Are You Prepared for Agentic AI and How to Sell It? Here's What You Need to Know.  

By Sam Nelson, VP of CX, and Koby Phillips, VP of Cloud 

Companies of all sizes today are continuously challenged to provide personalized, seamless customer support at scale. To win and thrive, they must immediately act on insights and deliver exceptional experiences that align with customers’ rapidly changing needs. Yet, a divide persists between customer experience (CX) and cloud operations, making it difficult to execute and respond with high-value services.

That’s quickly changing, thanks to agentic AI—a breakthrough technology that empowers companies to act with lighting speed, precision, and unprecedented agility.

Read on to learn what agentic AI is all about, how it applies to CX and cloud sales, and how it can drive better outcomes for lasting customer trust.

What is Agentic AI, and Why Should You Care?

Agentic AI refers to an emerging class of AI systems that interact with users and systems with autonomy, deep reasoning, and an ability to act independently toward achieving complex goals.

Unlike traditional AI, agentic AI behaves like an active agent—setting goals to achieve objectives, while quickly learning and adapting to changing conditions. Some of the top emerging use cases right now for agentic AI include customer support automation, IT and cloud operations, sales assistance, business process automation, and software development support.

According to Gartner, agentic AI will autonomously resolve 80% of common customer service issues without human intervention by 2029—leading to a 30% reduction in operational costs.

“Agentic AI is poised to revolutionize the way service interactions are conducted,” Gartner says. “While previous AI models were limited to generating text or summarizing interactions, agentic AI introduces a new paradigm where AI systems possess the capability to act autonomously to complete tasks.”
The main thing to understand about agentic AI is that it doesn’t just answer questions—it takes action. For example, imagine instructing an AI agent to help a customer upgrade to premium, and watching as it does its magic:

• Analyzes usage data. 
• Sends a personalized email with upgrade benefits. 
• Sets a meeting with an account representative. 
• Spins up a demo environment—all without human intervention.  

Did you know? Agentic AI is often referred to as the “third wave” of AI.
AI has evolved considerably in recent years. First, we had systems that predicted behavior, then conversed like humans, then generated content. Now we’re entering the agentic era – or the “third wave” of AI that acts autonomously to achieve goals.

• First wave: Rules-based AI  
• Second wave: Statistical/ ML-based AI 
• Third wave: Agentic AI/ reasoning 

The Core Building Blocks of Agentic AI 

Agentic AI is built on several foundational pillars: 

• Setting goals: Providing the agent with clear objectives and directions. 
• Planning: Breaking down complex missions into individual steps. 
• Memory: Internalizing instructions and applying contextual information. 
• Reasoning: Understanding the mission and making informed decisions.     
• Executing: Completing tasks to achieve defined outcomes. 
• Analyzing: Monitoring results and reacting to outcomes. 

To better understand how this all comes together, let’s break agentic down into three pieces of the AI “brain” that all contribute to an AI-driven experience. 

1. Predictive AI – The Brain That Plans Ahead 

What it does: Analyzes data to forecast what’s likely to happen. 

Impact: Helps clients proactively meet needs instead of reacting late. 

Example: A SaaS provider uses predictive AI to flag accounts likely to churn. An agentic AI then notifies the account manager, schedules a check-in, offers a personalized discount or training session. Now you’ve turned a risk into a retention — automatically. 

2. Conversational AI – The Brain That Listens and Speaks 

What it does: Understands and responds to human input naturally. 

Impact: Reduces friction, increases accessibility, and speeds up decision-making. 

Example: An agentic AI embedded in a customer portal chats with users about product issues. Based on the conversation, it identifies the root cause, escalates the ticket if needed, and solves the issue on the spot with links, documentation, or automated fixes. For the client, that means fewer supported tickets, faster resolution, and happier customers.  

3. Generative AI – The Brain That Creates 

What it does: Produces new content—text, code, graphics, workflows.  

Impact: Saves hours of manual work and enables rapid iteration. 

Example: A marketing team wants a new product landing page. The agent writes the copy, generates banner visuals, optimizes SEO metadata, and pushes it live via CMS integration. The marketing team is able to reduce launch time from weeks to hours — providing more time to focus on refining and enhancing materials and responding to other pressing needs. 

Governance: A Fundamental Need for Agentic AI 

Agentic AI represents a major technological leap forward, by granting AI systems the ability to independently interact with systems, data, and even customers.  

This new level of autonomy demands a heightened focus around trust, accountability, and autonomy controls. Companies must actively monitor agentic systems, establish clear boundaries and guardrails, and implement policies to ensure safety, compliance, and ethical behavior.  

For technology advisors, this shift creates yet another opportunity to provide strategic guidance—helping customers adopt agentic AI safely and connecting them to governance frameworks and services that minimize risk.  

Is Agentic AI Fully Available Yet? 

