Editorial
The Gist
-
AI shifts value. AI is reducing the time and cost of specialized services, and it’s forcing firms to rethink how they deliver and price their work.
-
Pricing models strain. Legacy billing structures based on time spent are breaking down as AI accelerates work and blurs the line between effort and output.
-
Trust becomes key. In a world where everyone can access AI, differentiation and client trust will define which service providers endure.
The landscape of professional services is on the cusp of a radical transformation driven by AI. The exploration of a major consulting firm unveiling AI-driven commercial offerings showcases a fundamental shift. The very concept of value in professional services is under the magnifying glass.
AI’s ability to automate what once were highly specialized tasks is drastically reducing the time and effort required to deliver actionable outcomes. This reduction is forcing consultancies, agencies and system integrators to rethink their operational and commercial models. While AI’s impact will profoundly affect all industries, professional services are on the front lines.
How Professional Services Took Shape
Let's review the history of professional services so we can understand their value proposition and monetization strategies. In early societies, blacksmiths, cobblers, tailors and artisans were generally paid by the goods they produced. The shoemaker priced their shoes on a cost-plus model, and they factored in time, materials, skills and a margin. Transaction and value generation were straightforward and understood by both parties. Better shoemakers could add a premium value to their better shoes.
As societies grew more complex, a new class of “‘artisans” emerged, those who didn’t make things but knew things. These people included scribes, advisors, architects, accountants and doctors, among others. The “asset” was no longer physical; it was intangible, tougher to measure and harder to understand for the buying party. It was a service. People paid because they knew that the doctor or scribe would solve a problem. Most of these services were provided by individuals.
Then, the Industrial Revolution arrived and changed the landscape. The advent of factories meant that shoes were no longer created by an individual shoemaker but by a shoe factory. Transactions were no longer between individuals but between enterprises and individuals. Products and services started to become untangled from inputs. Organizations began delivering services by accumulating a shared body of knowledge rather than relying on individual professionals. Large medical, financial, advertising and advisory service providers appeared.
Key Shifts in Professional Services Pricing Models
As AI and automation evolve, traditional service pricing models are under scrutiny. This table outlines the evolution and tensions in pricing frameworks across eras.
| Era | Pricing Model | Defining Trait |
|---|---|---|
| Pre-Industrial | Cost-Plus / Per Unit | Tangible goods priced on time, skill and material |
| Industrial | Time-Based (Hourly) | Linear relationship between time and output |
| Digital Era | Time-Based + Retainers | Time disconnected from value; knowledge work hard to quantify |
| AI Era | Hybrid / Value-Based | Outputs faster, cheaper—pricing must reflect expertise, not just time |
Why Time-Based Pricing Took Hold
This model required standardized solutions to scale, and the science of management arose and thrived. Frederick Taylor's work, for example, applied scientific principles to system optimization. Workers were paid by the hour because there was a linear relationship between the hours spent and the output generated. If a worker produced one pair of shoes per hour, it meant that in 10 hours, they would generate 10 shoes. Then the production line came in, which focused on consistency. The worker's value became attached to their contribution to an outcome, although the precise relationship of how became indirect.
In the post-war years, a new boom of service professionals arose. It was the boom of consultancies, agencies and knowledge workers. It was the MBA golden era. Clients and buyers were no longer individuals; they were enterprises seeking services from other enterprises.
Large corporations could not focus their efforts on complex, abstract, expensive skills outside their spaces, so they outsourced those. They “rented” that knowledge so it could be applied to their specific needs. The outsourced companies provided services that solved complex problems, managed risk and provided expert guidance in particular fields.
Clients paid for consultancy in the whole meaning of the term, since building or hiring that capability internally would have been too expensive. Not only did the input become even more blurry, but the outcome did as well. Yet, the billing model from the linear factory era persisted. This was partly due to an existing body of research supporting this model, but mostly it persisted because it was simpler. Set a rate, add monthly hours, multiply and charge.
Digital Work Blurred the Line
The digital era brought an enormous number of new services and service professionals to the equation, as well as accompanying providers like software developers, web designers, digital marketers, system integrators, online advertisers and influencers. Large-scale automation thrived, and the correlation of time and outcome became even blurrier. A star developer might solve a complex bug in one day, or a mid-capable developer could work on a meaningless task for a month. Still, the second would be more expensive, although the first delivered more value. But the system was so rooted that it was hard to change. From procurement to delivery, everyone understood the process.
And then came AI. Suddenly, a lot of the work attributed to experienced, expensive-to-train knowledge workers is becoming commoditized. The barrier to acquiring specialized knowledge is being lowered. AI generates outputs quicker and in many cases better than humans, in a very cheap way. What once took hours for a designer to create (i.e., variations of an image) can now be generated in seconds, completed with rapid iterations and improvements.
Charging for a designer’s time by the hour doesn’t make sense anymore. Why would I pay you for your human designer when I can generate those assets myself? Well, not quite. You still need a capable designer, developer or marketer, but from a different perspective.
