How Contact Center AI Is Affecting the State of Agent Experience
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When you think about contact center AI, the first thing that springs to mind is likely automating customer self-service.
But, according to our latest research, based on feedback from 1,000 frontline agents, some of the most transformative use cases come from applying AI directly inside agent workflows to eliminate busywork, increase productivity, and the contact center AI agent experience.
So what does that actually mean in practice?
Before diving into the key findings from the State of Agent Experience 2026 report, let’s start by grounding ourselves with a few questions leaders are asking right now.
Agent experience refers to the quality of a contact center agent’s day‑to‑day work, shaped by the tools, systems, workflows, and AI that they use. Great agent experience minimizes unnecessary manual tasks, provides scheduling flexibility and helps agents resolve issues efficiently. Over time, agent experience directly influences agent productivity, retention, and the quality of customer experience — especially as AI for contact center agents becomes more embedded.
Contact center AI improves agent experience by automating repetitive and administrative tasks — such as after‑call work, knowledge search, and handoffs — so agents can focus on complex, high‑value conversations. Verint’s 2026 research shows the highest ROI comes from applying AI to agent workflows, not just customer self‑service. This shift to an AI-powered agent workflows is central to improving the contact center AI agent experience.
No. The data shows AI augments agents instead of replacing them. The most successful organizations use AI to handle the work agents shouldn’t be doing, freeing humans to focus on judgment, empathy, and problem solving. In short, AI for contact center agents elevates the role rather than eliminates it.
With that context in mind, here’s what the research reveals about where contact centers should act now.
The “busywork” tax
Agents today spend a surprising amount of time not helping customers — but searching, documenting, and completing manual tasks.
According to the State of Agent Experience 2026 report:
- 45% of calls require agents to search for answers
- Knowledge retrieval adds ~2.7 minutes per interaction
- Across a 1,000‑agent contact center, this equates to millions of hours of lost capacity annually (Verint, State of Agent Experience 2026)
This is the hidden “busywork tax” — and it’s one of the most expensive inefficiencies in modern contact centers.
Agents are gathering context, navigating systems, searching for answers, completing transactions, and managing after call work — tasks that modern contact center AI can automate.
The takeaway: You’re paying skilled agents to do work AI can handle.
The cost of inertia
Many organizations recognize the potential of AI but remain stuck testing indefinitely — running proofs of concept without scaling AI into production.
That hesitation carries a real cost. Our research found:
- After call work alone takes agents ~3 minutes per call on average
- Automating after call work can unlock significant capacity per interaction
- Every additional month spent in pilot mode is another month of unrealized savings
Even automating a single workflow — like after call summarization — delivers immediate, measurable impact. In reality, AI implementation in contact centers only delivers value when it moves beyond experimentation and into real agent workflows, using real data and real interactions. This is where AI summarization for contact centers proves its worth fast.
The takeaway: Proofs of concept avoid reality. Production AI creates results.
The next gen agent
Agents’ roles are changing quickly.
The research found:
- 61% of agents expect their roles to become more complex or technical within three years
- Nearly half of agents already work across multiple channels
- Poorly implemented AI deployments risk eroding, not enhancing, value
As complexity increases, agents need AI they trust — embedded directly into their workflows, without adding friction. AI adoption must be intuitive and supportive. Otherwise, even powerful technology risks rejection.
The takeaway: The key to AI adoption is making it as frictionless as possible.
Fix EX — or pay through churn
Agent experience isn’t just an operational issue — it’s a retention issue.
Our research shows:
- 31% of agents say they’re likely to leave within six months
- 9 out of 10 say schedule flexibility directly impacts job satisfaction
- In a 1,000‑agent center, attrition costs can exceed $6M annually
When agents are overwhelmed by manual work and rigid schedules, churn accelerates. Conversely, organizations that improve AX through AI powered automation and flexible scheduling see measurable gains in retention, consistency, and performance.
The takeaway: Ignore agent experience and the cost shows up on your P&L.
What tasks should AI automate first in contact centers?
Based on direct agent input, the highest impact opportunities for automation are clear.
The research shows contact center AI should focus first on:
- After call work (ACW) summarization and documentation
- In call knowledge search and answer retrieval
- Interaction handoffs and intelligent routing
- End‑to‑end task completion using agentic AI
These tasks consume the most avoidable agent time per interaction — and directly impact handle time, adherence, and agent satisfaction.
Automating after call work: where to start
After call work is one of the fastest ways to reclaim capacity. 54% of calls require ACW, making it one of the most consistent drains on agent productivity.
By automatically generating summaries and case updates immediately after each interaction, AI reduces wrap up time while improving consistency and data quality.
Will AI replace contact center agents? The human + AI answer
The future of the contact center isn’t humans or AI. It’s humans with AI.
The State of Agent Experience 2026 makes one thing clear: leaders aren’t really buying AI. They’re buying outcomes:
- Higher capacity
- Faster, more consistent resolutions
- Lower operating costs
- Happier, more engaged agents
The real question isn’t whether AI belongs in the agent workflow. It’s how fast organizations move from pilot to impact.
Get the full State of Agent Experience 2026 report
This blog highlights just a few of the insights from Verint’s latest research. To explore all four trends — and the agent driven data behind them — download the full State of Agent Experience 2026 report.