If you want to raise money, call yourself an AI company

Median funding round for an AI start-up is about 15% higher than for other software companies - research

Artificial intelligence companies raise larger amounts of investment than non-AI companies, according to new research.

Companies that call themselves AI businesses have raised larger funding rounds and secured higher valuations than other software businesses.

The median funding round for an AI start-up last year was about 15 per cent higher than for a software start-up, says investment firm MMC Ventures in its new report. The difference exists across all stages of maturity, from seed stage through Series A, B and C funding.

Globally, venture capital investment in early stage AI companies has increased 15-fold in five years, while the number of investable prospects still remains limited.

Today, one in 12 new start-ups in Europe calls itself an AI-led startup.

MMC Ventures says this is partly due to an imbalance in the availability of capital and demand. Many venture capitalists wish to invest in AI but there are relatively few AI companies in which to invest.

And there are structural differences as well: an AI company can justify greater investment, given the longer cycles required to achieve develop a minimum viable product, the high cost of AI talent, and the larger teams required for complex deployments.

David Kelner, MMC’s head of research, told the Financial Times that venture capitalists in Europe respond to companies which claim to be raising money for AI.

However, MMC discovered that 40 per cent of Europe’s so-called artificial intelligence start-ups are in fact no such thing.

Based on public information and interviews with executives, four in ten of Europe’s “AI” start-ups do not use any AI programs in their products.

Ophelia Brown, a partner at Blossom Capital, which last week raised £65m Series A fund to invest in European tech startups, said that many AI start-ups hype up the claims of what they’re actually building.

“There are different levels of sophistication when it comes to building these algorithms,” she said.