AI Startups Are Far More Than Just ‘ChatGPT Wrappers’ — Techprenuer, Adebayo Komolafe

The rise of generative AI has sparked debates about the true value of startups leveraging large language models (LLMs). While some critics have dismissed these companies as mere “ChatGPT wrappers,” tech expert Adebayo Komolafe argues that this perspective is deeply flawed.

“Innovation doesn’t end with the invention of new technology — it thrives when businesses apply that technology to solve real-world problems,” Komolafe said.

He explained that history has shown how groundbreaking technologies often create new industries, with the biggest winners being those who innovate on top of the foundational tech — not necessarily the inventors themselves.

“Calling AI startups ‘wrappers’ is like calling Amazon an ‘internet wrapper’ or Salesforce a ‘cloud wrapper.’ The true magic happens when innovators build transformative solutions using that technology,” Komolafe noted.

Drawing a parallel with the cloud computing boom, Komolafe pointed out that when Amazon Web Services (AWS) launched in 2006, many believed infrastructure providers like Amazon, Microsoft, and Google would dominate. Instead, companies that leveraged the cloud — such as Netflix, Airbnb, and Slack — became the true success stories.

“Netflix didn’t win by building servers — they used the cloud to revolutionize content delivery. The same pattern will unfold with generative AI,” Komolafe stated.

He believes the most successful generative AI startups will not simply fine-tune existing models but will focus on solving industry-specific problems, gathering unique data, and enhancing user experiences. According to him, startups that tailor AI to sectors such as healthcare, legal services, or finance will have a stronger edge by combining AI with proprietary data and customized workflows.

“A company that integrates AI into a niche market — like architecture or fashion design — will build datasets that general-purpose models can’t match,” he explained.

Komolafe further emphasized that intuitive design will play a crucial role in ensuring AI adoption. “Users don’t care about the complexity behind AI models — they just want intuitive solutions that make their work easier,” he said, citing examples like Notion AI, which enhances team collaboration, and Runway ML, which reimagines creative workflows for video editors.

He also pointed out that startups developing vertical AI solutions — those tailored to specific industries — are better positioned to succeed. While general-purpose chatbots may be free, specialized AI tools for tasks like contract analysis or financial forecasting will command premium pricing due to their targeted value.

According to Komolafe, foundational AI companies like OpenAI, Anthropic, and Mistral will remain critical to the ecosystem, but their success will depend on the startups that build innovative solutions using their models.

“Just as AWS thrived by enabling businesses to scale, LLM providers will succeed by empowering startups to unlock AI’s full potential,” he said.

Komolafe concluded by urging investors and industry stakeholders not to underestimate the potential of AI startups.

“The internet wasn’t just about ISPs, and the cloud wasn’t just about AWS. Likewise, AI’s biggest impact will come from companies that master the art of applying it,” he said.

“The race has only just begun — and the true winners will be the startups that turn generative AI from a novelty into an indispensable tool for businesses and consumers alike.”