AI news
April 7, 2024

Why We Need a Positive AI Mindset

… and why it’s our duty to spread the word if we don’t want our colleagues to lose their jobs.

Marcus Völkel
Marcus Völkel

When we recently presented an interactive prototype that we developed under time pressure in a design sprint, we received nothing but positive reactions. The interesting thing? The idea wasn’t created in our heads alone — our design sprint team was complemented by a range of generative AI tools.

Artificial intelligence was our sparring partner, not only helping us to manage complexity, but also inspiring us to come up with creative approaches that we wouldn’t have considered before.

This presentation meeting was a real eye-opener for the participants: AI is not a job killer, but a partner that complements and expands our capabilities.

Nevertheless, is the hype around generative AI over — or is it just my filtered perception? In my bubble, I’m reading more and more critical articles and AI-bashing — often with lurid messages: AI will steal our creativity, our empathy will atrophy, quality will become a relic — and above all: our jobs will be stolen. This attitude is fed by media that present AI as either a panacea or a dystopian doomsday scenario.

Negativity bias and the phase of disillusionment

This feeds the negativity bias of laymen I deal with: They perceive negative information more strongly than positive information. Add the technological complexity and the feeling of being left behind — and AI bashing becomes a feel-better pill. But the fear of contact remains, the rants get louder and the mass of those who are left behind gets bigger. Negativity bias becomes confirmation bias: Ignorance and misunderstandings widen the gap between supporters and opponents.

So yes, the hype seems to be over, as is the case with every innovation at some point. What follows the inflated expectations at the beginning of every hype cycle is the phase of disillusionment: The limits and challenges of generative AI become clearer. What is particularly clear, however, is that AI is here to stay. This graph from Gartner predicts that Generative AI will reach its plateau of productivity in 1–4 years.

2023 Gartner Hype Cycle graph for emerging technologies. The graph illustrates the typical progression of technology hype and adoption, starting with the Innovation Trigger, rising to the Peak of Inflated Expectations, followed by the Trough of Disillusionment, climbing up the Slope of Enlightenment, and finally reaching the Plateau of Productivity.
Source:, Hype Cycle for Emerging Technologies 2023.

Escaping the state of shock

We have been in the process of anchoring AI tools in the processes and workflows of our digital agency for some time now (it’s March 2024). Internally, I also want to pass on the enthusiasm and passion that we need to continue developing innovative solutions.

Read how we anchor AI tools in workshop formats like design sprints:

Boost your design sprints with Generative AI

How we upgraded our UX research processes with Custom GPTs and a positive AI mindset

I thought it would be sooo easy. Especially in a company that is committed to customer centricity and innovation, it was unimaginable for me that not everyone shouted “Yes, here!” when we started rolling out ChatGPT Team company-wide, for example. But in conversations and workshops with people who only have half-knowledge of the topic or only know AI from the media, I always hear that they are afraid of contact.

I often feel as if they’re in a state of shock: “I know I have to do something, everyone is talking and writing about it, but when, how, and where do I start and what do I need to do?”

The uncomfortable truth is that those who already feel left behind will really be left behind if we don’t show them how to catch up. It’s our duty to do that. It is important to build a bridge between technological innovation and social needs.

Interactive formats for a positive AI mindset

We have therefore developed interactive formats for our employees to build this bridge.

  1. AI Lunch & Learn
    A chill, informative lunch series where we discuss current AI topics or introduce each other to tools and trends. It’s the perfect setting to build a positive AI mindset in a relaxed atmosphere.
  2. AI workshops
    The aim is to overcome entry barriers and gain practical experience with AI tools. For everyone who gets access to our ChatGPT workspace, there is a basic workshop to help them integrate ChatGPT and custom GPTs into their everyday work. Other workshops range from basics to advanced techniques.
  3. AI Hackathons
    In a hackathon, an interdisciplinary team (typically UX/UI designers and web developers) works on creative AI solutions within a certain period of time. This not only promotes teamwork but also demonstrates the practical applicability of AI in our agency.
  4. AI iSpirations
    In our so-called iSpiration events, we discuss best practices, case studies, and projects on the successful use of AI with external speakers that are not necessarily from our day-to-day work, but inspire us and allow us to think outside the box.
  5. Community of Practice (CoP)
    Establishing a CoP around AI creates an internal platform for ongoing exchange and continuous learning. Regular meetings, sharing specific experiences, and tackling challenges together help to break out of project silos and develop new ideas.

