Why Professional Services Model Is Holding Back SaaS Platforms

There was a time when professional services were essential to SaaS success. In the early days, when cloud software was still new and IT teams were still skeptical, professional services helped bridge the gap. Implementation consultants got platforms up and running. Integration teams connected systems. Training sessions turned users into power users. These services made the difference between a churned deal and a sticky account.

But that was then. Today, as SaaS platforms scale across segments and geographies, the same professional services model that once enabled growth is increasingly getting in the way of it.

SaaS Professional Services: A Model That Doesn’t Scale

Professional services aren’t inherently bad. They help customers, they reduce risk and often generate short-term revenue. Most enterprise‑focused SaaS companies still derive 8-10% of revenue from professional services, highlighting how entrenched the PS model remains, even as it strains growth potential. But structurally, PS are at odds with the SaaS model.

Services revenue is non-recurring. Every project requires people, margins are slim, and every new engagement adds operational drag. As recurring revenue compounds, services revenue plateaus, and begins to dilute the business.

For small customers, the model breaks quickly. Most SMBs won’t pay for onboarding packages or custom integrations. And even when they would, the economics don’t work for the vendor. As a result, too many “no-touch” customers left to figure things out alone, and too many accounts never reach full adoption.

For enterprise customers, the problem is more subtle. High-value deals get attention. But the long tail of customization requests such as small changes, region-specific workflows, edge-case integrations, often pile up in a backlog no one wants to own. They’re too specific for the product team, too low-value for services, and too annoying for customer success.

Professional Services Automation: A Quiet Shift Among Category Leaders

Some platforms have started breaking this pattern, not by eliminating services, but by shifting the delivery model entirely.

Slack is a powerful example. With Workflow Builder, Slack made it possible for non-technical users to automate approvals, onboarding, and handoffs directly inside the product. No devs or PS teams are required, but just in-product logic that users could own.

Then Slack took it a step further. With the launch of AI-generated workflows, users can describe what they want in plain language and the platform builds the automation for them. What used to require a scoped project and a consultant now happens in minutes, with no vendor involvement.

Salesforce took a more platform-led approach. With Flow, it introduced an engine for building logic across objects, apps, and systems. Today, Flow is embedded across the Salesforce ecosystem and powered by Einstein to suggest and even generate automations based on user intent. Admins can now create what used to be considered “custom development” without writing a single line of code.

Twilio followed a similar path with Studio, a visual builder for customer communications. Instead of hiring developers to script phone trees, chatbots, or notification systems, teams could drag and drop their way to automated flows across SMS, voice, and WhatsApp. For the first time, non-technical users could design and adjust engagement experiences themselves, without waiting in a development queue.

Still, there’s a catch. Whether it’s Slack, Salesforce, or Twilio, these tools only go so far. They empower ecosystems, yes, but mostly within the confines of predefined templates. That limitation means they’ve chipped away at professional services, but they haven’t eliminated the need. Complex, messy, real-world business logic rarely fits neatly into a template.

The Evolution Beneath the Surface

Over the past decade, the SaaS ecosystem has quietly built the no-code / low code tools that make this transition possible. First came workflow builders, allowing teams to model their business logic visually. But while these workflow tools made integration and automation more accessible, they were still limited in practice. Most were used for narrow, well-defined tasks - automating handoffs between apps, or setting up basic internal workflows. They were built around rigid, predefined blocks that worked well for structured processes, but didn’t leave much room for nuance or change. As a result, they were mostly adopted by technically minded users, while the broader business audience never quite followed.

Next came agent builders, often powered by large language models and packaged as no-code assistants. They arrived with big promises: to automate decision-making, handle user requests intelligently, and reduce the load on services teams. And while the potential was real, the reality has been more limited. Most agents can follow instructions and respond within predefined scenarios, but they struggle with complexity, ambiguity, and scale. Eventually, when real-world business logic goes beyond the scripted path, someone still needs to step in.

And now, that evolution is reaching a turning point, with many platforms embracing what’s becoming known as the AI extensibility layer. But this isn’t just another automation tool. It represents a deeper shift in how business users interact with software. Instead of relying on service teams or vendor-led projects, users can now build what they need themselves. They can create apps, define custom fields, deploy logic, and even spin up AI agents. Users only use plain language in a chat-like experience, and their possibilities are not limited to templates or pre-defined flows. These multi-agent interactions are beginning to replicate, and in many cases replace, the kind of hands-on support that professional services teams used to provide.

Rethinking the 80/20 of SaaS Professional Services

It turns out that most service requests are not particularly complex. While a portion requires deep technical expertise, the majority are routine, repeatable, and carry minimal risk. These include things like configuring data mappings, synchronizing systems, adjusting form logic, or making minor workflow modifications. They're not strategic initiatives, they’re foundational, operational tasks. And yet, they continue to consume a disproportionate share of professional services capacity.

This is where the Pareto principle applies. Roughly 20% of customer needs are genuinely complex, and they still require expert services. But the other 80% should never make it to a PS queue in the first place.

By embedding extensibility into the product, platforms can reassign these 80% of tasks to the people best positioned to handle them: the users. Not through support tickets or workaround scripts, but through guided tools that allow users to self-serve safely and confidently.

The benefits cascade from there. Implementation becomes faster. Product adoption improves. Customer success teams are freed up to focus on outcomes, not troubleshooting. And PS teams get to do what they do best: handle strategic, high-value work.

Serving the Segments That Services Leave Behind

This shift matters not just because it makes delivery more efficient, but because it opens doors to segments that the services model has historically excluded.

SMBs have long been left out of the customization conversation. They often don’t have the budget, or the appetite, for multi-week onboarding packages or third-party consultants. But with extensibility built into the product, they can tailor the platform to their workflows on day one.

Enterprise customers benefit too. They still get white-glove support when needed, but they also gain autonomy over the long tail of requests that PS teams can’t prioritize. Region-specific forms, departmental workflows, legacy system bridges - these can all be handled internally, without delays or backlogs.

For the platform, this doesn’t just reduce costs. It expands reach. It unlocks new revenue opportunities. And it builds deeper product stickiness across all customer tiers.

The Road Ahead

The professional services model helped SaaS get started. It built trust, ensured early success, and compensated for immature products.

But in a world where scale matters more than ever, the same model is reaching its limits. Services don’t scale like code. They don’t compound like subscriptions, and they can’t support a business where every customer expects to be up and running in days, not weeks.

What comes next isn’t the elimination of professional services. It’s their refinement. Strategic services will remain, and so will complex projects. But the delivery model for everything else - the repeatable, the predictable, the operational - needs to live inside the product. That’s what extensibility makes possible.