Blog
AI
Contact Center
Voice
Agentic AI
AI isn’t just a buzzword anymore; it’s becoming a part of how humans and machines communicate on a daily basis. And while generative AI grabbed the initial spotlight, a more powerful evolution is reshaping how enterprises actually get work done: agentic AI.
If you lead, build, or manage enterprise communications, this is the shift you need to understand. Let’s break down what agentic AI is, how it differs from generative AI, and why it’s already transforming the way brands connect with customers.
What is agentic AI?
Agentic AI refers to AI systems that reason, plan, and autonomously execute multi-step tasks across systems with minimal human oversight. If generative AI is a brilliant assistant that creates things when you ask, agentic AI is a capable colleague that gets things done on its own.
The simplest way to think about it: generative AI creates output. Agentic AI creates outcomes.
An agentic AI system can take a high-level goal (say, “resolve this customer’s billing issue”) and break it down into a series of actions: verify the customer’s identity, pull up their account, identify the problem, apply a credit, send a confirmation message, and log the interaction. All with reduced human intervention and the ability to hand off to a human when needed.
Gartner predicts that agentic AI will autonomously resolve 80% of common customer service issues by 2029. That’s not a distant fantasy. It’s a roadmap that enterprises are already building toward.[1]
How is agentic AI different from generative AI?
Generative AI helps people produce, while agentic AI helps organizations perform. These two terms are constantly lumped together, but they serve very different purposes.
Generative AI is reactive. It responds to prompts and produces content: text, images, code, and audio. It’s excellent at creation, summarization, and analysis, but once it gives you the output, its job is done. You’re the one who takes the next step.
Agentic AI is proactive. It uses generative models as a foundation but adds the ability to reason through problems, interact with external systems, and take action, often across multiple tools and platforms simultaneously. It doesn’t stop at the draft. It sends the email, updates the record, and moves to the next task.
Read more: Know your AI: The difference between agentic vs. generative AI
Where agentic AI shows up in communications
Agentic AI is already making a real impact in enterprise communications, particularly in the contact center, where complex, multi-step customer interactions happen thousands of times a day.
Here’s why this matters: the contact center has been layering AI onto its operations for years via chatbots, sentiment analysis, and call transcription. But most of those tools still require notable human in the loop intervention to actually do something with the output. Agentic AI changes the game by closing that gap between insight and action.
Here’s where agentic AI shows up in communications:
Intelligent call routing and resolution. Instead of routing a call based on a menu selection, agentic AI can analyze a customer’s request, identify likely intent based on available context, work with the systems, and trigger actions. When a request is too complex, it can hand off to a human agent and provides the full context of what’s been shared so the customer doesn’t have to repeat the entire process.
Proactive customer engagement. Agentic systems can monitor account activity, detect patterns, and take action before the customer calls. These include missed payments, unusual charges, or subscription renewals.
Cross-system orchestration. This is where agentic AI really flexes. It can coordinate actions across CRM, billing, telephony, and messaging platforms in a single workflow—something that previously required multiple agents, multiple tools, and many manual handoffs.
Real-world brands putting agentic AI to work
Major brands are already deploying agentic AI in their communications stacks and seeing real results. Responsible organizations are also ensuring that their customers know when they’re interacting with AI.
Salesforce is using its own Agentforce technology to deploy AI agents across customer-facing and internal operations. At Bandwidth’s Reverb25 event, Salesforce’s Senior Director of Product Management, Swati Deo, shared how the company deployed AI agents on its help sites, which serve 60 million customers across 740,000 knowledge articles, and saw those agents resolve more than 85% of customer inquiries, leading to a 65% reduction in response times.
Salesforce also deployed AI agents internally via Slack for HR and IT cases, demonstrating how agentic AI works on both sides of the organization. (Read the full Salesforce story →)
Wyndham Hotels & Resorts, the world’s largest hotel franchisor, partnered with AI platform Canary and Bandwidth’s Maestro to deploy voice AI across its properties. The system routes calls seamlessly between Wyndham’s CCaaS platform (Five9) and Canary’s voice AI, giving guests instant, personalized responses around the clock.
As Joe DeLuca, Director of Voice Contact Center Systems at Wyndham, put it: “It’s provided a de facto DR where we’re able to maintain the continuity in our dial plan and ultimately mitigate vendor lock-in.””After a successful pilot across hundreds of properties, Wyndham rolled the technology out globally. (Read the full Wyndham story →)
Genesys, a global leader in experience orchestration, is expanding its AI-driven communications infrastructure internationally with Bandwidth. Their approach connects data, AI, and human interactions on the back of ultra-low latency, secure number provisioning, and built-in compliance controls, enabling enterprises to deliver consistent, intelligent customer experiences across regions. (Read the full Genesys story →)
What all three have in common is that they’re not just adding AI to their existing stack. They’re rethinking how conversations happen, how systems connect, and how much of the customer journey AI can own.
Why the communications layer matters for agentic AI
Agentic AI in communications is only as good as the infrastructure it runs on.
When an AI agent handles a live voice call (verifying identity, pulling up account data, taking action on a customer’s behalf), the telephony underneath needs to be fast, reliable, and compliant. And in regulated industries, a gap in call recording or data handling can create real problems.
This is where Bandwidth operates. As the communications platform powering voice, messaging and AI integrations for some of the world’s largest enterprises, Bandwidth provides the infrastructure that makes agentic AI work in real-world customer interactions.
Bandwidth’s AI capabilities are built around flexibility. The Bring-Your-Own-AI model lets enterprises connect any AI engine (OpenAI, Canary, Cognigy, or a custom solution) directly into their voice infrastructure via SIP or programmable APIs. That means no vendor lock-in, full control over call routing, and the ability to evolve your AI stack as the technology (and your business) changes.
The AI will keep getting smarter. The question is whether the communication layer underneath can keep up—with the speed and reliability that enterprise conversations demand.
[1] – Gartner Predicts Agentic AI Will Autonomously Resolve 80% of Common Customer Service Issues Without Human Intervention by 2029, March 2025
The information provided in this glossary definition does not, and is not intended to, constitute legal advice, nor does it necessarily represent Bandwidth's products or business practices. This page is for general informational purposes only.Related posts
Blog
AI
Contact Center
The Agentic Pivot: Redefining enterprise communications in the era of orchestration
Blog
Security
Voice
How Bandwidth combats illegal robocalls, scam calls, toll fraud, and spam
Checklist
Contact Center
Voice Channel Risk and Trust Scorecard
