The position page states our opinion. This one answers what makes it trustworthy.
How we work
Sources come first. Every number carries a comparison and a source, and every direct quotation is looked up in the original before publication, however plausible it sounds. Where the evidence is thin, the text says so.
Most articles at ThinkBeyondAI start as a conversation between two people who do different things. A student asks why a process works the way it does, and a practitioner answers from inside it. It runs the other way just as often, when someone with fifteen years in a firm hears the question their field stopped asking. That conversation happens before the draft, and the draft carries what came out of it.
One named person owns the argument of each piece and keeps the byline. An editorial pass checks sources and reasoning before anything goes live. The contributor circle is open, and every submission goes through that same check. Learning material follows the same route: built with practitioners who do research and deployment work, and checked the same way before anyone sees it.
How we use AI
We write about artificial intelligence and we use it. Four commitments, phrased so you can hold us to them:
- AI is used in producing this publication, and we state that openly.
- A person owns the argument of every piece.
- A person verifies the sources before publication.
- Nothing is published unread.
Who works on this
ThinkBeyondAI was founded by Sven von Bismarck, Emil Ohligs and Carl Erhard, and it has grown well past the three. Students, researchers and practitioners write here, out of consulting, banking and academic research. A few words from our founders:
Sven von Bismarck. I never read economics and law as disciplines so much as rooms in which decisions land on people and companies. Early in my career I learned what it means to carry responsibility once a situation has stopped offering easy answers. That was first in consulting mandates, later as an interim manager and CFO in complex restructurings, working alongside family businesses, international investors and corporate groups. Clarity, judgment and speaking to people as equals have come to matter more to me than any model or spreadsheet cell. What I want from ThinkBeyondAI is that young talent does not unlearn thinking while the machines keep getting better.
Emil Ohligs. Studying physics in Vienna taught me the value of working in a structured way: state a hypothesis, build a model, check the result. That habit is still with me when I write here. What draws me to these systems is the mathematical and data-analytic layer underneath them. I want to know how a model actually works, which data it was trained on, which assumptions slip in unspoken, and what risks follow from that. Machine learning now runs from physics through to financial mathematics, which is what makes a sober look at it worth taking. Where are a model's limits, and what breaks when the data quality or the context is missing?
Carl Erhard. I grew up between Germany and the United States, and spent my school years collecting views into very different fields through internships and side jobs, from business and medicine to law, real estate and architecture. In 2023 I moved to Vienna, studied philosophy, and then started the business program at WU. What became clear along the way is how central the economy is to everything around it: anthropology as much as arithmetic, connecting people, firms, countries and technology. At ThinkBeyondAI I want to show what AI does to the economy, to professions and to the job market, realistically and with the research to back it.
International collaborators
Shay Luo spent twelve years in management consulting, latterly as a partner at Kearney, and now builds an AI consultancy in Silicon Valley. Assistant Prof. Inhwa Kim teaches business at Oregon State University and researches human-AI interaction and robotics, which sits directly on the subject of this site. They and other partner organizations are on the collaborators page.