For years, consulting has largely been sold the same way: scope the work, estimate the effort, deliver the project, and send the invoice.

But clients do not buy consulting because they want activity. They buy it because they want progress.

They want faster growth. Lower costs. Better customer experiences. Less risk. Stronger operations. More measurable business impact.

That is why Definity is introducing a new engagement model built around outcomes.

At Definity, we have always believed that technology should serve people, not the other way around. This new model is the next evolution of that mission. It reflects a more modern idea of partnership: one where success is defined not by effort expended, but by value created.

We are redefining how we deliver outcomes together through a model that is human-led and AI-accelerated. By combining strategic thinking, decades of experience, and trust with the speed and scalability of AI agents, we help organizations create value faster and with less risk.

And increasingly, we believe pricing should reflect that reality.

Why the Industry Is Moving Beyond Effort-Based Pricing

Traditional consulting models reward effort. They bill for hours, milestones, deliverables, and project completion.

But that creates a structural mismatch.

Clients care about what has changed in the business. Providers are often paid for what they do, not for what they improve.

Outcome-based pricing aims to address that problem by aligning payments with measurable business results. Mark Stiving, PhD. describes outcome-based pricing as tying what buyers pay to the business improvements they achieve, and argues that it is the closest alignment between price and customer value. He also notes that buyers do not care about internal activity measures such as tasks performed or tokens consumed; they care about results reflected in business KPIs.

That is the heart of the shift now underway across AI, software, and services: moving away from pricing based on internal effort and toward pricing based on external impact. Recent industry analysis has echoed the same trend, describing outcome-based pricing as a growing response to customer demand for measurable ROI rather than access, seats, or usage alone.

Our Announcement: A New Engagement Model at Definity

Definity is launching a new engagement approach to better align our incentives more directly with the results our clients want to achieve.

This is more than a commercial update. It is a different philosophy of delivery founded on a unique partnership model led by humans and accelerated by AI. We combine strategic thinking, deep delivery expertise, and trusted relationships with the speed, consistency, and scalability of AI to help clients realize value faster and with less risk.

Our long-term direction is clear: create a value-tied structure where our success is increasingly aligned with our customers’.

That means less emphasis on billing for activity and more emphasis on delivering measurable improvement.

What Outcome-Based Pricing Actually Means

Outcome-based pricing is often described as the gold standard of value-based pricing, but many people use the term loosely. Stiving argues that true outcome pricing works when pricing is tied to the KPIs buyers already use to measure business progress, because those KPIs are the practical bridge between product performance and incremental profit. He distinguishes outcomes from outputs and usage, placing usage at the bottom, outputs above that, outcomes near the top, and profit at the very top.

That ladder matters.

Usage-based pricing charges for activity: hours, seats, API calls, tokens, compute.

Output-based pricing charges for work completed: tickets resolved, documents processed, records updated.

Outcome-based pricing charges closer to the business result: reduced cycle time, improved conversion, lower support cost, higher throughput, better forecast accuracy.

The closer pricing gets to business performance, the more it resembles true value-based pricing. That is why outcome-based pricing is so powerful in theory and so difficult in practice. It asks both sides to define success in business terms, not delivery terms.

Not Every “Outcome” Model Is Truly Value-Based

This is where the conversation gets more interesting.

In the market, some firms are beginning to describe their pricing as outcome-based because they defer a portion of payment until a KPI is achieved. That is directionally better than pure milestone billing, but it is not always the same thing as true value-based pricing.

If the commercial model is still fundamentally based on project cost, and only the final payment milestone has moved from “upon delivery” to “upon achieving KPI X,” then the pricing logic may still be anchored in delivery economics rather than value economics.

In other words, delaying payment is not the same as pricing based on value created.

A truly value-based model would more directly connect price to the economic result itself, such as a percentage of revenue generated, a share of savings created, or a fee derived from measurable financial improvement like time saved, cost removed, or throughput gained.

That distinction is important because outcome-based pricing, in its purest form, is not just about risk-sharing. It is about value-sharing.

Why AI Makes Outcome-Based Pricing More Practical

Outcome-based pricing has been discussed for years, but it has historically been difficult to execute. According to Stiving, the barriers were clear: software often could not measure results well enough, attribution was messy, and vendors lacked enough control over the workflow to credibly claim responsibility for outcomes. As a result, SaaS companies mostly defaulted to seats, subscriptions, and usage because those were easier to meter, even though they were weak proxies for value.

AI changes that equation.

AI systems create logs, timestamps, performance trails, and structured workflow data that make outcomes easier to observe. They also operate inside digital systems where KPIs are already measured, and they perform work more consistently than human labor, reducing the noise that makes attribution harder. Stiving’s argument is that AI does not remove every barrier, but lowers them enough that outcome pricing becomes realistic in situations where it used to be impractical.

That is especially true for agentic AI and workflow automation. When an agent resolves a case, completes a step, updates a record, or executes a process, the line between system activity and business impact becomes much clearer. The same logic can apply to optimization systems, forecasting tools, classification models, and other AI-powered workflows when they produce improvements that are clear, measurable, and attributable.

What Counts as a Real Outcome?

A real outcome is not just something the system does. It is something the business cares about.

Stiving argues that the best pricing metrics are usually not raw profit, because profit is politically sensitive and influenced by many external factors. Instead, workable outcome pricing typically lives one level lower, in the KPIs companies already use to manage performance, such as conversion rate, average handle time, cases resolved, cycle time, error rate, or forecast accuracy. These metrics matter because buyers already trust them and understand how they connect to economic value.

That idea is critical.

A good outcome metric should already matter to the buyer. It should be measurable. It should be easy for both parties to understand. And the seller must be able to influence it in a meaningful way.

Without those conditions, “outcome pricing” can quickly become a branding exercise instead of a practical commercial model.

Why This Model Requires Confidence

Outcome-based pricing works best when the seller truly believes in the performance of the solution.

“This approach only works when the provider truly stands behind the result,” said Freddy Castro, Presdient of Client Operations at Definity. “Outcome-based pricing requires confidence — confidence in the solution, confidence in the execution, and confidence in the partnership. When that confidence exists, clients gain a simpler, more trustworthy path to innovation, and vendors earn the right to share in the value they help create.”

That is why this kind of engagement structure is so powerful when done well. It signals accountability. It signals trust. And it tells the client that the provider is prepared to stand behind the business result, not just the project plan.

Why Definity Is Taking This Step

At Definity, we believe clients deserve a better alignment model.

They are not buying hours for the sake of hours. They are not investing in technology because they want more activity. They are investing because they want to solve real business problems.

Our new engagement model reflects that reality.

It is built on human leadership, strategic thinking, and delivery experience. It is accelerated by AI. And it is designed to move the commercial conversation closer to what has always mattered most: outcomes.

We are not interested in using “value-based” language loosely. We believe the future belongs to models that increasingly connect payment to measurable improvement and shared success.

That is where consulting should go.

The Future of Consulting: Price the Result, Not Just the Work

Outcome-based pricing is not appropriate for every project. Not every KPI is measurable enough. Not every environment is stable enough. Not every provider has enough influence over the result.

But when the conditions are right, it is the strongest alignment model available.

It brings pricing closer to value.

It reduces risk for buyers.

It rewards meaningful results instead of motion.

And in a market crowded with AI claims, it signals confidence in a way that traditional pricing cannot.

That is why we believe this model matters.

And that is why Definity is moving in this direction now.