What Happens When AI Does the Work of 10 Employees but Software Companies Still Charge for 10?

Key Takeaways

• AI can decouple software revenue from employee headcount by completing work without adding human software users.
• Usage-based AI pricing can replace lost seat revenue but may create large, less predictable bills for customers.
• AI savings depend on pricing: providers may capture much of the value unless customers retain alternatives and spending controls.

What Happens When AI Does the Work of 10 Employees but Software Companies Still Charge for 10?

Imagine running a company with 10 customer service employees.

Every month, you pay for 10 software accounts so your team can answer questions, update customer records, and resolve complaints.

Then you introduce an AI agent.

It handles most routine inquiries, updates records, and responds to customers around the clock. Suddenly, perhaps only three employees need regular access to the software.

But your software provider still wants you to pay for 10 accounts.

If AI is doing the work, why are you still paying as though 10 people are doing it?

That question could challenge one of the technology industry's most successful business models. And surprisingly, the answer might make software companies even richer.

The Business Model That Made Software Companies Billions

For years, many software companies have relied on a simple formula: the more people using their products, the more money they collect.

It's called seat-based pricing. A seat generally represents one licensed user.

Imagine a software provider charging $50 per employee each month.

Illustrative figures in USD, not a specific provider's pricing.

The attraction is obvious. When customers add employees who need software access, subscription revenue can grow without the provider having to find new customers.

But AI introduces an uncomfortable possibility.

What happens when a business doubles its productivity without hiring another employee?

Or worse for the software provider, what happens when customers accomplish more work while paying for fewer accounts?

One AI Agent Handles 2,100 Customer Questions. Who Pays for That Work?

Consider a fictional online retailer receiving 3,000 customer inquiries every month.

Previously, employees handled delivery questions, refunds, and order changes through customer service software.

Now imagine the retailer introduces an AI agent capable of resolving 70% of those inquiries.

That's 2,100 inquiries handled by AI, leaving 900 for employees.

The company might still need human oversight, quality checks, and employees to manage complicated cases. Automating 70% of inquiries doesn't automatically eliminate 70% of jobs or software licenses.

But suppose the retailer can legitimately reduce its paid accounts from 10 to three.

At $50 per account, its monthly software bill falls from $500 to $150.

That's a 70% revenue decline for the software provider, assuming the contract permits the reduction and there are no additional AI charges.

The retailer is handling the same volume of customer inquiries, potentially with greater efficiency.

Yet its software provider earns less.

This exposes a weakness in traditional seat-based pricing: the amount of work completed and the number of human software users no longer have to grow together.

Software Companies Have Already Started Changing How They Charge

This isn't merely a hypothetical challenge.

Salesforce, one of the world's largest business software providers, offers multiple pricing options for its Agentforce AI technology.

Its published pricing structures include:

• $2 per conversation for certain customer-facing AI agents.
• $0.10 per standard action under its Flex Credits model, based on 20 credits per action.
• Per-user subscriptions and AI-related licensing for employee-facing applications.

These are different billing arrangements with specific conditions, not interchangeable prices. The figures are in US dollars.

Microsoft also offers per-user Copilot subscriptions alongside consumption-based pricing for certain AI agents through Copilot Credits.

The shift is significant.

Instead of earning money only when another employee receives a software account, providers can increasingly charge when AI performs billable activities.

The subscription isn't necessarily disappearing. It's getting a new companion: a meter that measures automated work.

And that meter could change who pays the biggest software bills.

What If Three Employees Generate a Bigger Bill Than 30?

Imagine two businesses using the same AI customer service platform.

Company A has 30 employees and handles 1,000 customer inquiries monthly.

Company B has just three employees but handles 20,000 inquiries through extensive automation.

Under traditional employee-based pricing, Company A could pay more because it has more licensed users.

Under usage-based pricing, Company B could pay considerably more because its system processes far more activity.

Which company should pay the larger bill?

