change in skills is rapid and requires preparation.
Updated October 2026.
What the Data Shows
| Data | Source |
|---|---|
| By 2030, 170 million jobs are expected to be created and 92 million displaced, a net gain of 78 million; nearly 40% of skills required at work will change | World Economic Forum, 2025 |
| 77% of employers plan to reskill their employees; 41% plan workforce reductions due to AI automation | World Economic Forum, 2025 |
| 14% of respondents from organizations using AI reported workforce reductions in the past year, less than half of the 32% who expected reductions in the previous survey | McKinsey, 2026 |
| 80% of respondents say AI improved their individual productivity | McKinsey, 2026 |
| Among Brazilian industries not adopting advanced digital technologies, lack of qualified personnel as an obstacle rose from 46.4% to 60.6% (2022–2024) | IBGE, 2025 |
Interpretation: Forecasts of workforce reductions exist, but measured effects so far have been smaller than expected. What changes rapidly is the content of work and the skills required.
dooop Framework: The 4 Shifts in Work
1. From Execution to Verification
When AI produces the first draft of a text, analysis, or code, human work shifts to reviewing, correcting, and deciding if the result is adequate. A Microsoft Research study with 319 knowledge workers, reporting 936 examples of generative AI use at work, concluded that AI shifts critical thinking toward verifying information, integrating responses, and supervising the task (Lee et al., 2025).
The same study shows the risk: greater trust in AI was associated with less critical thinking, while higher self-confidence in the professional was associated with more critical thinking.
2. From Memorized Knowledge to Judgment
Knowing the answer loses value when anyone can ask an assistant for a response. It gains value to know if the answer is correct, fits the context, and what the consequences of using it are. The World Economic Forum highlights analytical thinking, resilience, leadership, and collaboration among the fastest-growing skills, alongside AI and data competencies.
3. From Isolated Task to Flow
With agents, entire parts of a workflow can be executed by systems. Human work focuses on exceptions, decision points, and improving the flow itself. This requires people to understand the end-to-end process, not just their step. See How AI Agents Change Business Processes.
4. From Individual Work to System Coordination
Microsoft describes a near future where each professional creates, delegates, and manages agents, proposing to measure the ratio between humans and agents in each role (Microsoft Work Trend Index, 2025). The same report notes that 80% of workers say they lack enough time or energy for their own work, which helps explain the search for additional capacity.
What Changes for Operational Teams
| Before | With AI |
|---|---|
| Filling in, copying, and checking data | Reviewing what was filled and handling exceptions |
| Following a procedure | Understanding the procedure and signaling when it fails |
| Asking an experienced colleague for help | Consulting an assistant and knowing when it is insufficient |
| Being evaluated by volume executed | Being evaluated by quality and problems solved |
These changes require practical, day-to-day training, not just lectures about AI’s potential.
What to Do Now
- Map, by role, which tasks AI already performs and which verification and judgment tasks have emerged in their place.
- Teach verification, not just usage: how to check sources, numbers, and conclusions produced by AI.
- Review how work is evaluated to avoid rewarding volume when value has shifted to quality.
To prepare operational teams, learn about dooop’s program at dooop.com.br/ia-para-times-operacionais.
Frequently Asked Questions
Will AI eliminate jobs? Projections indicate displacement of some jobs and creation of others, with a net positive overall, according to the World Economic Forum. The effect varies greatly by role and sector, with those performing repetitive information tasks most exposed.
Which skill should I develop first? Verifying and evaluating what AI produces. It is the skill that supports all others and best protects against errors.
Also Read
- Which Human Capabilities Become More Important with AI?
- The Augmented Human: How to Work Better with AI
About dooop
dooop is a consultancy based in Caxias do Sul (RS) that prepares leaders and organizations to transform artificial intelligence into business capability through strategy, governance, and training.