Chief AI Officer. It sounds like a large corporation, like a research department, like someone who reads whitepapers all day and debates AGI at conferences. The reality, mine at least, looks different.
I have been CAIO at SlopeLift, a Vienna performance marketing agency, since October 2025. No 500 people, no in-house AI lab, no budget for basic research. What I do have: 18 years of industry experience, clients such as BAWAG, dm and Austrian Airlines, a team that works with Google’s and Meta’s algorithms every day – and the job of integrating AI into real processes before the competition does.
The honest description of my role has little to do with technology. It has a lot to do with asking uncomfortable questions.
The wrong question always comes first
When a company starts to use AI seriously, the first question is usually: “Which tool do we need?” That is understandable. And almost always the wrong way round.
It sounds unspectacular. But it changes how an organisation thinks about AI: process before tool.
The first thing I did systematically at SlopeLift was a kind of inventory – but the other way around. Instead of asking what AI can do, we asked: what do we no longer want to do ourselves? Which tasks eat time from qualified people who need that time for something more important? Where does missing knowledge block the process? Where do we regularly fail at the blank page?
Out of that inventory comes what we internally call the anti-to-do list. A list of tasks that are handed over to agents before anyone thinks about new tools. It sounds unspectacular. But it changes how an organisation thinks about AI: process before tool.
What the title really means
The CAIO role emerges from a concrete necessity: AI projects need decision-making power and their own budget. They need someone who knows the operational reality of the company and at the same time understands where the technology is heading.
The actual core is this: a CAIO is responsible for making sure AI does not stay a side project. In most of the companies I observe, AI still runs exactly like that: as a pilot project in one department, as a personal hobbyhorse of one executive, as a budget add-on to some digitalisation programme. That does not scale. It fails quietly, without anyone measuring it.
Central responsibility means: decisions get made, even when they are uncomfortable. Which processes disappear? Which skills become redundant? Where does the company draw a line between automation and human judgement? Those are leadership questions. With technology as context, but leadership at the core.
What remains
In 18 years of performance marketing I have watched manual bid optimisation get replaced by Smart Bidding. Watched granular campaign structures lose relevance under Performance Max. Watched reporting work that used to eat hours get done in minutes.
Every time, the same question came up: what remains when execution becomes a commodity?
The answer is the same every time. Judgement remains. The context that no system produces on its own. The ability to explain to a client why a number is wrong, even when the model reports it as right. The decision about which processes really belong in the shredder – and which do not.
That is the work of a CAIO. Every day, in an agency with real clients and real budgets.
Technology interests me less in all this than transformation. The most interesting question is what a company is prepared to let go of.
Florian Michael Fischer is CAIO at SlopeLift, a Vienna performance marketing agency, and teaches at the DMVÖ Academy.