Automation is not a binary — you either have it or you don't. It exists on a spectrum, and most businesses sit somewhere in the middle without a clear picture of where they are, what comes next, or what it would take to get there. The Automation Maturity Model provides that framework.
At Avian, we use a four-stage model to assess where a business sits and to build a roadmap that moves them forward systematically, not reactively.
Everything is done by hand. Processes are informal or undocumented. Data lives in spreadsheets or individual inboxes. Status updates happen via Slack or email. Reporting is assembled manually every week. There are no automation tools in use, or the ones in use are disconnected one-offs with no system behind them.
This stage is sustainable at very small scale — typically under 5-10 people — but it becomes a significant drag on growth the moment the business starts to scale. The cost of manual work compounds with headcount.
The business has started automating, but in a reactive way. Individual automations exist — a Zap here, a Make scenario there — but they're disconnected. There's no master system, no documentation, and no one person who has a full picture of what's automated and how. When automations break, they often break silently.
This is where most small-to-medium businesses sit. They've recognized the value of automation but haven't yet approached it systematically. The result is a patchwork that saves some time but introduces its own maintenance burden.
The business has a designed automation architecture. Workflows are documented, automations are tested and monitored, and there's a clear map of what tools connect to what and how data flows between them. The operation is largely self-maintaining — routine tasks run without human intervention, and exceptions surface automatically rather than being discovered after the fact.
This is the target state for most growing businesses. It requires an upfront investment in design and build, but the ongoing operational cost is dramatically lower than Stage 1 or Stage 2.
The most advanced stage, where automation includes AI-powered decision-making. Systems don't just move data — they analyze it, classify it, route it intelligently, and generate outputs. Examples include: AI-powered lead scoring that routes prospects to the right rep, document parsing that extracts and structures data from contracts or invoices, and intelligent reporting systems that surface anomalies and trends proactively.
Stage 4 is not a destination for every business — it's a frontier most will reach selectively, in specific processes where AI adds real value.
The honest answer for most businesses reading this is Stage 1 or Stage 2. That's not a failure — it's a starting point. What matters is having a clear picture of where you are and a realistic roadmap to where you need to be.
At Avian, our first step with every client is a maturity assessment — mapping their current state across people, processes, tools, and automation. From there, we build a prioritized roadmap that moves them from where they are to where they need to be, stage by stage.
Strategy Lead
