According to ServiceNow research that surveyed more than 34,000 executives, service professionals, and customers globally, service reps spend just 45 % of their time on actual customer issues.
So, what happened to most of the reps’ time? It was lost to manual work and to the overhead of disconnected systems that were never designed to work together; 80 % of reps must toggle between three to five systems just to resolve a single issue.
Unfortunately, most companies have been deploying AI on top of legacy contact center and customer service platforms without fixing what was already broken.
But those systems had two fundamental problems. They either deflected customers without resolving their issues or when a customer did reach a live agent, that agent wasn ' t empowered to resolve it because the tools, people, and systems needed to fulfill the request weren ' t connected.
AUTOMATION SURFACES THE WEAK LINKS
Legacy CRM was built to log what happened, not orchestrate what happens next. When issues span departments, that gap becomes visible in painful ways.
Let’ s say a customer calls about a service outage or a billing dispute, and resolving it requires work from teams across Fulfillment, Legal, Billing, and Operations. Legacy CRM can track the request. What it cannot do is route work to the right teams, trigger approvals, or ensure every task gets completed. In such cases, human employees become the middleware, manually copying data and chasing approvals across systems. Cases fall into black holes, and no one has full visibility into status or accountability.
DUCT-TAPING AI ON TOP DOESN ' T CHANGE THAT. AT BEST, IT GETS CUSTOMERS TO THE SAME DEAD END FASTER.
The data asymmetry behind this is well-documented but rarely addressed. 43 % of reps cite inconsistent customer data as a top daily challenge. Yet only 28 % of executives recognize it as a significant challenge.
This last datapoint is troubling. When Leadership does not see the foundation problem; instead they reach for solutions that do not address it: new dashboards, more tooling, another bolt-on.
Deploying AI on top of fragmented data, siloed applications, and broken workflows does not accelerate value. Instead, it accelerates dysfunction.
Only 34 % of executives report significant progress on building a genuinely connected enterprise approach, and that number explains why so many AI investments in the contact center are underperforming.
Real resolution requires AI connected to data and workflows. The system needs to know who the customer is, what they are entitled to, and what just happened.
Let’ s look at a disputed charge. Real-time data confirms the transaction, and the workflow resolves it immediately, or processes a refund, issues a replacement card, or schedules a callback, pulling in a human only when truly necessary.
Unified data, integrated applications, governed knowledge, and clean process design are now table stakes. For automation to deliver what it promises, the CRM must connect, sell, fulfill, and service on a single platform. Organizations that treat those as optional upgrades will keep hitting the same ceiling.
HUMAN AGENTS BECOME COM- PLEX RELATIONSHIP STEWARDS
As I noted earlier, most agents spend their days doing work that should not require a human: toggling between apps, doing data entry, and acting as middleware between departments.
CRM
Perhaps not surprisingly, only 39 % of service reps say they have the tools and training needed to deliver superior customer experience( CX). The tools are failing them.
What reps actually need are AI tools that surface context and next-best actions in the moment, backed by ongoing training that builds the judgment to use them well and the confidence to know when to step in.
But as automation absorbs routine work, the interactions that remain for humans are higher-stakes and more meaningful. They require emotional intelligence, judgment, and the kind of relationship-building that AI cannot replicate.
From our research, 87 % of customers say phone calls are their preferred communication channel. With that, 46 % say their biggest concern with AI chatbots is their inability to fully understand their questions or concerns.
AI specialists surface context and recommended next actions so the agent can focus on the relationship, not the mechanics.
That is the shift that makes service a genuine differentiator. And when a situation calls for a human, the right platform makes that handoff with full context, so the customer never has to start over.
PREDICTIVE SERVICE EVOLVES INTO AUTONOMOUS RESOLUTION
The next phase of AI-powered CRM moves beyond anticipating issues to resolving them independently: before customers ever reach the contact center.
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