Stop Chasing Faster. Start Designing For Fewer Repeat Contacts
Plus: Zoom, NiCE, Verint, and RingCentral all pushed the same idea this week: AI has to finish the job, not just move the ticket.
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Good Morning!
The contact center is having a small identity crisis, and honestly, it is overdue. Today’s edition is all about resolution over activity: better handoffs, tighter guardrails, smarter workflows, and less customer repetition. So, grab your coffee, and read on for the moves that actually matter to CX leaders this week.
The Executive Hook:
Here is the fight worth having in 2026: are you using AI to make interactions shorter, or to make customer problems disappear? Those are not the same thing. The last 24 hours made one thing clear: the vendors are shifting from copilots that suggest work to systems that take action across the journey, with quality controls wrapped around them.
The edge for CX leaders is not more automation. It is recoverable automation, with context, audit trails, and a clear fallback when the bot gets it wrong.
🧠 THE DEEP DIVE: Zoom Tries To Retire The Wrong Contact Center Metrics
Zoom’s newest CX announcement is really an argument against the way many contact centers still run. For years, teams have chased faster calls, higher containment, and lower visible cost, even when customers wind up calling back, repeating themselves, or getting stuck in broken next steps. Zoom is pushing a different idea: AI should not be judged by how quickly it closes an interaction, but by how reliably it helps finish the job. That is the shift CX leaders should pay attention to, because once resolution becomes the goal, the whole scorecard changes.
Here are the parts that matter most:
AI moves from advice to action. Zoom’s new AI Expert Assist 3.0 (see feature below) is built to go beyond prompts and actually update records, trigger follow-up steps, and document outcomes inside approved guardrails. That matters because the real friction in service is often not the conversation. It is the swivel-chair work after the conversation.
Quality management now has to score bots and humans the same way. Zoom said its quality stack will cover virtual agent interactions too. That is the right move. If your bot is judged on containment while your agents are judged on policy, empathy, and accuracy, you are running two different businesses.
Workflow orchestration is becoming the real control surface. Zoom’s push into workflow design means AI is moving out of the chat box and into the operating model. That is where customer effort, clean handoffs, and cost-to-serve actually move.
Workforce management is getting pulled into the same AI stack. Zoom also highlighted self-healing intraday workforce management. Easy to miss, but important. You cannot promise faster resolution if your staffing model still reacts too late.
The proof points are promising, not complete. Zoom shared an internal 25-point CSAT lift for its own virtual agent use and cited 92.8% first-pass accuracy on retail-domain tasks. Useful signals. Not broad market proof.
My take:
This is the right argument. CX teams have spent too long rewarding speed even when speed just creates a second contact. The better play is to measure customer effort, repeat contacts, policy-safe completion, and handoff quality. Also, credit where it is due: Zoom did not just add more AI sparkle. It added auditability, workflow triggers, and shared quality oversight. That is how AI becomes operational, not theatrical.
What CX leaders should do this week:
Pick one high-volume journey with ugly repeat contacts, like order status exceptions or billing corrections. Then rewrite the scorecard around three questions: did the issue get resolved, did the next step actually happen, and did the customer have to come back later. If your AI stack cannot support those three, it is not mature yet.
Source: Zoom
📊 CX BY THE NUMBERS: Consumers Will Use AI, But They Still Don’t Fully Trust It
Data Source: Klaviyo AI Persona Research
41% of consumers said they bought a product recommended by AI in the past six months. AI is already shaping buying behavior, not just browsing.
60% use AI at least weekly, but only 13% said they fully trust it. Adoption is outrunning trust, which is where CX teams get burned.
78% said they include emotional or personal context at least some of the time when using AI. Customers are treating these tools like conversations, which raises the bar for tone, memory, and privacy handling.
The Insight:
Customers are not waiting for your governance committee to feel ready. They are already showing up with AI-shaped expectations and conversational habits. The smart move is to deploy AI where context helps, answers can be verified, and a human can step in fast when trust starts to wobble.
🧰 THE AI TOOLBOX: Zoom AI Expert Assist 3.0
The Tool: A service-side AI assistant that can understand customer context and take approved actions across enterprise workflows.
Problem: Agents lose time bouncing between systems, writing notes, and chasing follow-ups while the customer waits and the issue drifts.
Solution: Picture an agent handling a messy billing call. Instead of getting a suggestion and then doing five manual steps, AI Expert Assist 3.0 can update records, trigger follow-up processes, and document the outcome inside preset guardrails. It also adds tracing on recommendations and actions, which matters when compliance, refunds, or escalations are involved.
Benefits:
Time: Less after-call work and less app switching.
Quality: Cleaner documentation and more consistent follow-through.
Experience: Agents stay present, and customers get fewer dropped next steps.
Where it sits: Front stage / Side stage
Best Fit:
Works best when the workflow has clear rules, structured next steps, and a real pain point in post-call admin.
Not a great fit when the policy logic is fuzzy, systems are badly integrated, or you cannot audit what the AI did.
Key Takeaway: Use it for action-heavy service work, not for high-emotion conversations where judgment and recovery still need a skilled human in charge.
Source: Zoom
⚡ SPEED ROUND: Quick Hits
NiCE Launches Agentic AI That Turns Interaction Data Into Ready-To-Deploy AI Agents — The important part is not “agentic.” It is the promise to turn voice, chat, workflow, and human interaction data into deployable AI agents faster, which could shrink the gap between insight decks and actual workflow change.
Verint Expands AI Bot Portfolio To Calabrio Customers — This is a practical CX story: more workforce, QA, copilot, and IVA capability without forcing a platform rip-and-replace, which lowers adoption friction for ops leaders who hate big migrations.
Spectrum Business And RingCentral Expand Partnership With AI Contact Center And Conversation Intelligence To Transform Customer Experiences — RingCX plus ACE brings unified omnichannel service and sales intelligence into one managed offer, with auto-scoring across 100% of interactions, which is useful if you want one operating view instead of three disconnected dashboards.
📡 THE SIGNAL: Build For Completion, Not Activity
The pattern across today’s stories is simple: AI is moving from assistant mode to operating model mode. That means the winners will not be the teams with the most bots. They will be the teams with the cleanest handoffs, the best audit trails, the smartest quality controls, and the discipline to measure repeat effort instead of vanity speed. This week, make one execution choice: pick a journey and decide whether your AI is there to deflect, assist, or complete. Then ask your team one sharp question: what happens to the customer when the model is only 80% right?
See you tomorrow.
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📬 Feedback & Ideas
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