These formats not only promote learning, but also team bonding and strengthen the feeling of being part of an AI-positive movement.

The four AI types: Enthusiasts, skeptics, pragmatists, and concerned

In the course of my work, four types have emerged. Each of these types contributes to the AI discourse in their own way. The enthusiasts drive innovation, the skeptics provide the necessary critical reflection, and the pragmatists help to find a realistic and sustainable way of dealing with AI. And then there are the concerned.

  1. The enthusiasts
    * Characteristics: They are often tech-savvies, innovators and early adopters. They are enthusiastic about the possibilities of AI and actively promote its use and development.
    * Behavior: Enthusiasts like to experiment with new AI tools, use them in different areas, and are open to the changes that AI brings.
    * Challenge: They sometimes tend to underestimate the limits and risks of AI and can ignore overcritical voices.
  2. The skeptics
    * Characteristics: The skeptics are cautious to distrustful of AI.
    * Behavior: They question the necessity and potential risks of AI. They prefer tried and tested methods and often raise (important) issues such as data protection, ethics, and job security.
    * Challenge: Their critical questioning is important, but can also lead to delays in the acceptance and integration of AI.
  3. The pragmatists
    * Characteristics: Pragmatists adopt a balanced attitude towards AI. They recognize the potential as well as the limits and risks.
    * Behavior: They weigh up the pros and cons and make targeted use of AI where it offers added value. They are open to new ideas, but also mindful of best practices.
    * Challenge: They have to constantly weigh up the pros and cons and move in a field between rapid innovation and necessary caution.
  4. The Concerned
    * Characteristics: They are characterized by deep-seated fears and distrust of AI, often based on limited or biased information.
    * Behavior: This group tends to avoid AI and defend their position with emotional arguments based on worst-case scenarios and personal fears.
    * Challenges: The main task is to reduce fears and promote a more realistic understanding through factual education, empathetic treatment, and the demonstration of positive, practical AI applications.

Yes: AI is changing jobs

Concerned people often ask questions such as “Will AI kill our jobs?” or “Will automation replace me?”. I see this as a fundamental uncertainty — but also a lack of understanding of the role that AI will play in our future world of work. This group in particular is often overwhelmed by the complexity and fear of being left behind.

Yes: AI is changing jobs by automating repetitive and time-consuming tasks. This in turn gives us the opportunity to focus on more complex and creative aspects of our work.

Our roles will change, not disappear. Those who use AI will increase their productivity and efficiency and create new opportunities — not only for themselves, but also for their organizations.

To reduce the fears and uncertainties, we need education, training, workshops, and, above all, exchange. People need to learn the skills and abilities to use AI effectively in their everyday lives and contexts. In this way, they learn to understand that they are in control of AI, not the other way around.

The bottom line: Generative AI is a tool, not a threat

I think it’s important to understand that AI in itself doesn’t “steal” jobs. Generative AI is a tool that helps people to improve work processes. But the truth is also that automation through AI, for example, can actually make jobs redundant, especially in areas that are heavily focused on repetitive tasks.

It’s about the way lifelong learning determines the future of our work: how we develop ourselves, how we train ourselves, how we use AI. Those who use AI benefit from it: They can work faster, be more creative, broaden their horizons, and become better at what they do. So the real change is not in the AI itself, but in the way we use it and deal with it.

In the end, it’s not AI that steals our jobs. It’s the people who use AI with a positive mindset. And we, the enthusiasts, the innovators, the advocates, the tech-savvies — we should help them to do just that.