A new report published by the Wall Street Journal looks into the issue of businesses profiting from AI. The thorny issue is simple, with the big hitters of tech like Microsoft, Alphabet, Adobe, and AWS spending a lot on AI, but customers are currently not paying enough for profits to be made.
In our startling headlining example, an insider told the WSJ that Microsoft used AI from its partner OpenAI to launch GitHub Copilot at $10 per month, but was losing >$20 per user per month on average in early 2023. Some Copilot users were even costing Microsoft as much as $80 per month.
It is well established that AI is a resource hog. Its proponents seem willing to invest in large quantities of expensive hardware, invest in associated software development, and run up power (and water) bills with abandon. As well as the large compute and data resources required to get an AI up and running, it must be maintained, upgraded, and serviced for competitive availability. But when will the returns on these big investments come?
Microsoft’s GitHub Copilot revenue-to-cost ratio doesn’t seem sustainable. We have previously seen companies like Microsoft absorb such costs early in a product development cycle to build a market, but the WSJ report indicates changes are already on their way.
Companies working to provide AI services will be striving for profit by attacking the cost problem from multiple angles. The source report suggests both Microsoft and Google intend to increase prices for AI-backed software and services. Multiple pricing tiers and more restricted AI access levels are being considered. Specifically, Microsoft and Google will charge $30 on top of their regular workplace software suite subscriptions for access to AI enhancements, it is claimed.
It doesn’t have to be all-or-nothing with AI if a provider wants to reins in costs. A good example of the rationing of AI is provided by Adobe, which uses a monthly credits system for access to its Firefly AI image generator.
To cut costs, companies are also looking at less powerful and cheaper AI tools, where they are good enough to get the job done. A relevant example here is to make use of ChatGPT 3.5 AI instead of the latest GPT-4, when it is adequate.
Another way to cut the price of AI provision comes from the hardware side. It is known that some AI businesses are interested in making lower-power, cheaper, and more efficient processors to take on AI workloads.
AI to Get a ‘Cold Shower in 2024’
With all the above considered it isn’t surprising that investors are starting to view AI investments with more caution. A report published by CNBC today focuses closely on this concern. It says that generative AI is set for a “cold shower in 2024,” as the buzz dies and a reality check comes - with eyes on business features like development and running costs, risks and regulations.
