From seats to usage: why AI is pushing SaaS toward precise billing

For years, the SaaS companies went with per-seat pricing. With this, you have to pay a set fee each month for every user. It was good when the costs did not change much. With the rise of AI-like large language models (LLMs), AI agents, and ASR systems, the costs now go up and down a lot. This is why it can be good to change prices to be or depend on how much you use something.

 

Why flat-rate pricing no longer holds

AI services use different amounts of computer power.

• LLMs make and work with tokens with every request.
• AI agents do several steps of thinking, which can make the need for computers go up.
• ASR platforms work with a lot of audio going through them.

These operations can create thousands of tokens each time, and this can lead to high costs. In some cases, it can be thousands of dollars for one request (Business Insider). When companies use these tools in many work steps, simple monthly plans are not enough to pay for big jumps in what people use.

 

The emergence of pay-as-you-go models

Many SaaS providers now use a pay-as-you-go model. This helps deal with the high cost that comes from more computer use. They charge customers based on:

• Tokens taken
• Queries started
• Sessions or talks
• Minutes of ASR use

This model matches the price with how much customers use it. Providers get their money back. Customers pay based on what they use. You can read more at JeraSoft – Telecom Billing Solutions. Some top companies like Vercel, Bolt.new, and Replit like this way too. At the same time, Monday.com and ServiceNow use mixed plans, where you pay a set fee plus extra if you use more. This helps keep things steady but still let you pick how you use it. Learn more at Business Insider.

 

The billing challenge: precision is key

Pay-as-you-go comes with some new issues. The billing now needs to show all the different ways people use AI. You might have to count things like how many tokens are used, how many ASR sessions happen, or how often agents talk with each other. If you do not measure all of this the right way:

• Providers can lose some of their money
• Customers may get bills that they did not see coming
• Disputes and problems between people can go up

 

Enter JeraSoft AI Billing: built for AI-powered SaaS monetization

Traditional billing systems do not meet the needs for the way AI services charge today. JeraSoft AI Billing is made just for this. It gives good support for AI-based pricing. There are features you get, like these:

AI Agent Monetization
– Charge for each message, session, or interaction.
– Track token use as it happens. This works well for GPT-powered sales bots, document work, or making summaries.
Token-Based LLM Billing
– Watch and bill for tokens used in different LLM APIs. This helps make sure costs line up as they should.
Detailed Cost Reporting
– See your costs and earnings for each client.
– Make pricing better with clear info.

These features help SaaS providers make money in a steady and easy way. They also let people keep a close watch and be in charge, no matter if they are working with single AI tools or mixing things. You can use credits, set levels, and have different kinds of subscriptions, even at the same time.

 

Final thought

AI is changing more than just software. It is also shaping how we make money from it. More and more, businesses need payment plans that let people pay for what they use. Tools like JeraSoft AI Billing help companies keep things fair and clear while they grow, earn, and build trust.

 

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