AI-Powered CPQ – Key Market Trends and the Evolving Competitive Landscape (2025-2028)

AI-driven CPQ is not just an enhancement—it’s a revolution. By 2028, quoting will be automated, predictive, and conversational, fundamentally changing how manufacturers sell. The CPQ market is on a rapid growth trajectory, projected to surge from $2.2 billion in 2022 to $7.3 billion by 2030. Meanwhile, AI adoption is accelerating across industries, with analysts estimating that generative AI could unlock an additional $1.2 trillion in sales and marketing productivity.

These trends are converging, setting the stage for a major transformation in B2B manufacturing sales. The next three years will be defined by AI-driven quoting, predictive pricing, and automation at a scale we’ve never seen before. Companies that embrace AI-powered CPQ will streamline operations, boost profitability, and outcompete those who hesitate. Let’s explore the key trends shaping this shift and how leading CPQ vendors are leveraging AI to gain a competitive edge.

Generative AI and LLMs Transforming CPQ

Large Language Models (LLMs) like GPT-4 and its successors are revolutionizing the way CPQ systems interact with users. Instead of navigating static menus, sales teams (or even customers) can engage with AI-driven CPQ solutions through natural language. Imagine a scenario where a customer simply types, “I need a heavy-duty crane for offshore use with a 15-ton load capacity,” and the AI-powered CPQ instantly configures the best-fit solution, pulling specifications, pricing, and availability in real-time.

Beyond configuration, generative AI is changing how proposals and quotes are created. AI can now draft detailed proposal documents, executive summaries, and even personalized sales emails based on customer data. Salesforce’s introduction of Einstein GPT—a generative AI for CRM—highlights this trend, injecting AI-created content into every stage of the sales cycle. In CPQ, this means faster, richer, and more personalized quoting, reducing manual effort and ensuring consistency.

Predictive Analytics for Smarter Pricing and Sales Insights

AI-powered CPQ is making pricing more intelligent by leveraging predictive analytics. Traditional pricing models often rely on historical sales data and manual input from sales teams. In contrast, AI can analyze thousands of past quotes, customer purchase behaviors, and market conditions to recommend the optimal price for each deal.

For example, a manufacturer quoting a bulk order might receive an AI-suggested discount based on past negotiation trends, customer loyalty, and current raw material costs. Instead of offering an arbitrary 15% discount, AI might recommend 12%, striking the balance between competitiveness and profitability. Companies using AI for CPQ pricing optimization have reported deal sizes increasing by up to 20% due to smarter discounting and upselling recommendations.

Beyond pricing, predictive analytics helps sales teams identify trends before they happen. AI can flag customers likely to need a product upgrade or service renewal, allowing proactive outreach. These insights give sales teams a competitive advantage by shifting from reactive quoting to strategic selling.

Automation and Self-Service in the Quote Process

The future of CPQ isn’t just about making sales teams faster—it’s about enabling customers to generate their own quotes with AI-driven accuracy. Self-service CPQ portals, powered by AI, allow customers to configure products and receive precise quotes instantly. This shift is already underway, with companies like Oracle seeing self-generated quotes skyrocket from 2% to 79% after integrating AI-powered CPQ.

AI-driven automation also streamlines approval workflows. Instead of routing every quote through manual approval, AI can assess risk levels and auto-approve standard configurations while flagging only high-risk quotes for managerial review. This reduces bottlenecks and shortens sales cycles significantly. Additionally, AI-powered visual configuration tools are emerging, allowing customers to see 3D models of their configured products—further enhancing the self-service experience.

The Competitive Landscape: How CPQ Vendors Are Using AI

With AI reshaping CPQ, leading vendors are racing to integrate AI-driven features

• Salesforce CPQ leverages Einstein GPT to automate proposal generation, suggest optimal configurations, and provide predictive pricing insights within the CRM ecosystem.
• Oracle CPQ has transformed its sales process with AI-powered self-service quoting, reducing errors and increasing efficiency.
• SAP CPQ integrates AI with ERP data, ensuring that AI-driven pricing and configuration decisions are always aligned with real-time supply chain conditions.

As AI continues to mature, expect these vendors to push the boundaries of automation, predictive analytics, and conversational CPQ experiences.

What’s Next? The AI-Powered CPQ Revolution Is Here

The CPQ landscape is evolving rapidly, and AI is at the heart of this transformation. In the next three years, we will see:

• AI-powered conversational interfaces replacing traditional CPQ workflows.
• Predictive analytics driving pricing decisions in real-time.
• Self-service CPQ becoming a mainstream expectation for B2B buyers.
• Competitive differentiation based on AI capabilities, with winners leveraging AI for speed, accuracy, and customer experience.

For manufacturers and B2B sales organizations, now is the time to act. AI in CPQ isn’t a futuristic concept—it’s already here, and companies that fail to adopt it risk being left behind. The question is not whether AI will transform CPQ, but how quickly businesses can adapt and capitalize on its potential.

This sets the stage for deeper discussions in the next articles, where we will explore best practices for integrating AI into CPQ and the challenges businesses must navigate.

Want to discuss how AI can elevate your CPQ strategy? Book a virtual coffee with Magnus or Patrik at cpq.se/meetcpqse.