Artificial intelligence has been influencing B2B pricing for years, particularly in areas like price optimization and data-driven decision-making. But today, a shift is underway. With the rise of Generative AI (Gen AI), many companies are exploring how to leverage this technology to refine pricing strategies, develop models, segment markets, and extract insights from vast amounts of data. The enthusiasm is growing, but so are the misconceptions.
Common Misconceptions About Gen AI in Pricing
One of the biggest misconceptions is that Gen AI is some kind of “white knight” that will instantly solve a company’s pricing challenges. In reality, technology is only as good as the foundation it’s built on. Many companies still struggle with fundamental pricing issues. Whether it’s their pricing strategy, execution systems, or even how they communicate pricing to the market. Without addressing these foundational issues first, Gen AI cannot magically “fix” pricing.
The excitement around Gen AI is leading to unprecedented innovation, opening new frontiers for pricing functions and promising a future where pricing strategies are more dynamic, data-driven, and precise. Companies are increasingly exploring how Gen AI can be leveraged for specific, high value use cases. These include advanced pricing analytics that detect previously unseen patterns, scenario modeling to simulate the impact of pricing changes in real time and identifying key value drivers that influence customer purchase behavior. Gen AI can even be used to assist in price strategy creation by synthesizing vast amounts of market data and competitive insights.
However, while these capabilities are promising, they come with significant caveats. AI-generated insights need rigorous validation. The known phenomenon of AI hallucinations, where AI can produce misleading or incorrect (while simultaneously compelling and convincing!) information, means pricing professionals must critically evaluate AI-driven recommendations, ensuring their accuracy and alignment with business objectives rather than blindly trusting them.
The Role of Human Oversight in a Gen AI-Driven World
This need for validation reinforces why having a human in the loop (HITL) remains essential. Despite all its capabilities, Gen AI is not yet at a point where it can autonomously make pricing decisions with full accuracy. Given the risks associated with incorrect pricing, whether it's lost revenue, margin erosion, or damaged customer relationships, businesses can’t afford to leave these decisions solely in the hands of AI.
Instead, pricing teams should see Gen AI as a thought partner; a tool for generating ideas, validating assumptions, testing theories, and even performing analytical tasks. But when it comes to setting and defending prices, human expertise is irreplaceable. Pricing professionals must be able to justify pricing decisions to internal stakeholders, sales teams, and customers. If their only justification is "because Gen AI said so," they risk eroding trust and credibility across the organization.
Adapting to Change: How Pricing Professionals Must Evolve
As the pricing landscape continues to change, the role of pricing professionals will evolve. They may no longer be directly responsible for running every analysis themselves, as AI-driven tools will be able to handle much of the execution. However, their expertise will still be required to ask the right questions, interpret AI-generated insights, and validate recommendations.
Key skills that will become increasingly critical include:
- Prompt engineering – Knowing how to frame precise and insightful questions to extract useful outputs from AI.
- Critical thinking – The ability to analyze AI-generated suggestions and identify potential biases or inaccuracies.
- Strategic communication – Explaining AI-assisted pricing decisions in a way that builds trust with internal and external stakeholders.
- Contextual application – Applying their experience to the specifics of a given situation, allowing them to either follow a Gen AI recommendation or take it with a grain of salt.
In other words, the most successful pricing professionals will be those who can blend their deep industry expertise with AI fluency, using Gen AI as a force multiplier rather than a replacement.
The Need for Upskilling: Why Pricing Professionals Must Start Now
Companies that want to stay ahead should begin upskilling their pricing teams now. This doesn’t have to be a massive overhaul. It can start with something as simple as:
- Introducing teams to widely accessible Gen AI tools.
- Training them on how to effectively prompt and interact with Gen AI.
- Encouraging them to use Gen AI for low-risk tasks like brainstorming and analysis.
- Ensuring teams are aware of the potential to introduce bias into pricing processes that leverage Gen AI. (Look for a future blog on this topic!)
By allowing pricing teams to experiment with Gen AI in a controlled, low-risk environment, companies can build familiarity and confidence with the technology while ensuring they remain in control of the decision-making process.
The Future of Gen AI: An Enabler, Not a Replacement
Despite its rapid advancements, Gen AI is still far from replacing humans in the field of pricing. Ethical concerns, compliance requirements, and the need for explainability will ensure that humans remain accountable for pricing decisions for the foreseeable future. Gen AI may assist, but it cannot be held responsible for a company’s pricing strategy.
Final Thoughts and Key Takeaways for Pricing Professionals
Don’t fear AI, embrace it! Whether you want it to impact your role or not, it will. To stay competitive, consume as much information as you can, stay up to date on developments in Gen AI, and start testing real-use applications. The more you familiarize yourself with the technology, the more confident and effective you’ll be in leveraging it for pricing success.
Ready to see how Gen AI can empower smarter decisions? Contact us today to learn how Zilliant Gen AI Pricing Analytics can transform your pricing strategy.
Matthew Knaggs is a Senior Business Value Lead at Zilliant, where he works with customers and prospects to demonstrate the ROI and business impact of implementing Zilliant solutions.
