AI and productivity: booster or quality accelerator?

The question that comes up time and again: will AI agents make us more productive? The potential of AI lies partly in the amount of work we can get done, but just as much in the quality and innovation it enables.

The question that comes up time and again: will AI agents make us more productive? Labour productivity in the Netherlands has barely grown since 2010, with less than 1% per year, according to figures from CBS. Rabobank Research emphasises that this limited growth in productivity is causing a serious problem. They state the following: if the industry continues to grow at an average of 2.1% per year until 2035, labour productivity must increase significantly. Due to the shrinking workforce, fewer workers due to an ageing population, and declining population growth, this growth can only be achieved by better utilising technology. The use of AI agents is not seen as an option, but as an economic necessity. Without this transition, we cannot cope with the workload, the economy will stagnate, and further growth will be impossible, according to Rabobank Research.

AI and productivity is therefore a topic that you could easily spend an entire afternoon discussing. It raises questions ranging from practical benefits to broader implications for work and innovation. But will AI ultimately truly make us more productive?

In an article by Sandra Olsthoorn in the FD on 10 January 2025, the so-called productivity paradox was discussed. We also saw this phenomenon with the advent of computers. The idea is that it often takes a while before technology actually leads to productivity gains. There are two main reasons for this:

1. New work patterns and adaptation time: Technology brings new ways of working. People need to get used to the technology and learn how to work with it. This learning process takes time and requires investments in training and adjustments to work processes.
2. Recouping investments: Companies must first recoup their initial investments in technology before they can fully utilise its benefits. This also applies to AI, which often requires significant investment in both infrastructure and skills.

Another interesting question that arises here: what do people do with the time freed up by the use of AI? Do they use this time to work more efficiently, or do they spend it on improving the quality of their work? In some cases, AI can increase productivity, while in other cases the focus shifts to a higher quality of output.

Thinking more broadly about AI and innovation

Another perspective is offered by Bob van Luijt, co-founder and CEO of Weaviate, in an article in Forbes. This book also includes a more extensive interview with him. He discusses the concept of "Going short on growth." Many decision-makers in companies primarily focus on cost savings when implementing technology. However, this short-term thinking can hinder innovation. Van Luijt advocates for a broader, visionary approach to technology:

• Exploring new opportunities: Technology such as AI offers unique opportunities to venture into new areas, improve services, and enable activities that were previously unthinkable.
• Focus on innovation: Instead of only looking at how AI can save costs, companies should consider how AI can contribute to strategic growth and long-term value.

His message is clear: dare to think bigger and do not just focus on economic models that are only aimed at short-term productivity gains.

Perhaps AI is not the ultimate productivity master we are hoping for, but rather a tool that helps us work smarter and more strategically. The potential of AI lies partly in the amount of work we can get done, but just as much in the quality and innovation it enables. And with that, we return to the topic we discussed in an earlier article on Ai.nl, which is that the use of AI agents is about a fundamental recalibration of organisations. It's about reinventing how tasks can be executed faster.

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