The introduction of ChatGPT late last year sparked a surge of interest in new generative AI technologies, and today virtually every major software vendor offers solutions based on language models.
Monetizing Generative AI: A Financial Conundrum
Despite enormous enthusiasm from both technology providers and customers, no one has yet figured out how to make money from these powerful new products. In contrast, as the Wall Street Journal reports today, companies like Microsoft, Google, and OpenAI that offer generative AI capabilities to their users are believed to be losing huge amounts of money on them.
GitHub Copilot’s Struggle
For example, one of the first products of generative AI was GitHub Copilot, a service used by programmers to create, correct, and explain program code. Microsoft, which owns GitHub, says the service has more than 1.5 million users and writes about half of the code they generate.
But even with its large number of customers, GitHub has become a huge money pit, a person familiar with the numbers told the Journal. GitHub charges users $10 per month to use Copilot, but on average loses about $20 per customer.
The High Costs of Generative AI
Generative AI is an expensive technology because models can take years to train and fine-tune, and even then they require huge resources to run on a day-to-day basis. “They require enormous computing power,” said Jean-Manuel Izaret, head of the marketing, sales, and pricing practice at Boston Consulting Group. “They require enormous intelligence.”
Optimizing Generative AI Usage
Additionally, many use cases have an element of excess. For example, ChatGPT runs on OpenAI’s GPT-4 model, which is considered one of the most powerful in the world. However, many enterprise ChatGPT subscribers use it for very limited purposes. According to the publication, using GPT-4 to summarize an email is like delivering pizza in a Lamborghini.
To stop the money drain, many companies are looking to develop less powerful models to perform simpler business tasks, while others are simply planning to raise their prices. For example, Microsoft plans to charge an additional fee of about $30 per month for the AI-enabled version of its Office 365 software suite. Currently, the cheapest version of Office 365 costs about $10 per month. AI features will be able to compose emails and PowerPoint presentations, automatically generate Excel spreadsheets, and perform many other tasks.
Similarly, Google plans to ask users to pay $30 a month for generative AI features in its productivity software, where the cheapest subscription currently costs just $6, says AppTractor.
Varied Approaches to Cost Control
At the same time, other sources report that Microsoft is looking to develop less powerful models to solve the problem of redundancy. For example, the company is building small, low-cost AI models for Bing that will be dedicated only to web searches. Some of these models will reportedly be based on open source AI from companies such as Meta Platforms*.
Adobe is using a different tactic. It created a credit system for its artificial intelligence imaging tool Firefly. According to the company, if a customer uses up their monthly credits, the Firefly service will be slowed down to prevent overuse. “We’re trying to provide great value but also protect ourselves from a cost perspective,” Adobe CEO Shantanu Narayen told the publication.
Customer Dilemma: Balancing Costs and Value
The problem for Microsoft, Google, and other companies that are considering raising fees for their artificial intelligence services is that they are balancing supply and demand delicately, since not everyone thinks the software is worth paying for. “A lot of customers I talk to are unhappy with the cost of using some of these models,” said Amazon Web Services CEO Adam Selipsky.
The Future of Generative AI Profitability
So far, the challenges of monetizing generative AI have not deterred investors, who have poured billions of dollars into the most promising startups this year, notes NIX Solutions. OpenAI is discussing a stock sale that would value it at more than $90 billion, three times what it was worth at the start of the year, according to The Journal.
However, many in the industry believe it is only a matter of time before investor enthusiasm wanes. When this happens, many will begin to take a closer look at the costs of AI and how to profitably use this technology.