Related Article: AI in Customer Experience Works Best With a Human Heart
Outcome-Based Pricing Isn’t So Simple
But why have we made things so complex in the past decades? Wouldn't it be easier to charge by the outcome? Wouldn’t it be better to buy a specific number of designs, pay for a completed website or e-commerce store, or invest in a successful marketing campaign?
Well, yes, but only if you understand what the output is and what it takes to achieve it. Yes, you could pay a lawyer to win a case, a systems integrator to develop your platform and a marketer to run your campaign, rather than pay them for their hours. The problem is that there is uncertainty about what it will take to get there. It’s also uncertain if the outcome is ever going to happen or change.
Agile methods have gained popularity because they handle uncertainty well, especially when project scopes shift or evolve. And broader market dynamics have driven change, as well. Just take a look at the transformation in the pricing strategy for digital products. Ten years ago, nobody offered software subscriptions and software was sold through perpetual licenses, often bundled with limited support and upgrades. Today, almost no one uses that model anymore.
Professional services are going to undergo a transformation of similar magnitude, for both providers and buyers. Companies have started to request lower times and prices for service providers, and for good reasons. AI is automating and augmenting a large percentage of efforts in creative design, software development, copywriting, strategy and even drug creation.
However, this comes with a price. AI is still a tool, and like any tool, it doesn’t deliver good results if an expert doesn’t use it. This is a key concept to understand. AI will not replace designers, developers, scientists or copywriters. It will shift their time into more valuable tasks. And, yes, that service is still going to be provided by expert agencies.
The New Role of Human Experts
The challenge, though, is how to price it. Professional services providers built their empires on knowledge scarcity, and AI is making expertise cheap and accessible. But still, you need those experts. It can be hard to see with all the AI noise around, but AI automation makes human expertise more valuable, not less.
The ideal case would be outcome-based pricing, but in the services sphere, that’s very hard to achieve. The expected outcomes and expected investments in terms of time and resources are generally not well understood at the beginning. As AI changes how quickly services can be delivered or products can be built, it is forcing a new conversation about value and pricing.
Four Forces Driving Change in Professional Services
These four dynamics are reshaping how service providers define value, manage risk, and build trust in an AI-augmented world.
| Force | Impact | Strategic Implication |
|---|---|---|
| Risk Allocation | Shifts based on billing model (hourly vs. fixed fee) | Requires shared accountability in new pricing structures |
| Information Asymmetry | AI lowers knowledge barriers for buyers | Pushes providers to be transparent and value-driven |
| Differentiation | AI erodes competitive advantage of common tasks | Providers must develop unique offerings, not just efficiency |
| Trust | Buyers seek relationships they can count on in an AI-saturated space | Trust becomes a primary driver of long-term value |
Pressures Reshaping the Professional Services Industry
Four critical dynamics are going to shape this transition. These dynamics are risk, information asymmetry, differentiation and trust. In a traditional time and materials approach, the risk is on the client, as the cost is certain, but the outcome is not. In a conventional turnkey or fixed-fee arrangement, the risk is on the provider as the cost is uncertain, but the outcome is.
AI has also transformed information asymmetry, as buyers want to better understand how services are being offered. There is going to be a greater push for transparency (i.e., what was AI-generated and what was not). Scarcity and differentiation of the service will be crucial. The rarer the expertise, the more likely clients are to pay to access it.
Agencies will have to ask themselves an important question. Given that AI is accessible to everybody, how can we, as a provider, come up with something unique and valuable?
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
Sep
25
Call Spoofing Trends Financial Institutions Can't Afford to Ignore
Don't let robocalls sabotage your customer relationships. Learn how to secure your voice channel.
Register
Webinar
Oct
16
Agentic AI Playbook: Real-World Customer Service Use Cases You Can Deploy Now
Boost self-service by 30% and slash call volume by 63% with agentic AI.
Register
Webinar
Oct
22
Beyond Storage: Smarter Content, Bigger Impact with DAM + AI
Discover how the DAM + AI duo makes content smarter, stronger and more accessible.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
CX Reality Check: What Your Customers Are Really Thinking
Register now and get the insights you need to not just meet rising expectations, but exceed them.
Watch Now
Finally, let’s talk about trust. The trust economy is going to be more relevant than ever, as providers know that everybody has access to AI. Still, not everybody will be able to make the most out of it, and they will value the relationships that they trust will bring solutions.
Related Article: Customer Trust: The Backbone of Digital Age
What Comes After the Hourly Rate
This brings us to value-based pricing. It has been tested before, but it will come back, as there are going to be ebbs and flows while the industry finds the new sweet spot. Service providers are going to be here for a long time but with a different type of service, and that’s a service that will be a blend of human and AI.
Humans will supervise AI and use it as an instrument. Software development, system integration, customer experience, marketing, branding, accounting and legal services will still need experts driving them. We will still need professionals, not just prompt-based outputs. But those professionals will increasingly rely on prompts as part of their work. They are still going to be expensive, but they will not be charged by the hour.
Learn how you can join our contributor community.
