The leading AI startups and Big Tech incumbents are striving to make massive technological strides, but they still have an open question to answer: Can they actually make money?
What’s the business model for AI?
The Big Tech outlook: The largest technology companies — such as Amazon, Apple, Google, Meta, and Microsoft — are all-in on artificial intelligence. Many of them have their own large language models, such as Google’s Gemini 1.5 Pro and Meta’s open-source Llama 3. For these companies, betting on AI is one of many bets: Google is still a search engine and an advertising company, Meta is still a social media giant, but they’re betting that they can make strides in developing this breakthrough technology. Depending on how you look at it, these AI plays are either loss leaders or long-term investments to keep these companies on the cutting edge and boost their existing product lines.
And what the Silicon Valley giants can’t do themselves, they’re happy to outsource to specialized startups. For example, Amazon invested $8 billion into Anthropic, and Microsoft poured $13 billion into OpenAI. While Microsoft develops its own AI models, it has also integrated OpenAI into its Copilot assistant across its enterprise suite of products.
The startups: But without other products to cross-subsidize their ambitions, the smaller pure-play AI startups are left hunting for rock-solid business models.
OpenAI, which makes ChatGPT, lets users test out the chatbot for free but sells subscriptions for their most advanced tools and higher usage rates for $20 a month. The company also sells enterprise subscriptions to companies — reportedly about $60 per user each month for companies with 150 employees or more, which comes out to $108,000 per year for a company of that size. And it’s found some success with more than 1 million paid users of the enterprise version of ChatGPT — about $720 million in revenue. Other AI startups, such as Anthropic (which makes Claude), the search engine Perplexity, the image generator Midjourney, and the music generator Suno, have similar freemium models with bigger checks coming from business-to-business sales.
“The real money will be in business-to-business AI solutions provided they’re carefully deployed securely — something that the likes of Salesforce and Microsoft are promising,” said Gadjo Sevilla, senior analyst at the market research firm eMarketer. “This is easy for companies with large captive user bases since AI features will be an incremental cost to existing services and are also scalable across enterprises.”
The open-sourcers: While most AI companies have proprietary (or closed-source) models, a few have opted for open-source development, whereby they publish their code for free for developers to use and adapt it. Stability AI, which makes the open-source image generator Stable Diffusion, lets people use its model for free but charges companies that make $1 million or more in annual revenue for commercial licenses and support. That’s a monetization strategy that Meta could pursue in the future for its currently free and open-source Llama models.
The government option: AI companies have a third source of revenue beyond consumers and businesses: governments. OpenAI has secured contracts with US government agencies and public institutions as varied as NASA, the National Gallery of Art, the IRS, and Los Alamos National Laboratory, according to FedScoop. Microsoft, meanwhile, has AI deals with both the US and UK governments. And specialized firms like Palantir and Anduril have capitalized on US defense contracts with their AI technology for battlefields.
Running at a loss
OpenAI is currently valued at $157 billion, but the company behind the ChatGPT chatbot is still losing money. In September, the New York Times reported that OpenAI expects to make $3.7 billion in 2024, but it’s set to spend $5 billion in the process — a net loss of $1.3 billion.
The company’s internal projections estimate that revenues will hit $11.6 billion in 2025, but it will need to keep its costs — on training its models, running its services, and paying employees — stable to turn a profit. Meanwhile, Anthropic is reportedly burning through $2.7 billion this year. These companies’ top costs are computing infrastructure such as servers and chips, staffing with top talent, and the cost of offering free services to casual users.
To become profitable, these companies must lower costs, raise prices, or develop in-house capabilities like chips and data centers to reduce reliance on paying other firms.
Playing the long game
Perhaps AI startups need to think like the tech giants and play the long game. After all, these many billions of dollars in funding should give them some runway.
Sevilla said that OpenAI is headed in the right direction. “OpenAI shifting from nonprofit think tank to a for-profit AI innovator now behooves the company to generate sustainable profits,” he said, referring to the company’s recent change in ownership structure. “It’s challenging Google in search and browsers, it's trying to make inroads into education, and there's a good chance it will develop its own hardware to reduce reliance on Nvidia. Any of these areas can generate profits, but it could take time.”
Dev Saxena, director of Eurasia Group’s geo-technology practice, said the real value lies in building platforms that other companies will use to develop their own AI applications — “the same way that the internet unleashed so much entrepreneurialism and innovation."
In other words: The winners of the AI race might not be the companies with the most advanced AI but those who build the infrastructure and platforms other businesses need — and those who find a way to make money doing it.
