Beyond Buzzwords: AI in RevOps

RevOps leaders don’t need more hype. What they need is clarity. Right now, “agentic AI” is being used to describe everything from basic workflows to simple automation. That muddies the waters for teams trying to decide what actually drives results.

At Domestique, we think it’s important to draw clear lines between these concepts. Each has a place in building operational strength, but they’re not interchangeable. 

Here’s how we break them down, with real examples:

Workflows:

Workflows are simple logic built into tools. Think: If this, then that.

For example, if a demo request comes in via HubSpot, create a deal, route it to the right SDR, and send a follow up email.

Workflows work because they provide consistency and scale. They break down the moment the inputs are messy or there’s an edge case.

Automation: 

Automation removes repetitive tasks, and cuts out the manual busy work.

For example, syncing Salesforce activities into Outreach automatically so reps don’t have to log things twice.

The benefit is time savings and fewer errors. The limitation is that it still follows the rules and parameters that have been set up, and does not think for itself. This is simply execution. 

Assistants:

Assistants bring some deeper intelligence into the mix.

For example, a tool that drafts a cold outreach email using CRM data, or a chatbot that answers, “What’s our standard discount threshold?” These are a step up from pure automation because they can take messy inputs, apply context, and produce a useful output.

But there’s an important caveat. With assistants, you are still setting up the framework, the rules of engagement, and the inputs they can draw from. They are designed to handle a defined scope of tasks and queries, and they won’t stray outside of that lane.

Think of a RevOps assistant like a super competent junior team member: You feed it the data sources it can reference (CRM, pricing tables, playbooks). You define the use cases where it’s allowed to operate (drafting emails, answering policy questions). You will still need to validate its output and decide how or when to use it

Assistants help reps move faster, bring context to repetitive tasks, and lighten the operational load. But they are not autonomous. They don’t choose what to work on, and they don’t reframe the problem if the inputs are wrong. Their strength is efficiency in a bounded scope, not independent problem-solving. 

These tools are becoming more common, and for many teams, they’re already delivering meaningful gains.

Agentic AI:  

Agentic AI, unlike the categories above, is truly autonomous. It takes an objective, breaks it down into steps, executes, learns from the outcome, and adjusts along the way. It is not just running a workflow faster. It is deciding what to do next in service of the goal.

For example, a system that identifies a pipeline gap, analyzes historical conversion rates, forecasts the shortfall, and launches an outbound campaign. It drafts the messaging, assigns tasks, and adapts based on results.

That sounds powerful, but it is not “set it and forget it.” Leaders still have to establish guardrails, define the orchestration, connect data, and oversee the outcomes. The responsibility for results does not shift away from the team.

Most vendors using the term today are still describing workflows with AI wrappers or narrow assistants. True agentic systems are rare. 

Why we care, and why you should too

We help our clients implement AI responsibly, and that starts with being precise in language. Semantics do matter. 

Each layer (workflows, automation, assistants, and agentic AI) has its place. Most teams today benefit from stronger workflows and automation. Some are ready to add assistants. Agentic AI will come, but only when the right data and processes are in place.

The teams that invest in fundamentals now will be the ones best positioned to capture the upside when true autonomy arrives.

If you’re evaluating where AI fits into your RevOps strategy, start with clarity. Get the foundations right, then explore how assistants and, eventually, agentic capabilities can extend your team. 

If you’d like to compare notes or see how we’re helping other operators take this approach, reach out!