Verint has found that contact center AI investment is accelerating, but fragmented data still threatens its business value.
The company’s State of Contact Center AI 2026 report found that 87% of contact center leaders plan to increase spending on automated agent assistance. It also found that 62% now view the contact center as a value center, where its value outweighs the cost of running it.
That marks a clear shift in how enterprises see the contact center. For years, many leaders measured it mainly through cost, speed, and containment.
Now, AI is pushing the function closer to revenue, retention, and customer journey performance. But Verint’s research suggests that disconnected systems could slow that transition. Anna Convery, CMO at Verint, framed the research as a guide for leaders moving from operational management to business impact:
“This report is built for contact center leaders navigating that tension, providing guidance on where to invest, what’s actually working, and what it takes to move from running a contact center to operating one that drives measurable business value.”
That line sets up the real story. Contact centers may have the appetite for AI, but many still lack the connected data foundation needed to turn that investment into value.
Contact Center AI Is Becoming a Value Center Test
Verint’s report shows that contact center AI has moved beyond the experimentation phase.
AI now supports agents, supervisors, forecasting, quality programs, and customer-facing interactions. That makes the technology more central to how enterprises manage customer experience.
The performance case already looks strong. Verint found that 94% of organizations say AI tools have increased human agent performance.
It also found that 75% report performance gains from AI in agent training, while 78% report gains from AI in evaluation and performance management. That gives CX leaders a stronger internal case for investment, but it also raises the standard for proof.
A contact center that claims to be a value center must show more than lower handle times. It must show better resolutions, stronger loyalty, cleaner journeys, and more productive teams.
That creates a tougher measurement challenge. Leaders need to connect AI performance to customer outcomes, and they need systems that can track those outcomes across the full journey.
Fragmented Data Could Slow AI Value
The report identifies data availability and customer journey tracking as key blockers to value center transformation. That finding cuts through a lot of AI noise. The issue is rarely whether a contact center’s systems can feed AI with accurate, connected, and usable customer context.
Verint found that the average contact center uses technology from three or more providers. It also found that 20% use five or more.
That creates a real fragmentation tax. Customer records, interaction histories, workforce systems, quality tools, and channel data often sit in separate platforms.
When that happens, AI only sees part of the customer journey. That limits personalization, weakens automation, and makes measurement harder.
It also creates operational risk. Broken integrations can disrupt workflows, while closed ecosystems can make it harder for leaders to adapt as needs change. Speaking to CX Today, Rebecca Wettemann, CEO and Principal Analyst at Valoir, framed production readiness as the real AI test for customer-facing teams:
“But we hear that and people say, ‘wait a minute, I want to make sure before I put this in production that it’s actually going to do a positive interaction with my customer if it’s customer facing, and that it’s not burning through tokens.’”
Her point lands directly on the challenge facing CX leaders. AI can improve service, but only when teams can control outcomes, understand costs, and trust the data behind each interaction.
Supervisors May Become the Next AI Battleground
Verint’s research also suggests that supervisors will become a major focus for contact center AI investment.
The report found that 94% of organizations see value in additional AI-powered tools for supervisor support. That includes real-time coaching, automated quality scoring, and performance pattern detection.
This matters because supervisors sit at the pressure point between strategy and execution. They must improve agent performance, protect customer experience, manage compliance, and keep teams engaged.
AI can help by surfacing patterns faster than manual reviews. It can also support more consistent coaching and reduce the lag between customer issues and operational action.
But the value still depends on data quality. A supervisor dashboard that pulls from incomplete or inconsistent systems may create confidence without clarity.
For CX leaders, the practical question is simple, can the organization give supervisors AI that reflects the real customer journey?
Customer Perception Still Needs Work
The report also warns that customers have not fully bought into AI-led service. Verint found that 64% of consumers have seen AI’s impact on customer service. However, only 62% believe that impact has been positive.
That gap should concern any business treating AI adoption as an automatic CX win. Customers judge AI by outcomes, they care whether the experience feels easier, faster, and more relevant. They do not care whether the brand has invested in the latest automation layer.
That creates a clear mandate for contact center leaders. AI programs must start with moments that matter across the customer journey. They must also measure whether automation improves the experience, reducing workload alone will not be enough.
The report shows progress on that front, but it also shows unfinished work. Only 44% of organizations say AI has significantly reduced routine and repetitive work for agents, while 53% say it has somewhat reduced it. That suggests AI is improving performance before it fully changes the work itself.
What CX Leaders Should Take From This
Verint’s report points to a more mature phase of contact center AI adoption. The investment case is strong, and the performance gains are visible. But the next stage will reward teams that connect data, simplify technology stacks, and define AI success through business outcomes.
For CX leaders, the highest-leverage move in 2026 may be less glamorous than launching another bot. It may be unifying customer data, improving integration discipline, and giving supervisors better real-time visibility.
That is where the value center promise becomes real. AI can help contact centers move closer to revenue, retention, and loyalty, but only when leaders build the operational foundations to support it.
The future of CX will favor teams that make AI work across the full customer journey. Customers will feel the difference when every system, agent, and decision has the same view of what matters.
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