AI agents are all the rage, and every SaaS company is looking for a way to adopt some AI tool. After speaking with revenue operations leaders and practitioners who are actively deploying them, one thing is clear: successful AI initiatives aren't driven by the latest model—they're driven by solid planning and execution.
Recently, our CEO, David Carnes, sat down with three RevOps leaders who are leading their teams in adopting agents:
If you're working on your team’s agent strategy, here are eight lessons worth learning from.
The best projects begin by identifying a repetitive, time-consuming process that has a measurable impact on the business. AI is the solution—not the strategy.
We recommend thinking about an agent like you would a new hire – what are you bringing on a new hire to do? What would they solve? What would success mean? What would their job description look like?
Many organizations see quick wins by using agents for:
These processes are high-volume, relatively low-risk, and easy to measure.
An agent is only as good as the information it can access. If your CRM is incomplete or your processes aren't standardized, expect inconsistent outputs. The age-old adage, “garbage in, garbage out,” still applies when you use AI!
Before deploying agents, make sure your data is accurate, accessible, and governed.
The most effective implementations don't eliminate people. Instead, your best humans should get to focus on the high value work only they can do.
Define when an agent can act independently and when it should escalate to a human. In Tracie’s experience, it could take 4-6 months before an agent can operate independently and consistently.
You don't need ten agents on day one. Choose one workflow, establish success metrics, iterate, and expand from there.
Our panelists mentioned creating parking lots for agent functionality to chip away at. When OpFocus works with you on agent planning, we start by creating an agent roadmap that takes into account high impact, low hanging fruit, and how to step up agent capabilities over time.
A polished demo doesn't equate to long-term success. Beyond the pre-canned features and functionality, you’ll want to ask the vendors you’re evaluating about these additional areas:
Our panelists emphasized how helpful it was to have vendors who provided white glove support (like Relevance AI’s enterprise plan) or who had support teams that were responsive beyond initial deployment. (OpFocus can also serve as your partner in planning, building, deploying, and managing agents!)
Treat AI agents like any other production system. Establish clear ownership, documentation, approval processes, and monitoring from the beginning to reduce risk and maintain trust. You can read all about how OpFocus recommends approaching agent governance.
Change management matters. Teams are more likely to embrace AI when they understand its purpose and see it reducing repetitive work—not replacing expertise.
Choosing the right AI agent strategy can feel overwhelming, especially with the number of tools entering the market. At OpFocus, we help organizations cut through the noise by evaluating which agent platforms fit their specific use cases, developing a practical roadmap for adoption, building and deploying AI solutions, and establishing sustainable governance processes that support long-term success.
Whether you're just exploring AI or ready to scale beyond a pilot, our team can help you implement agents that deliver measurable business value while keeping your operations secure, reliable, and manageable.