We are now in the early stages of agentic AI, with companies just starting to experiment with new tools and services. However, things are moving quickly in this space and you’ll want to get ahead of the opportunity before your competition. 

According to the latest research from digital automation provider SS&C Blue Prism, 29% of organizations are now using agentic AI 🡥 for automation, while 44% plan to implement it within the next year. A separate study from Deloitte also found that “among all the emerging GenAI-related technological innovations, agentic AI🡥 currently appears to be capturing the most interest and attention.”  

Deloitte’s survey found the two most interesting areas today are agentic AI (52%) and multiagent systems (45%), which Deloitte describes as a more advanced, complex variant of agentic AI. There is also strong interest in multimodal capabilities (44%), new training techniques (45%), and smaller, less resource-intensive models (35%).  

Some of the early leaders in agentic AI include: 

• Salesforce Einstein Copilot for CRM 
• Microsoft 365 Copilot  
• ServiceNow “Now Assist” Agents  
• UiPath Autopilot 

Keep in mind that the agentic AI space is rapidly changing. Keep your eye out for new tools and services as the year progresses. By this time next year, an entirely new set of optimized solutions will be available. 

Agentic AI: A Key Enabler for CX and Cloud 

As a technology advisor, you’re in a unique spot to connect strategy with execution.  

Agentic AI transforms customer insights into autonomous actions, bridging the gap between knowing what customers need and delivering it, instantly and intelligently. 

It’s important to understand that this isn’t just about automation—it’s actual decision-making. When cloud services can adapt in real-time to customer needs, it unlocks agility we’ve only talked about in theory. Agentic AI eliminates the guesswork in CX and cloud sales, enabling a much deeper understanding of customer needs within cloud-based systems and autonomously acting on those insights to drive outcomes.  

Think of agentic AI as the connective tissue between CX and cloud, bringing together data, decisions, and action under one intelligent system—creating faster wins for your teams, and more value for your clients. 

Agentic AI helps to: 

• Bridge the gap between CX and cloud. 
• Eliminate silos between tools and teams—one agent can serve both sides.  
• Offer higher-value services.  
• Design and deploy agent-based workflows for onboarding, support, upselling, and provisioning.  

As a bonus, agentic AI will also increase client stickiness. Once an agent is embedded into the client’s flow, it becomes mission critical.  

Key Personas Who Benefit: 

• Sales reps: Offload admin tasks, personalize outreach, and close faster.  
• CX leaders: Automate insights-to-action workflows and improve NPS. 
• Cloud architects: Enable no-touch provisioning, scaling, and monitoring.  
• Tech advisors: Position AI not just as a tool, but as a strategic agent. 

Agentic AI in Action: How Agentic AI Transforms the Client Journey 

Now that you have a solid understanding of agentic AI, let’s connect the dots and see what this looks like in the real world for your customers. 

Use Case #1: Smarter Sales Enablement  

Imagine a CX team sees that a lead has interacted with multiple knowledge base articles—but hasn’t yet converted.  

Agentic AI can create a custom email sequence based on the lead’s activity, book a meeting with a rep, and generate a tailored pitch deck. If the deal closes, the agent can even provision a trial environment via the cloud team.  

Result: Smarter outreach, with faster onboarding.   

Use Case #2: Proactive Support Across Channels 

In this example, a client hits a bug, requiring immediate support.  

Instead of waiting for them to file at ticket, agentic AI will detect the issue from app logs, generate a fix, notify the client with a status update via Slack or email, and follow up to confirm a resolution. 

Result: Support becomes proactive, instead of reactive. Client trust skyrockets. 

Use Case #3: Rapid Cloud Resource Provisioning 

A partner requests a sandbox to test integrations—expecting the process to take several weeks or longer to execute. 

Agentic AI will predict the right architecture based on previous partner environments, generate infrastructure-as-code, and automatically deploy the environment securely, with access controls in place.  

Result: Request to deployment in under 30 minutes. No delays. No tickets. No security issues. 

Final Thoughts: One AI Agent, Endless Possibilities  

The leap to agentic AI is similar to the jump from radio to television in the early 20^th century. With earlier forms of AI, customers gained insights and productivity improvements. But with agentic AI, they will see tangible results—tasks being completed in real-time, complex workflows becoming fully automated, and next-generation customer experiences that were once thought to be impossible. 

Just how powerful is agentic AI? Here at Telarus, our advisors are already seeing some clients reduce onboarding times by 70%. It’s like giving your customer an extra brain and a pair of hands that never sleep. 

So don’t wait for your customers to start asking about agentic AI. As a technology advisor, it’s time to familiarize yourself with the next wave of AI technologies that are coming to market and start looking for ways to integrate them into your customers’ environments and solve CX challenges.  

The agentic AI era is officially here, and things are about to get much more interesting. Let’s use this opportunity to build smarter, together.  

For further reading, check out Sam’s blog post: From Generative to Agentic: The Evolution of AI in CX in 2025.