Business Models for Generative AI?

As much as we presently struggle to define revenue models for generative AI or perhaps AI in a broader sense, past experience with major technology transitions provides a way of envisioning the possible adaptations. Consider whether generative AI is more like a "spreadsheet" or more akin to the internet.

The spreadsheet was invented in the 1970s and quickly became an essential tool for businesses of all sizes. It allowed businesses to store, organize, and analyze data in a way that was never before possible. This led to better decision-making, increased efficiency, and reduced costs, and also provided the rationale for buying personal computers. 

At a high level, generative AI might be the use case that spurs adoption of new or additional computing capabilities. 

Compare that to the internet, which eliminates distance and geography as key business constraints; virtualizes many formerly-physical processes and changes production costs (as for media, content, messaging, document exchange, voice communications, conferencing, retailing, advertising, teaching). 

Virtually all of us would consider the internet a bigger overall innovation than was the spreadsheet. 

The analogy one chooses will hint at degree of impact. 

Also, much of the direct new activity will be in “picks and shovels;” enabling infrastructure to support AI, such as computation, storage, advice and tech support, the creation of language models and generation of inferences will be direct revenue models. 

But most of the impact will be indirect, as was the impact of computing itself in the mainframe, minicomputer, personal computer, client-server, internet and mobile evolutions of computing. 

Infra suppliers (hardware, software and services) will create revenue enabling generative AI. But most entities will apply generative AI in their existing businesses, with mostly-indirect outcomes. Generative AI will be a means, not an end. 

Still, there might also be new lines of business created in the application and use case areas, as we have seen with cloud computing, e-commerce, search, social media and content streaming, all the result of the existence of the internet. As was the case for those innovations, we might not be able to predict their emergence or their revenue models. 

Generally speaking, for most industries the impact is likely to resemble the impact of spreadsheets (richer analysis, lower-cost customer service, faster modeling) more than the impact of internet disaggregation (products become services, death of distance). 

Pre-Internet Revenue Model	Internet Revenue Model
Hardware sales	Cloud computing
Software licenses	Software as a service (SaaS)
Maintenance and support contracts	Infrastructure as a service (IaaS)
Advertising	Technology supported by advertising (Google search, Facebook social media)
Subscription	Video streaming, content apps that displace newspapers, magazines, music streaming
Transaction	E-commerce
Affiliate marketing	Online travel agencies, price comparison websites
Leasing	Cloud computing
Concessions	Online gaming
Sponsorship	Esports

So most of the revenue models will fall within an existing range: usage fees, subscriptions, licenses, advertising, product sales, product leasing, advice, instruction, tech support and so forth. 

Technology	Revenue Model
Computing	Infrastructure gear and services sales, indirect support of advertising, commerce
Cloud computing	Infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS)
Mobile access	Mobile data plans, mobile advertising
Broadband	Broadband internet access fees