Will your job be taken over by AI? No-but your work is changing (thanks to AI Agents)
AI will not wipe out 'all jobs'. Approximately 80% of your current tasks can soon be handled (in part) by AI Agents-software that executes assignments independently. Result: teams become smaller, overhead shrinks, and your craftsmanship becomes even more important.
AI will not wipe out ‘all jobs’. Approximately 80% of your current tasks can soon be handled (in part) by AI Agents-software that executes assignments independently. Consequences: teams become smaller, overhead shrinks, and your craftsmanship becomes even more essential. The winners possess three skills: adaptability, critical thinking, and domain knowledge. You will become the conductor of an AI orchestra (AI Agent orchestration).
What exactly are AI Agents?
AI Agents are systems that autonomously plan and execute tasks. Think of: conducting research, scheduling appointments, analyzing data, drafting emails, creating content, summarizing customer cases, preparing quotes-without you directing every single step. They combine models (LLMs), tools, and workflows to deliver results instead of isolated answers.
Why is this different from "just AI"?
- From assistant to executor: not just generating text, but completing tasks.
- Tool usage: an agent can control your CRM, calendar, spreadsheet, or codebase.
- Reasoning & planning: agents break goals down into subtasks and provide feedback loops.
Will jobs disappear eventually then?
Short answer: no. What will change is the mix of tasks within those jobs. Much repetitive, peripheral work will be automated. As a result:
- Teams become smaller, and focus shifts toward core work.
- Specialists (with deep professional knowledge) gain more value.
- New roles emerge (agent design, management, monitoring, ethics, security).
See it as upgrading your role: less time spent on administration and handovers, more time for your profession-strategy, creativity, client contact, negotiation, diagnostics, analysis.
80% of your tasks automated-what does that mean in practice?
- Recalibrated task sets: what you do today in 8 hours may take 2–3 hours tomorrow with agents-the rest of your time goes toward deeper work and quality.
- Increased quality: humans devote attention to exceptions, nuance, and creative solutions.
- Reduced lead times: proposals, reports, and analyses are generated faster, allowing for more iterations with clients/colleagues.
Important: automation ≠ disappearance of value. You determine context, goal, quality, and impact.
The 3 skills you need to sharpen now
1) Adaptability
The ability to learn, unlearn, and relearn. Tools and models change rapidly; your ability to move with them is a superpower.
Exercise: schedule 1 hour each week to test a process step with an agent (prompting, tool integration, evaluation). Document what works.
2) Critical Thinking
AI output is not sacred. You need verification, source criticism, and assumption checking-especially as you hand over the 'keys' more frequently.
Exercise: utilize a QA checklist (source citation, consistency, plausibility, bias, dates, definitions) before sending anything out.
3) Domain Knowledge & Experience
Your craftsmanship becomes more vital. You know what 'good' looks like, recognize exceptions, and set the right requirements for an agent.
Exercise: create a golden set: 10–20 example cases with perfect outcomes. Use these to train and test agent quality.
AI Agent Orchestration: You as the conductor of an AI orchestra
Call it AI Agent orchestration: the ability to formulate goals, configure agents, connect tools, monitor quality, and combine results.
Core competencies of a good 'conductor':
- Defining goals and KPIs sharply (what is "good enough"?).
- Designing processes & tools (which steps, which APIs/source data?).
- Governance & security (permissions, logging, audit trails).
- Evaluation & adjustment (A/B testing, feedback loops, regression tests).
What can you do today? (Practical roadmap)
- Inventory tasks (30–60 min/task) that are highly repetitive.
- Choose 1–2 use cases with clear input/output (report, proposal, analysis).
- Build an initial agent flow (prompt + tool + review step).
- Measure time savings & quality, establish a golden set.
- Scale controlled up to team level (permissions, monitoring, guidelines).
Pro-tip: start small, but measure everything. Data on time savings and quality makes scaling easier.
// About the author
Job van den Berg
Mede-oprichter, AI Keynote Spreker & Techondernemer
Tech-ondernemer (1989) met een achtergrond als socioloog (Research Master (MSc) in statistiek en sociologie) en een van de meest gevraagde keynote sprekers over AI en data in Nederland. Als mede-oprichter van Ai.nl, The Automation Group en Proxies leidt hij engineers die agentic AI van prototype naar productie brengen binnen enterprises. Op het podium vertaalt Job die hands-on praktijk naar concrete strategieën. Eerder was Job Chief Data bij o.a. DPG Media en Kantar. Hij is co-auteur van 5 boeken over AI waaronder 'AI Agents' en 'Handboek AI Strategie' en een veelgevraagd expert in de landelijke media.
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