The Value Economy: Why AI Winners Will Be Built on Outcomes, Not Features

For more than a decade, modern software businesses have been built around the same assumption: if you can lock customers into recurring subscriptions, growth will compound and value will take care of itself.

That assumption is breaking.

Across industries, leaders are questioning why they are paying for seats, features, and tools that may or may not deliver measurable impact. CFOs are scrutinising software spend with the same discipline once reserved for infrastructure and headcount. Teams are being asked to prove not just usage, but outcomes.

AI has accelerated this reckoning. When intelligence becomes abundant and marginal costs collapse, value no longer lives in access to tools. It lives in what those tools actually change.

This is the shift from the Subscription Economy to the Value Economy.

Why the subscription model is under pressure

The Subscription Economy optimised for predictability. Fixed fees. Seat expansion. Feature bundling. Annual contracts.

It worked when software was scarce and switching costs were high.

Today, the opposite is true. AI-native tools can be deployed in minutes. Alternatives are plentiful. And the cost of “trying something new” is close to zero. In this environment, software that cannot clearly demonstrate value becomes expendable.

Many organisations now make decisions by simply switching tools off and waiting to see who complains. Often, no one does. Not because the software was useless, but because its value was never made visible.

AI has exposed a structural flaw: most software vendors never learned how to measure, expose, or monetise the outcomes they deliver.

What do we actually mean by “value”?

Value is often considered to be subjective or hard to pin down. In practice, it is neither. Value is transformative impact. What changes because a solution exists, and how that change can be measured.

Most value falls into one or more of three categories.

1. Capability value

What becomes possible that was previously difficult, slow, or impractical?

Capability value is measured in time and effort removed. Fewer steps. Less human effort. Less machine or energy usage. Faster completion.

2. Economic value

What monetary outcomes are realised?

This includes money saved and money generated, relative to the cost of the solution. Sometimes costs fall. Sometimes organisations willingly spend more to unlock growth or speed that wasn’t previously achievable.

3. Human value

What changes for the people involved?

This includes emotional value (confidence replacing frustration, clarity replacing stress) and social value (status, reputation, belonging). These factors are often dismissed as “soft”, yet they regularly determine adoption, advocacy, and longevity.

Most successful products deliver value across all three dimensions.

From abstract value to operational reality

Understanding value is not enough. It has to be operationalised. Across the strongest businesses, the same four steps repeat.

Step 1. Identify value

Where exactly does transformation occur?

This cannot be done from a slide deck. It requires observing users in real workflows and understanding both direct and downstream effects. A small efficiency gain in one team may unlock revenue or satisfaction gains elsewhere.

Step 2. Measure value

Every dimension of value can be measured. Measurement does not mean perfect precision; it means consistent comparison.

Before-and-after analysis, controlled experiments, and with-or-without scenarios all work. In real operational studies, AI assistance has already been shown to measurably increase productivity and output in customer-facing roles. These are not anecdotes. They are observable deltas.

Step 3. Expose value

Value that is not visible might as well not exist.

Metrics should not live in quarterly reviews or bespoke reports. They need to be accessible in seconds, embedded directly in products and workflows. When a stakeholder asks “why do we use this?”, the answer should be obvious.

This is increasingly what finance leaders expect: clear, ongoing links between spend and outcomes.

Step 4. Monetise value

Only once value is identified, measured, and exposed does monetisation become strategic rather than defensive.

In the value economy, pricing moves away from cost-plus thinking and toward value capture. The core question becomes: for the value delivered, what is the customer willing to give in return? Sometimes that is money. Sometimes it is data, participation, advocacy, or commitment.

Transformers vs natives in the value economy

Not all companies are starting from the same place.

Transformers are legacy businesses adapting their models. Ryanair - Europe's Favourite Airline is a classic example. Its value exchange is explicit: low-cost travel to many destinations in return for passengers doing more. Secondary airports, rapid turnarounds, paid ancillaries. The outcome is clear, and so is the trade-off.

In software, customer support platforms such as Intercom and Zendesk have been forced to adapt just as quickly. Tools that once charged per agent are now introducing pricing tied to resolved queries as AI takes on more work. The shift is real, but many vendors have priced defensively, anchoring fees to their own costs rather than the value customers receive.

Natives are different. They were built for outcomes from day one.

Creator platforms like Substack and Patreon only earn when creators earn. Cost-reduction platforms like BILLSHARK only get paid when savings are realised. Energy platforms like OhmConnect monetise verified reductions, not access to dashboards. Marketplaces like Airbnb or Upwork only earn when transactions complete. At MarketSizer Data-Driven Decisions® we're building right in the middle of the Value Economy - with pricing not based on "signals" but on delivering qualified opportunities to sales teams that they can actually win.

In all cases, revenue follows value. If the outcome doesn’t happen, neither does the fee. This is not a pricing tactic. It is a business model choice.

Why the Value Economy compounds: the "flywheel effect"

The most powerful feature of the value economy is not pricing. It is co-creation.

The strongest platforms get better as users participate. Amazon demonstrated this early. Seller investment improved selection and price, which improved demand, which justified further investment. Every action strengthened the system.

Notion works the same way. User-created templates attract more users, who create more workflows, which improves adoption. AI accelerates this loop by learning from usage.

Intercom has made this explicit with its new Fin Flywheel. Customers train AI agents, deploy them, analyse outcomes, and continuously refine performance. Usage becomes the input.

When users, AI, and platforms are aligned around shared outcomes, growth stops being something you push. It becomes something the system generates.

Features can be copied. Flywheels built on co-created value cannot.

What the Value Economy actually means for SaaS in 2026 and beyond

The value economy is not about charging differently. It is about building differently. Designing products around outcomes. Measuring impact continuously. Exposing value clearly. And aligning incentives so that customers and platforms win together.

If the subscription economy was about predictability, the value economy is about alignment. The companies winning right now aren’t guessing. They are disciplined about value:

• They identify where real transformation happens for customers

• They measure it in concrete terms: time saved, cost removed, revenue created, confidence gained

• They expose that value continuously, inside the product, not in quarterly decks

• And only then do they monetise, pricing after the outcome is delivered, not before

Miss one of those steps and the model breaks. Measure nothing and you’re cut. Expose nothing and you’re forgotten. Monetise too early and trust evaporates.