What has changed since 2019?
Back in our blog from 2019 Artificial Intelligence in Service Design, we predicted that AI would play a greater role in services, but that this would also come with its fair share of challenges. Now, in 2026, we’d like to look back on this and, above all, consider how we can continue to design services that have the greatest possible impact. One thing is certain: AI is no longer hidden in the background, but forms a visible layer in people’s daily lives and in service provision.
AI has moved from the back end to becoming a fully-fledged stakeholder
AI has now come to the very forefront and, for many, is even present in their daily lives. This has many positive consequences, such as faster services with shorter waiting times and getting an answer to your question at any time of the day. It often also improves the accessibility of a service by simplifying complex information, and often tailoring it to your specific situation.
At the same time, AI at the forefront does not mean that human service provision should disappear. AI is powerful as an accelerator and support tool, but it is not desirable in every situation and certainly not for everyone. Some people cannot or do not want to work digitally, need extra support, or find themselves in a context where a human conversation is essential. If we automate too much, we run the risk of creating a less accessible service for those who need help the most.
That is why we should design AI as an additional layer within the service: an option and a tool, with clear opportunities to work with a human when necessary or desired.
Trust is becoming a key differentiator.
Back in 2019, we noted that the difficulty in explaining the ‘why’ behind traditional machine learning acts as a barrier to trust. Today, we are working with far more complex LLMs, which has often made this even more challenging. That barrier to trust has therefore only become more prominent and significant. Legislation and smart control systems help to manage part of the risk, but the technology is evolving so rapidly that policy and practice struggle to keep up.
The tricky thing is that these new models do appear to reason logically, and as a result often inspire trust in users quickly and easily. But sounding convincing is not the same as being explainable or correct. Misinformation and hallucinations can lead to incorrect advice with major consequences, reputational damage and extra remedial work. Add other inconsistencies to the mix and you get frustration and mistrust, whereby trust can sometimes be completely shattered even after a single bad experience. Research1 shows that Flemish people display considerably less enthusiasm towards AI and harbour more and more concerns. Even young people are increasingly concerned about authenticity and fear they will no longer be able to distinguish between what was created by a human and what was created by AI.
The strongest organisations will be precisely those that can use trust as a differentiator, with smart control and escalation mechanisms. In these times, trust is therefore not just a hurdle, but can also be the very key to bringing valuable and sustainable services to market.
That authentic human touch at just the right moment.
These days, all it takes is a few clicks to get AI output that’s barely distinguishable from human work. From clear summaries of complex information to detailed prototypes and even fully generated videos. And all this simply by entering a clever prompt. It is, frankly, impressive how quickly this has become ‘normal’, but it is precisely in that ease that tomorrow’s obstacles lie.
As many organisations deploy the same models in similar ways, there is a risk of a wave of standardisation: visualisations, tone of voice and solutions in general are beginning to converge. This makes differentiation more difficult, and at the same time, the perception is growing that AI output is ‘too perfect’, meaning it is more quickly perceived as impersonal or less authentic.
That is why it is important to consciously examine where, in your service provision, people really make the difference. Let AI handle the routine work, so that employees can devote their time and energy to the key moments that really matter.
Conclusion
AI is no longer just hype, but a permanent feature of service provision, because it increasingly makes the difference in speed, accessibility and quality.
The more powerful AI becomes, the more important service design becomes: to keep services reliable, secure and human. The opportunity lies not in “AI everywhere”, but in AI in the right places within the user journey. That is why we believe in human-first, AI-enabled: technology as an enhancer, not a replacement.
Our role is clear: we help organisations deploy AI with maximum impact, in an accessible way, and starting from the human and the user, not from the tool. What feels new today will be standard tomorrow. The organisations that are already embedding AI responsibly and humanely into their services are the ones making the difference.
