Future-ready stacks combine SaaS, AI, workflows and human skills into adaptive systems. Here’s how to manage capabilities as your new foundation.
“RIP SaaS, hello AI” has become a popular refrain online, implying AI will replace SaaS. That framing, however, overlooks how martech stacks actually work.
The debate between SaaS and AI has sparked endless speculation: Will one overtake the other? Will software vendors fade as AI matures? Those questions sound bold, yet they overlook the real issue.
A future-ready stack isn’t defined by which software category you adopt but by how effectively you manage its output — regardless of the underlying technology.
AI doesn’t replace SaaS. Both belong to the same continuum of how businesses build technological capabilities to execute and adapt.
The real shift leaders need to make is simple but profound: stop viewing the stack as a collection of tools and start managing it as a portfolio of capabilities.
What’s new and unique about AI?
AI agents introduce a new class of technology built on large language models rather than traditional code-and-database architectures. The challenge is in producing predictable outcomes.
Because AI is adaptive and probabilistic, its strength is augmentation — enhancing human and system performance — rather than full replacement.
AI agents are most effective when designed for a specific, well-defined task. Their focused scope allows them to deliver reliable results within clear boundaries.
Platforms like n8n, relay.app or gumloop offer a range of agent templates that handle highly granular tasks, such as:
- Newsletter automation (personalized send times, content repurposing).
- Lead cleansing and enrichment (checking email validity, adding missing firmographic data).
- Outreach sequencing (AI-personalized follow-ups triggered by behavior signals, social monitoring, lead qualification).
Is SaaS very different from AI?
Yes and no. SaaS, by design, operates through rule-based systems that deliver predictable outcomes. You know what you’ll get and it scales reliably. In that sense, it behaves differently from AI.
Still, SaaS — like AI — has never truly been about the tools themselves. For years, analysts evaluated best-in-class software but rarely examined how brands actually used those tools. The prevailing assumption was that the technology was underperforming if every feature wasn’t used.
In most SaaS products, roughly 12% of features account for the majority of usage, according to Pendo research. Gartner reports that only about one-third of available tools are used at all. Viewed through Pendo’s lens, that level of adoption is surprisingly strong.
Our own research at MartechTribe reinforces this pattern: the value of SaaS lies less in the tool as a whole and more in the select features teams rely on most.
Composability works much like Lego blocks — individual, interchangeable components that connect to form what’s needed. Shadow IT and point solutions often filled those missing pieces, driving experimentation and innovation.
This dynamic has long shaped the martech SaaS landscape, which has evolved into a long tail of specialized apps — with countless smaller apps orbiting around a smaller set of core platforms. That trend is accelerating as AI models embed into more niche solutions.
When to pick AI or SaaS
Both AI and SaaS now operate in increasingly atomized ways, making composability the daily reality of stack management. It’s tempting to frame them as competitors, but that mindset doesn’t reflect how they actually function together.
Both operate under the same logic, yet their strengths differ.
- SaaS provides reliability and predictability — the solid foundation you can depend on.
- AI offers flexibility and adaptability, adding a layer of creativity and responsiveness that SaaS alone can’t deliver.
The two don’t cancel each other out. They work in concert.
Jason Lemkin described this contrast through the idea of vibe coding.
- SaaS is steady, dependable and forms the backbone you build on.
- AI, by contrast, is probabilistic. It can surprise you, sometimes brilliantly, sometimes frustratingly. That makes it less suited for replacement but exceptionally useful for augmentation.
Scott Brinker expanded on Lemkin’s concept with a scale that illustrates how AI and SaaS are converging into a fluid fabric of capabilities. Within this fabric, SaaS platforms, AI agents, use cases, workflows, datasets and human skills interweave around customer journeys.
The takeaway: capability management has become the actual currency of the stack — the smallest unit that determines how effectively your ecosystem performs.
What are capabilities exactly?
A capability is simply the ability to accomplish a task or job. It doesn’t matter whether that job is enabled by a SaaS feature, an AI agent, a workflow, a dataset or a human skill. What matters is that the capability exists, can be relied on and integrates into the larger system.
This is where leaders need a shift in perspective. For too long, stacks were like shopping lists of apps — CRM here, marketing automation there, plus a handful of AI pilots on the side. The result is bloat and tool sprawl.
Step back, though, and those tools are just containers. What truly matters is what they allow you to do. Seen through that lens, a stack is less a static toolbox and more a living system of capabilities — constantly evolving as customer needs, competition and market conditions change.
Organize your strategic capabilities
Viewed this way, stacks behave more like solar systems. Each has a center of gravity — the core platforms — with specialized apps, AI agents, workflows and human skills orbiting around them.
Traditionally, SaaS has served as the backbone of these systems. You set the rules, the software executes them and the outcomes remain consistent. That’s why SaaS has been so effective for CRM, billing, compliance and workflow automation.
AI, however, operates differently. It can brainstorm, generate and respond in ways SaaS never could. But it also requires humans in the loop — because good enough isn’t the same as correct every time.
Together, these pieces form an org chart of capabilities. SaaS, AI and human skills sit side by side, each playing a distinct role. A post that visualized this concept went viral on LinkedIn in May.
The post showed a template for a SaaS startup’s marketing team — organized by capability rather than tool — allowing features, AI agents and human skills to combine seamlessly.
While this template suits a SaaS startup, we found a similar pattern across 1,600+ global martech stacks — there’s no one-size-fits-all model. Each organization assembles a unique mix of capabilities shaped by its industry, business model and company size.
Tests comparing capabilities across industries confirmed it — the differences are wide. This is the future of stack management — not tools, apps or categories, but capabilities organized around the jobs to be done.
Manage your martech stack through capabilities
Advantage now comes from how you connect and apply what your tools can do. A martech stack operates as a living system of capabilities powered by SaaS, AI agents, workflows and human skills — each serving a clear purpose within the whole.
It’s not about how many tools you have — it’s about how well they work together to drive real results. The companies that come out ahead will be the ones that treat managing capabilities like a strategic priority, adapting their systems as quickly as their markets change.
The post Martech stacks evolve through capabilities, not tools appeared first on MarTech.
About the author
Background in marketing and software development. Supporting brands to optimize their Customer Technology Stack. Publishing about Martech Stack effectiveness. Researching a proprietary Martech Datawarehouse, consisting of three databases: 1,500+ real-life company stacks, 13,000+ Martech solutions, and 4,600+ Martech requirements/features.”
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