For software providers, charging for usage creates opportunities to earn revenue as automation expands.

For customers, it can connect spending more closely to actual activity.

But there's a catch.

An AI agent doesn't need a coffee break, and neither does its billing meter.

Suppose a business pays $0.10 per billable action and its AI agents perform 100,000 such actions monthly.

That's a $10,000 bill.

One customer request might involve several billable actions, and different providers measure usage differently. Real charges depend on the pricing plan, credit rules, and applicable limits.

Suddenly, a business that celebrated saving money through automation might find itself worrying about an entirely different expense.

That's why spending caps, usage alerts, and predictable pricing matter.

The $5,000 Question: Who Actually Keeps the AI Savings?

Here's where the business story becomes particularly interesting.

Imagine a retailer introduces AI automation and saves $5,000 every month in operating costs.

Its software provider then charges an additional $1,000 monthly for AI usage.

Assuming those are the only relevant cost changes, the retailer still saves $4,000.

The software provider collects another $1,000.

Both sides could benefit.

But what happens if the provider charges $4,500 instead?

The retailer keeps only $500 of its original savings, while the software company captures most of the financial benefit.

The same AI technology could therefore produce very different outcomes depending on pricing, competition, and the customer's alternatives.

This raises a bigger question than whether AI will replace software subscriptions.

When AI makes work cheaper, who gets to keep the savings?

The customer buying the technology, or the company selling it?

The answer could help determine which software businesses become more valuable in an AI-driven economy.

Could AI Make Software Companies More Profitable?

Absolutely possible, but not guaranteed.

Consider a software customer previously paying $500 monthly for 10 employee accounts.

After introducing AI, it keeps three accounts costing $150 and pays another $700 for AI usage.

Its new monthly bill is $850.

That's a 70% revenue increase for the software provider, despite a 70% reduction in human licenses.

The customer could still come out ahead if automation saves more than the additional technology spending.

But revenue isn't profit.

AI processing, infrastructure, integration, security, and customer support all cost money. A provider might collect more revenue while earning a smaller profit margin.

For investors, that distinction matters.

A software company announcing rapid AI revenue growth isn't necessarily becoming more profitable at the same pace.

The real test is whether revenue from automation exceeds both the lost subscription revenue and the additional cost of delivering AI services.

Will Monthly Software Subscriptions Eventually Disappear?

Probably not.

Businesses still need people to approve decisions, manage sensitive information, collaborate, and supervise automated systems.

Fixed subscriptions also provide something valuable: predictable expenses.

The more likely outcome is a combination of three pricing approaches.

Outcome-based pricing is especially interesting.

Imagine paying an AI provider only when a customer's problem is successfully resolved.

That sounds appealing, but what counts as a successful resolution? What if the customer contacts support again tomorrow? Who is responsible when the AI provides an incorrect answer?

Those questions make outcome-based billing harder to implement than it first appears.

For many businesses, hybrid pricing may be more practical: a predictable subscription combined with additional charges for AI activity.

The Next Software Giant Might Not Need Millions of Human Users

For decades, many seat-based software businesses benefited when customers added more licensed employees.

AI could weaken that relationship.

A company with 20 employees might eventually accomplish work that previously required a much larger team, although automation doesn't guarantee equivalent job losses or eliminate the need for human judgment.

For software providers, the challenge is earning a fair share of the value created by automation without making customer bills unpredictable.

For customers, it's ensuring that the financial benefits of AI don't simply disappear into higher software charges.

And for investors evaluating the next generation of software companies, one question could become increasingly important:

Is this business making money because customers need more employees, or because customers are getting more work done?

Those are two very different business models.

The biggest winner may not be the software company with the most paid users.

It may be the one that figures out how to get paid when the work gets done—even when no human clicks a button.

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Sources

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• Subscription vs Usage-Based Pricing: Which Model Works Better for Startups?
• The Capital Efficiency Paradox: Why More Startup Funding Isn't Always Better