Ai is dismantling the last remaining paradigm of software revenue models.
First, a quick refresher on software rev. models:
Pay for hardware, software comes free.
Pay for software per device.
Pay for SaaS per user.
Pay for internet properties with user attention.
Pay for cloud on metered usage.
With AI, I believe we are seeing early signs of the final move from software’s enterprise-revenue, to per-user-revenue and finally to per-outcome-revenue.
Outcome based, or value based, revenue models are probably going to be the hallmark of future enterprise tech providers.
Sure, the early days of AI still has per user per month revenue (ChatGPT Plus or Gemini Advanced), but when it comes to Ai applications, customers will quickly learn that outcomes (and not access) are all that matter.
In the past, when we visited a weather website, we recieved a table of temperature ranges; the user still had to figure out their own outcome from this output.
With AI, we expect “the temperature in your city is _ degrees” – Instead of a spreadsheet of data, AI provides a clear outcome.
When your user interface is a textbox or audio button, the user behaviour shifts to expecting a “answer or solution” – basically, an outcome.
Similarly, value delivery behaviour shifts from “software is a tool” to “software is a partner in my quest to better outcomes”
Of course, quantifying an “outcome” is it’s own problem statement. Customers cannot depend on “I’ll know it when I see it”.
How do you measure and define “outcomes” in a standardized way?
THAT may be the real revenue problem worth solving for AI business models.