For years, businesses have solved technology problems the same way: find software that does the job and pay for it every month.

Need a CRM, project management platform, reporting tool, automation system, analytics dashboard, or customer service solution? There is probably a subscription for it.

Artificial intelligence is starting to challenge that model.

As AI agents become capable of completing work across multiple systems and AI coding tools make custom software easier to create, businesses have a new option. Instead of automatically asking which platform they should buy, they can increasingly ask: Do we need another piece of software at all?

That question could have enormous consequences for the software-as-a-service industry. As much as $234 billion in enterprise application software spending could be at risk from agentic AI by 2030, while 32 percent of organizations have already decided against purchasing at least one software product or feature because they could build the functionality internally.

For businesses, this creates an opportunity to rethink something that has quietly become one of the most complicated parts of running a modern company: the technology stack.

Businesses Have Spent Years Adding Software

SaaS made sophisticated technology accessible to almost every company. Businesses no longer needed to build expensive custom systems for every problem. They could purchase a subscription, create accounts, and get to work.

That created enormous value, but it also created software sprawl.

A company may have one platform for sales, another for marketing, another for project management, another for customer service, and several smaller tools handling reports, integrations, meetings, approvals, and automation.

Each subscription can seem reasonable on its own. The problem becomes clearer when businesses look at the entire stack.

Employees jump between systems, data gets duplicated, integrations break, licenses go unused, and companies pay for overlapping capabilities simply because those tools have become part of the routine.

AI could make businesses much less tolerant of that complexity.

AI Agents Could Change How Employees Use Software

One of the biggest changes happening with AI is that employees may not need to interact directly with every platform involved in their work.

An AI agent could retrieve information from one system, update another, analyze data from a third, prepare a response, and complete a workflow without an employee manually moving between every application.

Consider a salesperson preparing for a customer meeting. Today, they might open the CRM, review previous emails, check meeting notes, research the company, and pull information from several other platforms before preparing a briefing.

An AI agent could increasingly handle much of that work.

The underlying software still matters because it contains the information, but the employee may no longer need to actively use every interface. AI agents operating across applications could therefore change where businesses see value in their technology stack.

Instead of paying primarily for access to an interface, companies may increasingly care about the data, capabilities, and outcomes underneath it.

The Per-User Pricing Model Could Come Under Pressure

Many SaaS companies have built their businesses around a simple idea: more users mean more licenses.

If 20 employees need a platform, the company buys 20 seats. If the team grows to 50, the business pays for 30 more.

AI complicates that relationship.

If an AI agent can complete work inside a platform on behalf of multiple employees, businesses may start questioning why every person needs an individual license.

This could weaken traditional SaaS pricing, particularly for platforms where employees only need access because a workflow currently requires them to log in.

That does not mean every software company loses its business model. It means businesses may become much more selective about what they are actually paying for.

Are they paying for critical infrastructure and proprietary data, or are they paying because an employee needs another dashboard to complete a task?

AI could make that distinction much easier to see.

Not Every Software Platform Is Going Away

AI is not about to eliminate every SaaS platform.

Businesses still need secure systems that store customer records, financial information, operational data, employee information, and other critical business information.

A CRM may remain extremely valuable even if employees interact with it differently. An ERP system does not stop being important because an AI assistant can retrieve information from it.

Core business platforms are likely to remain especially important because of their integration depth, security, auditability, and role as systems of record.

The greater pressure may fall on smaller platforms whose main purpose is completing a narrow workflow.

If a tool primarily moves information between systems, generates routine reports, summarizes data, or provides another interface over information already stored somewhere else, AI may offer businesses another way to accomplish the same outcome.

AI Is Changing the Build Versus Buy Decision

Historically, most businesses purchased software because building it themselves was expensive and complicated.

Custom software could require developers, months of work, significant budgets, testing, maintenance, and ongoing technical support. Buying an existing platform was usually the easier decision.

AI coding tools are changing that calculation.

Developers can now use AI to accelerate coding, troubleshooting, integrations, documentation, and application development. Even nontechnical teams can increasingly create basic tools using AI-assisted and low-code platforms.

That shift is already affecting purchasing decisions. Nearly one-third of organizations have already passed on at least one software purchase because they could build the functionality internally.

That does not mean every business should start developing its own software. It does mean companies have more options than they did a few years ago.

A specialized platform costing tens of thousands of dollars annually may deserve another look if AI makes it dramatically easier to recreate the few functions the company actually uses.

The Best Option May Be a Combination

Businesses should also avoid assuming the future is simply build or buy.

A company could keep its CRM as its primary system while using AI to retrieve information, update records, summarize opportunities, and coordinate activity across other tools.

It could retain large enterprise platforms while replacing some of the smaller applications around them.

Companies may also use AI layers over existing systems, keeping the technology that reliably stores their data while changing how employees interact with it.

That may be much more realistic than replacing entire software stacks.

The platforms stay. The workflows change.

Before You Cancel Anything, Look at the Real Cost

Building something with AI can feel surprisingly easy. Maintaining it is a different question.

A working prototype is not the same thing as reliable business software.

Companies need to consider who will maintain an internal tool, how security will be managed, where data will live, what happens when integrations change, how the system will be documented, and what happens if the person who created it leaves.

There is also a risk that companies simply replace SaaS sprawl with AI sprawl.

Having 50 undocumented internal AI tools that nobody fully understands is not necessarily better than having 50 subscriptions.

The objective should not be to replace software simply because AI makes it possible.

The objective should be to build a simpler, more effective technology stack.

Your Next Software Renewal Should Look Different

The next time a major software contract comes up for renewal, businesses should ask more than whether employees are still using it.

They should ask what business outcome the platform actually provides.

Which capabilities are genuinely valuable? Which features are employees actually using? Could an AI agent complete part of the workflow using systems the business already owns? Could the number of licenses be reduced? Could several tools be consolidated?

Most importantly, ask this:

If we were designing this process from scratch today, would we buy the same software?

Businesses frequently keep technology because replacing it feels harder than continuing to pay for it.

AI is creating more alternatives, which means old purchasing decisions deserve another look.

The Biggest AI Opportunity Might Be Subtraction

Most conversations about AI begin with what businesses should add.

What new platform should we buy? What new agent should we build? What new automation should we introduce?

The more interesting opportunity may be subtraction.

Which manual steps no longer need to exist? Which workflows can be simplified? Which platforms duplicate functionality? Which subscriptions solve problems that AI can now handle another way?

The companies that benefit most from AI may not end up with the largest technology stacks.

They may end up with smaller, more connected, more intelligent ones.

Instead of simply asking “What AI tool should we buy next?”, businesses should start asking a second question:

“What technology might AI mean we no longer need?”

That could become one of the most valuable AI questions a company asks.

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