News - February, 2026

From SaaS to Agents: the next abstraction layer

Munich/Luxembourg– February 3, 2026 - SaaS scale-ups are realizing that adding “AI features” isn’t the point—the real shift is toward automation at scale.

 

SaaS scale-ups are realizing that adding “AI features” isn’t the point—the real shift is toward automation at scale. This pushes product teams toward agentic workflows, deep integrations, and enterprise-grade governance, while GTM teams move beyond seat-based pricing to hybrid or outcome-based models tied to measurable business results. AI is changing what customers buy (outcomes), how value is delivered (agents with context), and how it is monetized (usage and results, not just users).

 

Software has eaten the world – now it needs to become agentic

Modern SaaS platforms are where knowledge work happens. They provide the tools, data, and workflows that underpin nearly every business process. With the arrival of AI—and especially agentic AI—these platforms must reinvent themselves across product, go-to-market, and pricing, or risk being displaced by a new agentic layer in the tech stack.

Many SaaS companies initially responded by adding a handful of AI features. That is not enough. To stay relevant, platforms must evolve into environments where agentic co-workers and human knowledge workers collaborate—while simultaneously adapting their GTM motion and pricing to reflect this new mode of value creation.

 

Product is shifting from “tools for human” to “agentic platforms” 

Historically, SaaS platforms provide the context, data, integrations, and tools that knowledge workers need to get their jobs done. They are, at their core, tools. Adding a few AI features doesn’t change that. In an agentic world, these platforms must evolve to support collaboration between human workers and agentic co-workers. This requires not just data and integrations, but a true agentic platform with enterprise-grade guardrails, governance, and auditability.

For example, a social media management product can no longer stop at enabling a team to plan and publish content. It must become an agentic platform that autonomously creates content, designs and executes campaigns, measures impact, and reports results to its human manager.

Similarly, a recruiting platform must evolve from a tool for HR teams into an agentic recruiting system—one that researches candidates, builds and manages the funnel, schedules interviews and assessments, analyzes results, and proposes hiring decisions.

This shift fundamentally changes the user experience. A conversational command interface becomes the primary way to delegate high-level tasks to agents, complemented by a builder or studio to configure and customize them. Equally critical is a powerful control plane to observe, govern, and constrain agent behavior, including policy management, explainability, audit logs, escalation paths, and human-in-the-loop overrides.

 

Customers stop buying software – they buy delegation

Agentic solutions are forcing SaaS companies to rethink their go-to-market approach. The traditional pitch was to equip teams with better tools—more features, more capability—while responsibility for outcomes remained firmly with humans.

The new pitch centers on value and results. Proof-of-value metrics such as time to first automation, resolution rate, deflection, and cycle-time reduction become critical. At the same time, trust, security, and governance move to the foreground, as responsibility for delivering consistent, high-quality outcomes increasingly shifts from users to the agentic platform itself.

Meanwhile, the role of humans changes from executing tasks to managing outcomes. Humans retain control, review the output of their AI coworkers and ensure quality.

 

Pricing is moving away from pure seats toward usage/outcomes

The value of agentic co-workers scales with capability and usage, not with the number of human seats they support. Seat-based pricing breaks down in a world where greater automation—and fewer people—creates more value.

As a result, companies are experimenting with new pricing models, including:
• hybrid approaches (seats plus usage-based metrics)
• consumption-based add-ons
• outcome-based pricing, where customers pay when the job is done

This shift is already visible in customer service, where solutions like Intercom’s Fin and Zendesk price based on outcomes such as cases resolved rather than users.

 

Summary

In the agentic AI age, SaaS winners won’t just add AI—they’ll re-architect around automation, trust, and pricing that matches value. The competitive moat of the future is no longer a large code base, but rather proprietary data, deep vertical expertise and the agility to always use the latest AI models.