AI Is in Its Awkward Era - Companies on this year's Inc. 5000 detail their growing pains, as investors expand their understanding of AI beyond chatbots and generative art.

For AI entrepreneurs, the enthusiasm is doubleedged. Interest in their tools has never been greater, as nearly half of the Inc. 5000 honorees who took our CEO Survey (see page 49) cite the use of at least one AI service. OpenAI was the top provider. But genAI hype has also led to misconceptions about what these tools actually do. As AI zips to the top of investors' portfolios, founders say the biggest factor limiting their growth isn't fundraising; it's overcoming a towering knowledge gap.

- By Ben Sherry

Artificial intelligence entered its adolescence last year, as evidenced by one hell of a growth spurt. Investors piled on in 2023 as companies across industries looked to hop on the AI train. In the U.S., investment in the sector grew to $67.2 billion, with a third going directly to makers of generative AI products, the technology popularized by OpenAI's ChatGPT. According to Stanford University's 2024 AI Index Report, genAI investment jumped to more than $20 billion, up from the $2.21 billion invested in 2022.

For AI entrepreneurs, the enthusiasm is doubleedged. Interest in their tools has never been greater, as nearly half of the Inc. 5000 honorees who took our CEO Survey (see page 49) cite the use of at least one AI service. OpenAI was the top provider. But genAI hype has also led to misconceptions about what these tools actually do. As AI zips to the top of investors' portfolios, founders say the biggest factor limiting their growth isn't fundraising; it's overcoming a towering knowledge gap.

Benjamin Plummer understands this implicitly. He's the CEO of Invisible Technologies (No. 152), a San Francisco-based software and data services provider. Invisible helps clients such as Microsoft and Cohere create high-quality data to train their AI models. To do so, Invisible uses a roster of more than 5,000 contractors, all experts in their fields, who help fine-tune or stress test different models.

"You might have a health care company training a chatbot that needs 100 doctors to test and evaluate the model," explains Plummer, 38. By creating complex workflows with multiple experts testing and grading models, richer training data is collected. Plummer says helping organizations like OpenAI-a client since before the launch of ChatGPT-train models has been a "huge part of our growth over the past year."