AI agents don’t replace your strategy. They bring it to life—but only if you’re ready to guide them.
That’s a truth most teams know in theory, but struggle to apply in practice. This results in a wave of AI excitement followed by stalled pilots, disconnected data, and teams wondering what all the hype was for.
Let’s be clear: The problem isn’t (usually) the tech. It’s the readiness of the data, processes, and systems needed for AI agents to deliver on their promise.
AI agents will change the game for post-sale teams—surfacing unseen risks, automating repeatable tasks, and scaling success without scaling headcount. But without the right foundation, they’ll just be another technology promise that never delivers.
This isn’t about blowing everything up. It’s about getting aligned on three things that will move AI agents from pilot to powerhouse.
1. A Clear Business Problem to Solve
This is where a lot of AI initiatives lose momentum: They start with the solution instead of the problem.
Yes, AI agents can do a lot. But that doesn’t mean they should do everything. The most effective deployments will start with a focused goal. A Customer Success (CS) team wants to reduce churn by surfacing risk earlier. A Digital CS leader needs to support long-tail customers without adding headcount. A CCO is trying to move the needle on Gross Revenue Retention (GRR) and needs to reallocate Customer Success Managers’ (CSMs’) time from repetitive check-ins to deeper value conversations with top accounts.
Once a focused goal is established, teams can work backward to determine the best opportunity for AI agents to make an impact in the process. Often it’s digital-led or long-tail customer segments where contacts aren’t getting consistent touchpoints. To fill this gap, agents can be deployed to extend coverage and deliver a better experience through timely outreach, intelligent nudges, or escalations based on risk signals. Those are your early indicators of results. Over time, the lagging metric (GRR in this case) starts to reflect the impact.
AI agents won’t change the value your customers expect. They’ll change the way that value gets delivered. That’s why Gainsight customers who succeed with agents treat them as a force multiplier, not a fix-it-all. They anchor the agent to a clear customer outcome, avoid chasing shiny tools for their own sake, and choose solutions built with deep domain knowledge. Because when you’re solving CS problems, you need AI agents that actually understand CS.
2. Internal Readiness and Buy-In
Deploying an AI agent isn’t like flipping a switch. You can’t just turn it on and expect impact. You need people who are ready to work with it.
That starts with a champion—an individual or group who doesn’t just approve the use of AI, but helps define its role and guide its adoption. The most successful teams have people who can move the conversation from skepticism (“Is this replacing me?”) to curiosity (“How can this help me level up?”).
Yes, AI agents save time. But time savings alone aren’t the goal. What matters is how you reinvest that time. Maybe CSMs focus more on proactive expansion plays. Maybe onboarding specialists deepen the customer journey. Maybe your digital team fine-tunes what’s already automated. Whatever the direction, it needs to be intentional and clear.
That also means preparing your team for a shift in how they work. AI agents redefine roles and responsibilities in CS over time. CSMs will evolve from playbook executors to playbook architects. Ops leaders will move from reactive to strategic. Managers will coach for outcomes, not just activity.
And don’t forget your IT and Infosec colleagues. These teams can help define requirements, assess risk, and fast-track vendor evaluations. Waiting too long to loop them in can stall a promising POC before it even gets started. Early collaboration pays off in smoother rollouts, stronger trust, and faster time to value.
Having the right frameworks, domain expertise, and real-world experience is paramount to your ability to hit the ground running. You don’t have to invent the process from scratch—just make sure the process fits your strategy and your people.
3. Securely Connected (and Clean-Enough) Data
Let’s bust the biggest myth in the AI conversation: Your data doesn’t have to be pristine. It just has to be connected.
AI agents need access to the right signals—from CRM to product usage, support tickets to sentiment—so they can interpret what’s happening and take action. Success with agents isn’t about flawless dashboards. It’s about creating a real-time flow of data from sources that carry meaningful customer intelligence.
Still, governance matters. Make sure you’ve considered infosec, access control, and compliance before agents start reading email threads or triggering customer outreach. And make sure you are connecting data you feel mostly confident in, that’s “good enough” to validate your AI or agentic use cases.
But connection alone isn’t enough. You also need to define where the agent fits in the process. Ask yourself these questions:
- Does it flag sentiment risk and create a CTA for your CSMs?
- Does it initiate an automated email sequence when product usage dips?
- Does it trigger a health score update based on a series of missed meetings by an executive or champion?
Agents work best when they’re embedded into real workflows—they thrive in ecosystems. Garbage in, garbage out still applies—but context in, intelligence out is the real goal.
That’s why getting these foundational elements in place—clarity of purpose, internal readiness, and connected data—isn’t a hurdle. It’s a head start. When those pieces align, AI agents stop being a promising idea and start becoming a true part of how your team operates. Not a side experiment. Not a siloed tool. But a trusted partner that scales your impact, sharpens your focus, and helps every customer interaction move closer to value.
The promise of AI agents is real. And with the right preparation, the results will be too.
Learn More
Learn more about the promise of agentic AI for customer success by exploring Atlas, Gainsight’s AI agents for retention and Growth.
