The Rise of M2M Marketing: Why SaaS Vendors Must Start Selling to Machines, Not Just Humans

The Rise of M2M Marketing
Why SaaS Vendors Must Start Selling to Machines, Not Just Humans

There’s a quiet revolution happening in the way software gets discovered, evaluated, and used, and most SaaS vendors aren’t ready for it. We’re entering the era of Machine-to-Machine (M2M) Marketing, where your next user might be an LLM agent.

As large language models become the interface for complex workflows, autonomous agents are starting to make decisions that were once human: Which forecasting API should I call? Which compliance check should I run? Which analytics tool fits this dataset?

These decisions aren’t based on landing pages, pricing tiers, or cold outreach. They’re based on metadata, schemas, and relevance—marketing to machines.

This shift is being catalyzed by protocols like Anthropic’s Model Context Protocol (MCP) and OpenAI’s tool-calling features. These allow LLMs to discover and invoke external tools in real time. Any tool that registers itself via a manifest with the right structure and description can be used autonomously by an agent.

Let that sink in: your SaaS tool can now be discovered and selected without a human ever touching your product. The agent doesn’t care about your logo. It cares about your input schema, latency profile, and whether your manifest description aligns with the task at hand.

This opens up a massive, underexploited marketing opportunity.

To win in this new world, you need to rethink your go-to-market motion:
• Your tool manifest is now part of your brand identity.
• Your parameter schemas are part of your product surface.
• Your execution performance (speed, error rate, reliability) is a ranking factor.
• Your clarity in describing what your tool does determines if it’s selected.

It’s like SEO for AI, but much more consequential. You’re not trying to rank on a webpage. You’re trying to be chosen by an autonomous agent as the best tool for the job.

And this won’t be a niche phenomenon. In high-volume agent-based workflows like finance, legal automation, operations, and e-commerce, tools will be invoked millions of times programmatically. Monetization will be API-first. The tool itself becomes a callable microservice in a larger AI workflow.

The winners in this space will be those who understand that marketing no longer stops at the UI. It extends into the machine layer. The LLM isn’t just an interface; it’s a gatekeeper looking for clarity, precision, and utility, not design systems or email drip campaigns.

So if you’re building SaaS in 2025, it’s time to start thinking
"How do I make my tool attractive to an AI agent?"

In the era of M2M marketing, your best customer might be a machine.

If you’re building AI-facing B2B tools or thinking about agent-based ecosystems, I’d love to connect. This space is about to explode, and those who understand the dynamics early will shape the way software is bought, sold, and used for the next decade.