AI Isn’t Changing Software Buying. It’s Changing How Buyers Think About Value.

Over the last year, I have found myself in a surprising number of conversations where the question was not whether a software product was good enough.

The question was whether it needed to exist at all.

Not because the product lacked value. Not because the company had a better alternative. But because, for the first time, buyers felt they could realistically build something similar themselves.

A few years ago, this was not a serious discussion.

Today, it shows up everywhere:

• A marketing team wants to replace a workflow tool with a combination of AI and internal automations.
• An operations team questions whether a specialized SaaS subscription is worth renewing.
• A founder looks at a product that costs thousands of dollars per month and wonders whether an internal team could recreate the core functionality.

Most discussions around this trend focus on a simple question: build or buy?

I think that is the wrong question.

The more interesting change is happening much earlier in the buying process.

AI is changing how buyers assign value.

And that has implications not just for software companies, but for agencies, consultants, service businesses, and practically every knowledge-based business.

Buyers Are Deconstructing Products

Historically, software was evaluated as a complete product.

A buyer would compare vendors, review features, calculate ROI, and make a decision.

Today, buyers are increasingly breaking products into components.

Instead of evaluating the entire product, they are evaluating its ingredients:

• What part is the interface?
• What part is workflow automation?
• What part is proprietary data?
• What part is accumulated expertise?
• What part is simply a wrapper around a foundation model?

This is a subtle but important shift.

The moment buyers start deconstructing products, they stop assigning value evenly across everything the product contains.

Some components begin to look highly differentiated.

Others begin to look replaceable.

The Most Misunderstood Effect of AI

A common argument I hear is that AI will allow companies to build software internally instead of buying it.

In some cases, that is true.

But I think the larger impact is psychological.

AI has reduced the perceived complexity of software.

That is very different from reducing the actual complexity of software.

The distinction matters because buyers often experience the visible part of a product while remaining unaware of everything beneath it.

They see:

• Dashboards
• Workflows
• Interfaces
• Outputs

What they do not see are years of accumulated decisions:

• How data is structured
• How exceptions are handled
• How reliability is maintained
• How edge cases are solved
• How customer behavior has shaped the product over time

The easier it becomes to recreate the visible layer, the more important the invisible layer becomes.

Most companies have not adjusted their messaging to reflect this reality.

This Is Not Just a SaaS Story

The same pattern is emerging in services.

Take the rise of productized services and AI-enabled agencies.

On paper, many of these services appear easier than ever to replicate internally.

A company can:

• Hire creators
• Buy software
• Automate workflows
• Generate content

Yet many organizations continue to work with external specialists.

Why?

Because execution was never the entire product.

Expertise was.

The real value often sits in pattern recognition, judgment, operational maturity, and lessons learned across dozens or hundreds of previous engagements.

AI lowers the cost of execution.

It does not automatically lower the cost of experience.

That distinction is going to matter far more than most people realize.

The Product Marketing Problem Nobody Is Talking About

Most AI companies are currently competing on capability.

• Generate this.
• Automate that.
• Analyze this.
• Create that.

The problem is that capabilities are becoming increasingly temporary advantages.

The lifecycle of differentiation is shrinking.

Features that once created years of advantage can now be replicated in months, sometimes weeks.

As a result, many companies are investing heavily in product development while unintentionally weakening their positioning.

They are teaching the market to value the easiest part of what they do.

The companies that build durable positions over the next decade will likely market something very different:

• Not features
• Not automation
• Not even AI itself

They will market the knowledge embedded within their products.

• The data they have accumulated
• The decisions they have refined
• The patterns they have observed
• The outcomes they consistently improve

In other words, they will market what cannot easily be recreated.

The Question Every Company Should Be Asking

As AI continues to reduce the cost of building software, many businesses are focused on how quickly they can ship new functionality.

That matters.

But I suspect a more important question is emerging.

If someone could recreate 80% of your product in a weekend, where does the remaining 20% of your value come from?

Most companies do not have a good answer.

The ones that do will likely define the next generation of category leaders.

Because as software becomes easier to create, buyers will become increasingly selective about what they are actually paying for.

And increasingly, they will not be paying for software alone.

They will be paying for accumulated intelligence, expertise, and judgment.

The businesses that understand this shift early will have a significant advantage.

The businesses that do not may discover that the thing they believed was their moat was simply their most visible feature.