Generative AI (GenAI) is currently transforming a wide range of industries – from marketing to software development. And the B2B sales of complex products is no exception.
In fact, the impact of AI in B2B sales is already measurable: According to a recent study (February 2025), AI-supported CPQ systems (Configure-Price-Quote) increase sales productivity, improve forecast accuracy, and significantly speed up quoting processes. Another study shows that by 2026, 30% of G2000 companies will use GenAI in their CPQ and B2B e-commerce systems, reducing their reliance on traditional sales by 30% while boosting profitability by 45%.
But amid the excitement, the critical question is: What can GenAI actually do in B2B sales today, and where is human expertise still essential?
In short: Generative Artificial Intelligence
Generative Artificial Intelligence (GenAI) refers to AI models that generate new content or solutions based on existing data. It can create texts, images, 3D models or complex proposals, using patterns, correlations and probabilities from large amounts of data.
Generative AI is drawing significant attention in B2B sales – especially in the context of CPQ systems.
The promises are compelling: automated configurations, instant quotes, and real-time smart recommendations. But what is actually possible today – and what is still just hype?
Data-driven selling: GenAI can increase conversion rates and revenue by suggesting discounts, copy changes, product bundles, or upsells. For example, it can identify patterns in historical quote data – such as the fact that a 10% discount on a certain component increases win rate by 5% – and apply that insight directly during quoting.
Natural language configuration: Customers or sales reps can describe their needs in plain language (“I need a 200 kW system with a compact enclosure”), and the system automatically generates a valid technical configuration – even if such an option isn’t part of a standard dropdown menu.
Knowledge distribution: GenAI can automatically distribute product knowledge to new hires, reducing onboarding time.
Lead prioritization in CRM: GenAI can assess leads based on likelihood to close and revenue potential, generating to-do lists and prioritizing which contacts should be followed up.
Offer text optimization: Based on successful quotes, GenAI can analyze copy and suggest alternative phrasings with higher conversion rates.
Replace your sales team: Complex negotiations, personalized consulting, and attention to human nuances remain core tasks for your sales staff. In a CPQ environment, GenAI won’t configure “unbuildable” products – it relies on pre-set configuration logic to ensure technical accuracy. The real challenge: Can the AI interpret customer needs correctly?
Operate flawlessly without oversight: Without a clear data foundation and human oversight, GenAI risks making poor recommendations or incorrect pricing decisions. The role of sales is shifting – from creator to reviewer and advisor, ensuring the AI truly understands the customer.
Solve all your data issues:
GenAI is only as good as the data it works with – and for many companies, this is still a major challenge.
GenAI is not a replacement for humans in B2B sales – it’s an amplifier of human capabilities.
Companies that invest now in a clean product and data foundation and define clear use cases can gain major efficiency boosts – like faster quote cycles, better forecasts, and improved win rates.
Next steps for companies with complex product portfolios:
Those who set realistic expectations and act strategically can turn GenAI into a true competitive advantage.
BYRON WELLS
solution manager
DOMINIK SCHMITT
head of web products & software developer
INA ROGALEV
junior marketing manager
This might also interest you
