In 2026, the marketing technology landscape grew by just 0.7%, increasing from 15,384 to 15,505. At first glance, it appears to have stalled and reached its limits. But that headline number hides what’s really happening beneath the surface: nearly 1,500 tools were added, while more than 1,300 disappeared. This is not stagnation. It is renewal.
Source: State of Martech 2026 report, Scott Brinker & Frans Riemersma
For years, we have used the martech landscape not for the final number (even though that’s what excites most people), but to observe the deep and subtle shifts happening right in front of our eyes. It offers a unique vantage point.
What it shows today is clear. Peak Martech is a myth. Martech is entering its Darwin phase. The martech landscape is renewing. Value is growing.
That is the shift. And that shift has direct consequences for your stack. The era of accumulating tools is giving way to an era of replacing them. At the core of this transition is a structural change in how value is created.
SaaS platforms are no longer the primary source of differentiation. They are becoming infrastructure: systems of record, workflow engines, and integration layers that provide stability and structure. The real value is moving on top of that foundation. AI is becoming the value layer.
Where SaaS operates on rules and predefined logic, AI operates on language, context, and probability. It doesn’t just execute workflows. It interprets, decides, and adapts.
It is as if AI added sound to silent movies. The foundation remains the same, but the experience and the value change fundamentally. This changes the role of the stack. It is no longer about assembling the right tools. It is about enabling the right outcomes.
The landscape is not flat. It is being rewired.
AI becomes the value layer on top of the SaaS infrastructure
If the landscape is being rewired, the most visible impact will be in how companies create customer value. Nowhere is that shift more pronounced than in personalization.
For years, personalization has been defined by rules. Segments, workflows, triggers. If a customer fits a profile, they receive a predefined experience. This worked in a world where customer journeys were relatively predictable, and channels were controllable.
That world is disappearing.
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Retrieving structured data, such as a customer’s age or city, probabilistically does not make sense. This is where SaaS remains essential as infrastructure. But as AI becomes the value layer, personalization is no longer about configuring journeys. It is about continuously interpreting context and deciding how to respond in real time.
The shift is subtle but profound: from designing experiences in advance to generating them dynamically, powered by a solid SaaS and data foundation.
This is not an incremental improvement. It is a paradigm shift.
OLD (SaaS Era)NEW (AI Era)Rule-basedContext-basedDeterministicProbabilisticSegmentsIndividuals in real timePredefined workflowsAdaptive decisioningCampaign-drivenContinuous interactionMarketer-configuredAI-assisted / AI-drivenStatic journeysDynamic experiences
Renewal is the new growth
If this shift is real, it should show up in the data. And it does.
The martech landscape is no longer dominated by pure growth. Instead, it is spread across four distinct states: Growth, Renewal, Stability, and Decay. In this model, inflow signals opportunity, while outflow signals pressure. Together, they form a market thermometer that reflects how martech vendors interpret demand through market research and customer feedback.
What stands out is not where growth happens, but where it doesn’t.
1. Growth: Redefinition, not expansion
CMS, project and workflow, ecommerce, and iPaaS are growing. These are not new categories. They are being reshaped. CMS is evolving into a machine-readable infrastructure for AI agents. eCommerce is adapting to AI-driven discovery. iPaaS is becoming the orchestration layer that connects everything. Growth is happening where AI changes the job to be done.
2. Renewal: Where the real action is
Content, collaboration, and personalization are renewing. This is the dominant pattern in today’s landscape. High inflow meets high outflow. New ideas are entering rapidly, while first-generation solutions are exiting just as quickly. The market is actively discovering what the new need really is.
Content is the clearest example. The GenAI boom triggered an explosion of tools, followed by rapid consolidation as core capabilities became commoditized. The same dynamic is now playing out in personalization and collaboration.
Most of martech now sits in renewal. It is being rewritten. The market is not expanding. It is replacing first-generation solutions with AI-native ones. Renewal is not instability. It is creative destruction.
3. Stability: Mature, foundational
Core systems such as CRM, customer service, and customer intelligence (including cloud data warehouses) show limited movement. They remain essential, but their role is shifting toward foundational infrastructure rather than innovation.
4. Decay: Losing standalone relevance
Chat, video, and email are shrinking. These categories are not disappearing, but their role is changing. Functionality is being absorbed into broader platforms and AI-driven workflows. AI is upgrading chat and video. Email is moving from being a system you optimize to a channel AI decides to use.
The winners in this next phase of martech will not be the companies with the most tools. They will be the ones with a stack that allows AI to create the most value. If martech is being rewired, the response is not to add more tools. It is time to rethink how the stack creates value. Here are two steps to take.
1. Build for value
The role of SaaS is changing. It is no longer where differentiation lives. It is the foundation that unlocks value. The goal is not to cover every use case with a tool. It is to identify the three to five use cases that deliver the most value and focus on them first.
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This means learning to engineer value first, rather than tools. Value engineering starts by answering three key business questions before addressing technology. It starts with three questions.
- Who is your most valuable customer?
- What do they buy most?
- Where is the margin?
Only once these are clear does automation start to make sense. The objective is not to implement tools, but to create an environment where AI can operate effectively within a clear value model.
2. Build for context
In a world of AI-driven execution, fragmentation becomes the biggest constraint: 90.3% of marketing organizations now use AI agents in some capacity, yet only 23.3% have deployed them in full production.
The shift is not just about integration. It is about how SaaS and AI work together.
SaaS provides structure: data, workflows, consistency. AI creates value on top: interpreting context, making decisions, and adapting in real time. Value emerges at the intersection of these two layers.
The best stacks are not the most feature-rich. They are the most aligned, focused on a small number of high-impact use cases where SaaS enables, and AI amplifies.
Integration is no longer just technical. It is a strategic asset.
It is about context engineering: creating the conditions for the stack to operate effectively, not by adding more tools, but by ensuring that data, workflows, and decision-making are aligned around a common set of use cases.
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