Introduction
This article shows how AI can modernize your CPQ to streamline workflows, reduce manual effort, and drive faster, smarter sales.
Sales teams are drowning in clicks, bogged down by outdated CPQ systems that feel more like obstacle courses than tools. Built to streamline quoting and pricing, most have become productivity killers—clunky, complex, and costly. But a seismic shift is underway. Enter Agentic AI: intelligent, task-savvy agents that promise to reinvent CPQ by turning hours of quoting into minutes, slashing errors, and unlocking a smarter, faster path from prospect to proposal.
The Struggles of Traditional CPQ
While CPQ applications have successfully digitized the sales process, they’re still far from frictionless. In fact, across industries—from telecom to high-tech to medical devices—sales teams continue to battle outdated systems that demand way too much cognitive effort. The result? Sales reps are stuck in a constant state of mental overload, navigating complex tasks and endless clicks.
Based on our experience working with multiple clients, becoming fully proficient with these systems can take anywhere from 6 to 12 months of training—an investment that often gets wasted as high employee turnover (20-25%) demands constant and costly training to on-board new sales reps. Big enterprises are feeling the pain the most, with some spending as much as $30,000 per rep just to get them up to speed on a convoluted CPQ system.
But the frustrations don’t end there. Sales teams regularly face user experience nightmares: an average of 45-60 clicks to create a basic quote, navigating through 8-12 different screens, and learning a maze of steps to accomplish simple tasks. It’s no wonder most salespeople see CPQ as a necessary evil—it’s one of the most time-consuming parts of their job.
And then there’s the challenge of product selection. In a world where sales teams are expected to know hundreds—if not thousands—of products inside and out, staying on top of it all is nearly impossible. Only 12% of sales reps feel confident they know their company’s full product lineup, forcing them to rely on specialized experts to guide their decisions. The result? A costly web of sales support specialists that can drive up sales costs by 35%.
How AI Can Revolutionize CPQ
AI-powered CPQ is the future—and it’s here to tackle the inefficiencies holding sales teams back. Picture this: instead of juggling endless clicks and complicated workflows, you have a personal AI assistant that effortlessly handles the heavy lifting. Let’s take a look at how an interaction between John Sellars, a sales rep at a telecommunications carrier and his personal AI assistant this plays out in action:
With the AI-powered personal assistant, it took a few short instructions instead of over 5000 clicks required to create the quote for Acme. Saving time, reducing errors, and making the whole process feel like a breeze.
Peek Behind the Scenes of AI in CPQ
Let’s take a closer look behind the exchange between our sales rep, John Sellars, and the AI Assistant to understand how AI agents completely transform the way CPQ systems capture and process orders:
Intelligent Task Automation:
The AI Agent is trained to handle the entire quote creation process—from associating the quote with an open opportunity for Acme to finalizing the details. Instead of clicking through 25+ steps, a single conversation with the AI gets it done.
Data-Driven Recommendations:
AI doesn’t just populate values for different fields on Quote and Quote Line Items—it actively boosts sales. By analyzing customer history, industry benchmarks, and complementary products, AI increases sales through tailored product recommendations. Companies such as Verizon have seen a 40% sales uplift through deployment of agents supporting customer reps.
Autonomous Configuration:
The AI takes care of the heavy lifting:
Finds addresses for Acme’s regional offices, saving 5-7 minutes of manual search
Determines connection types (Fiber or COAX) and bandwidth for each location
Configures connection types, bandwidth values, modems, and optional security products automatically for every office
Adds 10 offer configurations to the quote in one fell swoop
Click Reduction:
Where sales reps might have clicked through 5,000+ times, the AI Agent condenses it into a single click.
Advisory Role:
The AI doesn’t replace the salesperson; it partners with them. It ensures instructions are accurately interpreted and allows for adjustments as needed while ensuring high accuracy.
With AI on your side, sales reps can focus on closing deals faster and kiss goodbye the frustration of manual offer configuration and quoting.
