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Cut the AI Hype: What Actually Works in UCaaS and CCaaS

Written by Michelle Tilton | Apr 11, 2025 9:49:27 PM

You’ve heard it all before: AI is transforming everything. Every vendor is “AI-powered.” Every platform promises game-changing results. But here’s the truth—most teams don’t need more AI. They need AI that actually works.

In Unified Communications as a Service (UCaaS) and Contact Center as a Service (CCaaS), AI has real potential—but only when it delivers clear, measurable value. Think faster resolutions. Happier agents. Fewer dropped calls. Not just another dashboard or digital assistant no one uses.

This blog breaks down which AI features are actually making a difference right now—so you can focus on results, not buzzwords.

What AI Is Already Doing (That Actually Helps)

AI is already part of many communication platforms, whether you notice it or not. But not every feature is equally valuable. The most effective use cases are the ones saving time, improving service, or reducing cost—without getting in the way.

Here are five ways AI is actually working today:

  • Transcribing calls and meetings in real time, making it easy to search and review conversations later. Example: Dialpad automatically transcribes meetings and lets you search them like a Google Doc.
  • Auto-generating summaries and follow-ups, helping teams stay on track without manual note-taking. Example: Zoom AI Companion sends out post-meeting summaries with action items.
  • Predicting customer behavior based on past interactions, so agents can be better prepared. Example: Genesys uses AI to predict customer needs based on journey mapping.
  • Routing calls and chats to the right person, based on skill, language, or customer history. Example: RingCentral’s AI routes Spanish-speaking customers to bilingual agents automatically.
  • Spotting patterns in support issues, customer sentiment, or compliance risks. Example: NICE CXone analyzes sentiment across thousands of interactions to flag churn risk.

If an AI tool isn’t driving one of those outcomes, ask why it’s there in the first place.

Where AI Makes a Measurable Difference

1. Generative AI Assistants

You don’t need an all-knowing chatbot. You need a virtual assistant that handles the basics well.
Generative AI can:

  • Respond to common questions without escalating to a human
  • Draft summaries and flag follow-up tasks
  • Help agents compose replies faster

These tools shine when they save time or prevent context-switching. The goal isn’t to replace people—it’s to free them up for more complex, valuable work.

Example: Yellow.ai’s chatbot reduces email volume by 30% by resolving tier-1 inquiries on first contact.

2. Voice Intelligence

Call data is rich but underused. AI-driven voice intelligence tools can:

  • Transcribe and analyze calls instantly
  • Flag emotional tone or sentiment shifts
  • Highlight compliance risks or key topics

Platforms that use this data to deliver coaching tips or improve quality scores are the ones that make voice intelligence worth it.

Example: Dialpad’s real-time sentiment analysis alerts supervisors when a call starts going sideways.

3. Smart Routing

AI-powered routing moves beyond geography or round-robin queues. It uses:

  • Historical data
  • Customer preferences
  • Real-time sentiment and urgency

Done well, it cuts resolution time and raises customer satisfaction. Some tools even predict which agent is most likely to solve a request, based on past performance.

Example: Genesys Cloud CX uses predictive routing to reduce average handle time by up to 15%.

4. Predictive Analytics

AI shouldn’t just react—it should forecast. High-performing platforms use AI to:

  • Spot spikes in volume before they happen
  • Identify friction points in customer journeys
  • Flag agents who may need coaching

Predictive insights help you make adjustments before things break, not after.

Example: Talkdesk uses predictive AI to forecast demand and adjust staffing automatically during peak hours.

Benefits That Actually Matter

Productivity Gains

AI that automates busywork—like note-taking, summaries, or routing—helps teams stay focused. That’s where real ROI shows up: faster handling times, less manual effort, fewer errors.

Better Customer Experience

Customers want answers fast, not flash.

AI improves experience by:

  • Instantly handling common questions
  • Connecting people to the right agent the first time
  • Surfacing context, so no one has to repeat themselves

When done right, AI doesn’t feel like AI. It just feels easier.

Actionable Insights

The value isn’t in the dashboard—it’s in what you do with it. AI surfaces trends in:

  • Common complaints
  • Agent performance
  • Customer satisfaction

This helps you coach faster, tweak scripts, and fix issues in near real time.

A Few Leaders (and What to Learn from Them)

These are just a few of the platforms leading the way in making AI genuinely useful—not just flashy:

  • Zoom – AI Companion gives live meeting recaps, action items, and scheduling help.
  • RingCentral – RingSense AI adds transcription, translation, and real-time feedback.
  • Genesys Cloud CX – Predictive routing and AI-assisted coaching are its standouts.
  • Yellow.ai – Multilingual, omnichannel bots that actually work.
  • Dialpad – Known for live sentiment analysis and real-time agent assist.

Don’t just ask what features they have. Ask how those features impact outcomes.

Where to Be Skeptical

Not all AI adds value. Here’s where to keep your guard up:

Adoption Problems: If your team doesn’t trust the tool, it won’t matter how advanced it is. Focus on rollouts that include training and transparency.

Privacy and Compliance: AI systems often need access to sensitive data. That raises real questions about storage, access, and regulation. Make sure privacy is baked in, not bolted on.

Accuracy and Oversight: AI still makes mistakes. Always have humans in the loop—especially in high-stakes or sensitive interactions.

Final Thoughts: Don’t Chase AI—Use It Intentionally

AI is already baked into most communication platforms. The winners won’t be the ones with the flashiest tools—they’ll be the ones who know where and how to use them.

So instead of chasing the next big thing, focus on what matters:

  • What problems are you solving?
  • Where can AI save time or improve service?
  • How will you measure success?

Want help cutting through the hype?

Let’s talk. We’ll help you identify the use cases that actually move the needle—and skip the rest.