AI might profoundly change the way we work, but ensuring its wise use requires significant effort. There is an obvious risk of increasing quantity rather than enhancing quality
Technology always comes with the promise of helping us get on top of things. But at the same time, technology systematically gives us more things to get on top of. When cars became widely available, one might have expected that this hyper-efficient mode of transportation, which could get us from A to B in no time, would drastically reduce travel time. Instead, what happened was that the number of A’s and B’s we deemed important to travel between exploded. The same pattern repeats itself with other technologies. Before email brilliantly automated the most time-consuming aspects of letter exchange, writing and distributing letters took up a very limited part of a typical workday. Today, it has become a massive time sink. The underlying dynamic seems to be that we do more of what becomes easier rather than using the time for value-creating activities.
AI Shouldn’t Repeat Past Mistakes
The question every organisation should be asking itself today is how to approach the promising technology of our time — artificial intelligence — without repeating these unproductive patterns. Interestingly, the branch of AI generating the greatest expectations — generative AI — is also riddled with dilemmas. Unlike traditional AI, which is well suited for tasks such as data analysis, forecasting, and segmentation, generative AI excels in areas like text production, interaction, and idea development. Unfortunately, it seems we are already well on our way to using generative AI to repeat past mistakes—doing more of what becomes easier instead of creating real value: More AI-generated corporate LinkedIn posts, link-building blog articles, lengthy emails, and press releases. More sent-out proposals and rising number of disengaged job applications.
The AI Paradox: Producing and Filtering at the Same Time
What’s striking is that the flood of content initially triggered by the rise of digital media and communication channels was, in the first place, addressed using AI: machine-learning algorithms that filter the overwhelming amount of information. Today, as an increasing share of information is generated by AI, we are approaching an absurd situation where we now have two types of artificial intelligence —one that filters data and one that generates data — ultimately leaving us with the same challenge as before. Once the infinite stream of information is generated, sent, and received, another AI model sorts through it, leaving us with a more manageable amount that still requires human attention. Whether it’s job applications, proposals, or emails, there is a limit to how much we can realistically process. So, in the end, we end up roughly where we started—but now with a new technology taking over much of the communication between businesses, people, and partners. Escaping the technology trap is not easy, but there are steps we can take.
Critical Questions Before Embracing AI
On a practical level, we can continue asking ourselves and each other critical questions about what we intend to use generative AI for. Does this actually improve quality? How does it align with our core business? Does it have a positive impact on employee well-being and company culture? What new behaviors will it create?
AI Should Be More Than Just Generative
From a technological perspective, when exploring AI’s applications within an organisation, we should ensure that we think about AI broadly rather than limiting it to generative AI. Meaningful automation, efficiency gains, and genuine quality improvements should not be sought exclusively through generative AI but also through classical AI and other available tools.
Vision Before Technology
Fundamentally, our approach to technology adoption should adhere to timeless principles and address the essential questions that were crucial before AI and remain just as critical today:
- How do we create an outstanding workplace?
- How do we deliver exceptional customer experiences?
- How do we develop fantastic products?
- How do we stay relevant in our market?
- How do we ensure economic, environmental, and social sustainability?
Or put differently: Let vision take precedence over technology. Given AI’s potential, there is a real risk that it either becomes a solution searching for a problem — leading to failed projects and wasted investments — or that we create a mindless production machine that increases the volume of content, interactions, and ideas without making a real difference to our core business.
We should not fear generative AI, but as with all technology choices, we must think carefully before embracing it.
This article have previously been published in Danish on the business news site Finans.dk and the co-auther is Tim Daniel Hansen
About the authors
Tim Daniel Hansen is the CEO of Droids Agency delivering consulting services and products within Artificial Intelligence and Intelligent Automation.
Thomas Telving is a tech-analyst, philosopher and AI ethicist doing talks and teaching courses about smart use of generative AI and AI ethics.
Translated by the help of generative AI.
Photo: Alexander MIls, unsplash.com