Getting Your CPQ AI-Ready: What Needs to Change
If you’re serious about unlocking the power of AI in your CPQ stack, it’s not just about plugging in a chatbot. Legacy systems need some critical upgrades to support agentic automation that’s fast, smart, and scalable.
1. Rethink the User Experience (UX)
To earn user trust, AI needs to feel like a co-pilot—not a black box. Here’s what users want:
Hybrid UI that mixes smart AI suggestions with a manual override
Visual confirmation of AI actions to increase trust
Step-by-step visibility to cut error rates
Bottom line: If your AI is going to make decisions, users need to see—and believe—what it’s doing.
2. Upgrade the Backend: Fast, Flexible, API-First
That smooth AI-powered interaction we walked through earlier? Behind the scenes, it’s powered by a flurry of backend service calls:
Pulling open Opportunities
Creating Quotes tied to Opportunities
Looking up Service Accounts and office locations
Running product recommendations
Checking serviceability (e.g. access type, bandwidth)
Configuring the Business Internet offers
Adding 10+ configured products to the quote
To support dynamic AI workflows like this, your backend systems need well-documented, high-performance, and scalable APIs.
3. Define Smart Agent Autonomy
Should AI agents just act, or ask first? The answer: it depends.
For high-stakes actions (e.g. deals over $10K), requiring confirmation reduces the risk from errors
For routine stuff, letting agents act autonomously boosts efficiency
The sweet spot? A tiered autonomy model that adapts based on risk and complexity
Think of it like giving your AI a driver’s license—with different rules for highways and parking lots.
4. Go Multi-Agent, Not Monolith
Don’t make one agent do everything. Split the work:
Specialized agents for product recommendations, configurations, pricing, approvals, and more
Multi-agent systems can deliver better performance in complex sales
Focused agents show higher accuracy in their niche
Use a central orchestration layer to coordinate agents and keep everything humming—this reduces integration headaches
This modular setup also makes it easier to evolve, reuse, and scale your AI over time.
5. Plan for Mistakes: Bulletproof Your Error Handling
AI isn’t perfect. So build smart safety nets:
Transaction logs for instant rollbacks → 84% faster recovery
Business rule validations to stop bad quotes before they go live
Anomaly detection to flag weird configs before they hit a customer
Your AI needs the same kinds of guardrails your team would expect from a seasoned sales ops pro.
The Bottom Line?
Smart UX, scalable APIs, modular agents, and rock-solid error handling aren’t just “nice to have”—they’re the foundation for an AI-powered CPQ that actually delivers on its promise.
Operationalizing AI: Making the Business Case
Operationalizing AI: Making the Business Case
As you embark on your AI journey, expect to be asked for a business case for operationalizing your AI efforts.
Here are some metrics to track the cost and benefits of AI deployment—impacting both top and bottom lines:
Costs to Consider:
Recurring software and service licensing fees
Consumption costs (e.g. LLM usage, API calls)
Ongoing support (enhancements, bug fixes, support personnel)
Implementation costs (initial development, testing, deployment, training)
Top-Line Benefits:
Reduction in number of clicks — extrapolated to time savings and productivity gains
Increase in deal size (e.g. higher ARPU in telecom)
Improved Return on Ad Spend (ROAS) in ad sales
Faster ramp-up time for new sales reps
Higher sales productivity
Increased cross-sell and upsell effectiveness
These metrics speak for themselves. Companies that embrace AI-driven CPQ will see measurable gains across the board.
Get in touch with CRMantra to prepare your business case and get results.
Conclusion: CPQ, Supercharged by AI
AI isn’t just improving CPQ—it’s reinventing it. The once clunky, click-heavy quoting process with undifferentiated UX becomes fast, intelligent, and frictionless. With AI in play, sales teams gain:
Less cognitive overload
Smarter product recommendations
Quotes in minutes, not hours
More time selling, less time clicking
And we’re just scratching the surface. As AI agents get more advanced, CPQ will shift from a sales tool to a strategic growth engine.
If staying competitive matters, AI-powered CPQ isn’t optional—it’s the next move. We’re all in on this transformation—and we’re here to learn, share, and lead the way forward.
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