Agentic AI: Will We Choose the Spreadsheet or the Soul?

The occasionally justified fear surrounding agentic AI is that it will cost jobs and make organizations more efficient, but also colder. Technology takes over labor, companies cut costs, profits rise. The classic automation narrative. And let's be honest: that reflex is understandable. In economically uncertain times, cost reduction is a quick, measurable lever to pull. But perhaps we are looking at it the wrong way.

Leaders who see AI primarily as a cost-saving machine reduce their role to spreadsheet management. They optimize margins, restructure FTEs, and present a polished quarterly result. In my view, that is not leadership with ambition, but management without a soul. A true leader does not start with the question: "Where can we cut?" but with the question: "Where do we want to grow? How can we provide more value? What ambition do we finally dare to realize?" Agentic AI is not a glorified cost item; it is a capacity multiplier. It enhances thinking and execution power. The question, therefore, is not how many people you can replace, but how much value you can add. Profit resulting from contraction is finite. Profit resulting from value creation is scalable.

Yes, you can reduce a support team from ten to two people. That is significant and sometimes inevitable. But imagine if those other eight people retrained and moved closer to the customer, the innovation, or the mission. Imagine if they started proactively identifying customer needs, building communities, and testing new propositions. Then the conversation shifts from "saving costs" to "increasing impact." Companies that focus heavily on customer experience understand this. IKEA decides to put more, not fewer, people in the store precisely to strengthen the experience. Sales organizations deliberately choose to let teams engage with customers more frequently and deeply. Technology takes over repetitive work so that people can focus on relationships, creativity, and trust. The reorganization of work then leads not to depletion, but to enrichment.

That is a fundamentally different view of productivity. Productivity is not just about fewer hours per output, but also about more meaning per interaction.

The same applies to the government. If agentic AI takes over processes carefully-with an emphasis on being ethical, safe, and sovereign-space is created. Space for customization. Space for human contact. Space for the conversation that goes beyond a form. In recent decades, we have increasingly protocolized and digitized public services. Counter logic, standard answers, referrals. Agentic AI can enable exactly the opposite: less administrative pressure, more time for genuine service. Not fewer civil servants, but civil servants who are allowed to be civil servants again. Not less contact, but better contact. You could say: agentic AI can put physical and human interaction back at the center because it reduces bureaucratic dead weight. The core question is: where do you position the human? On the fringes, as a cost item? Or at the heart of your strategy, as a carrier of meaning?

My prediction is that governments and companies that use agentic AI to pursue greater ambitions-to solve real societal and customer questions-will come out on top. Organizations that say: "We use AI to learn faster, understand better, and serve more personally." Not: "We use AI to become cheaper." And the interesting thing is: many forward-thinking organizations are already choosing that path. They see AI as a strategic lever, not a financial planer. Of course, all of this must be done ethically, safely, and responsibly. That is not an afterthought, but a prerequisite. Transparency, human control, data security, and digital sovereignty are essential. But let us not narrow the debate solely to risks and control measures.

Let us instead have a conversation about ambition. About how agentic AI can help us become more human instead of colder. How it can make organizations not just more efficient, but more courageous. How it can create space to stand closer to customers, citizens, and employees. Perhaps the real contrast is not man versus machine, but scarcity thinking versus growth thinking.

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// 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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