AI-First or AI-Fail? This is why startups fail with AI – according to an AI consultant
The big AI hype came at the end of 2022 with the launch of ChatGPT – suddenly generative AI was available to everyone.
Christian Röpke has long been intensively involved with the topic: As early as 2019, as Head of AI at the mobility startup Tier, he built the first ML applications, including fraud detection and the optimization of scooter deployments, and later coordinated the AI and data activities within the company.
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"In early-stage startups, the Head of AI is more of a tech lead, hands-on, and close to the product. Scaling becomes much more about coordination," says Röpke.
Today, as an Applied AI Consultant, he supports young startups in integrating machine learning (ML) and large language models (LLMs) into their products in a meaningful way – or building entire business models on them.
We talked to him about how this can be achieved – and when it’s better to avoid it.
For many German startups, it's clear: If you want to remain relevant in the future, you can't avoid AI . According to a survey by the digital association Bitkom, 39 percent of tech startups believe that without a clear AI strategy, companies cannot survive either technologically or in recruiting or fundraising.
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