Builders who work close to the problem
Near the top of the list are the people who build artificial intelligence systems and live with the results. Founders and engineers who work close to deployment tend to be the most grounded guests, because they have learned the difference between a demonstration and a dependable product. They can explain what is genuinely hard, what surprised them and what they had to change once real customers arrived.
Nicole Junkermann values these guests because they cut through hype with experience. They have seen where a tool helps and where it quietly creates more work, and they are usually honest about both. Their accounts of building, failing and improving are exactly the kind of practical detail that makes the podcast useful rather than ornamental.
These are also the conversations that connect most directly to her work as an investor. Understanding how builders think about problems, data and defensibility is central to backing companies across artificial intelligence and deep technology, and the podcast is a chance to learn it firsthand.
Clinicians, scientists and people in regulated fields
Another group Nicole Junkermann is keen to invite works in fields where the stakes are high and the standards are exacting: clinicians, scientists and professionals in regulated industries. These guests bring a discipline that the wider conversation often lacks. They are used to asking hard questions about evidence, safety and accountability, and they apply the same rigour to artificial intelligence.
Healthcare is a particular interest, given how much artificial intelligence could contribute and how carefully it must be handled. A clinician who has actually used these tools in practice can describe the reality far better than any forecast. The same is true of scientists using machine learning in research and professionals navigating the rules that govern sensitive decisions.
These voices keep the podcast honest. They remind everyone that a fluent answer is not the same as a correct one, and that in many fields the cost of being wrong is high. That perspective is a useful counterweight to the enthusiasm that surrounds the technology, and it makes for richer conversation.
Economists, educators and people who study work
Because the future of work runs through so much of the AI Overview, Nicole Junkermann wants more guests who study work itself: economists, educators and people who think about how skills and organisations change. The question of how artificial intelligence reshapes jobs deserves more than anecdote, and these guests can bring evidence, history and a wider lens.
Educators are especially welcome, because the conversation about skills is really a conversation about learning. If the valuable human abilities are shifting towards framing, judgement and communication, then how we teach and train has to shift too. Guests who are rethinking that are working on one of the most important questions in the field.
Economists can help separate durable change from passing disruption, and place the current moment in a longer story of technology and work. That kind of perspective is hard to get from inside any single company, and it is exactly what a thoughtful listener wants alongside the practical accounts of builders and clinicians.
People who design how organisations operate belong in this group too. Operators, human resources leaders and the managers who actually redesign roles can describe what changes on the ground when a capable tool joins a team. Their accounts turn the broad question of the future of work into something concrete, and they help Nicole Junkermann keep the conversation rooted in real workplaces rather than abstractions.
Ethicists and the people asking the harder questions
No serious series about artificial intelligence is complete without the people who ask the harder questions about responsibility, fairness and oversight. Nicole Junkermann wants guests who think carefully about how these systems should be governed, not in slogans but in practical terms that organisations can actually use.
These conversations matter because trust is the foundation of adoption. A technology that is powerful but poorly governed will struggle to earn a lasting place in sensitive settings. Guests who can explain how to design human oversight, document decisions and keep people accountable add something the podcast cannot do without. It is a theme that connects to many of the other conversations, from healthcare to the questions she asks founders.
The aim is not to stage a debate between optimists and critics. It is to bring thoughtful people together so that the promise and the responsibility are discussed in the same breath. That balance is what Nicole Junkermann is after, and ethicists are an essential part of it.
What ties the wish list together
The common thread across this wish list is not fame or contrariness. It is the ability to make a complex subject clearer and to stay honest about what is known and what is not. Builders, clinicians, economists and ethicists each bring a different angle, and together they form the kind of well rounded conversation the AI Overview was created to host.
Choosing guests is really choosing what the podcast values. By seeking out people who are practical, rigorous and willing to admit uncertainty, Nicole Junkermann is shaping a series that helps listeners understand artificial intelligence rather than simply react to it. The next set of conversations is a chance to widen that circle, and that is exactly the plan.
Questions fréquentes
What guests does Nicole Junkermann want on the AI Overview?
Nicole Junkermann wants builders who work close to deployment, clinicians and scientists in high stakes fields, economists and educators who study work, and ethicists who think about oversight.
Why does she want guests from regulated fields?
Because they bring rigour about evidence, safety and accountability, and they keep the conversation honest about the fact that a fluent answer is not always a correct one.
What does Nicole Junkermann look for in a guest?
She looks for people who can make a complex subject clearer, ground it in real experience and stay honest about both the promise and the limits of artificial intelligence.