AI feels new – but this is not the start of the story

In my last post in 2025, I asked the question: Everyone is talking about AI – but what are we really doing?

This post is the next step in the same series. In 2026, I will share reflections, frameworks and experiences around what AI actually means in practice - starting from the syllabus book Generative AI for Business by Shubin Yu, which is part of my master's study, combined with my own experiences and practical observations.

Christmas has given room for quieter days, reflection and self-study. For me, this period has been an opportunity to further immerse myself in AI and strategy - both through the subject matter in the study and practical exploration of various AI models and areas of use.

AI is experienced as new for many, but is in reality the culmination of several decades of technological development. Already in the 1950s and 1960s, the term artificial intelligence was introduced. Since then, we have been through several waves - from expert systems and neural networks, via machine learning, to deep learning and today's generative models.

The breakthrough around 2020–2023 therefore did not mark the start of AI, but a clear shift in availability and application. Large language models made the technology practical, scalable and relevant in a business context.

At the same time, I feel that many organizations are falling apart - something the book also addresses. We test the tools and see quick benefits, but often lack the strategic understanding: What is really new now, and what is required to create lasting value?

In this series, I will use the book as a structured starting point and extract the main lines further along some clear tracks. Among other things, I will take a closer look at:
• the transition from simple AI use to strategic transformation
• the importance of data, context and own sources of information
• what is required to implement AI in practice – from exploration to scaling
• how AI affects management, people and commercial processes
• as well as ethics, governance and responsibility

Where it is natural, I will also connect this to my own experiences from previous roles - particularly within IoT, automation, robotization and data-driven ecosystems - which I see today more clearly in the context of AI.

The next post comes on Wednesday, where I go into more detail about a central framework from the book: The five A's (from Access to Agents) - and why most organizations stop earlier than they think.

I hope more people will share their own experiences, perspectives and questions along the way - either here in the comments section, in direct dialogue, or over an informal cup of coffee. This is a field where we are all still learning. Join me on my little "journey".