Guest Author: Tom Gorin
In the rapidly evolving landscape of business-to-business (B2B) commerce, the integration of artificial intelligence (AI) is emerging as a game-changer. AI is revolutionizing various facets of business operations, and one significant area of its impact is on pricing strategies. This blog post explores the profound effects of AI on B2B pricing and why it is crucial to understand these changes in today's context.
The Case for Price Drops and Stable Margins
In the January 8, 2025 AI Chat podcast episode (Preparing for AI Agents with John Munsell), host Jaeden Schafer interviews John Munsell of Bizzuka, Inc and LSU. They discuss John Munsell’s experience with AI solutions and share a list of very compelling tools and use cases.
In addition, Munsell shares his perspective on how AI will impact the workforce, which also affects the pricing of goods and services. Specifically, Munsell’s argument is that as AI develops, first movers will greatly benefit from it, reducing their costs and growing their margins.
However, as AI becomes more widespread and the competitive landscape equalizes, these margins may eventually return to their original values, albeit at lower prices. AI adoption will increase competition and create a downward push on prices, eventually leading to a stabilization of margins at levels comparable to pre-AI levels.
In their view, the overall impact becomes an initial increase in margins followed by sharp price declines, stabilizing margins, and a drop in workforce (replaced by AI). However....
An alternative: Improved Margins
While the potential for price drops is significant, there is also a compelling argument that AI can lead to improved margins for B2B businesses. This view hinges on the idea that AI can enhance pricing strategies by providing deeper insights and enabling more precise pricing decisions.
In fact, this is one of the key differentiators that we offer at PROS. Our AI solutions enable our customers to optimize every selling and pricing decision, by leveraging vast amounts of data and identifying patterns and trends that were previously inaccessible, leading to proven revenue and margin improvements of 1-3%. Take Wilbur-Ellis for example, which faced challenges with manual, time-consuming pricing processes that led to outdated prices and inefficiencies in a market with razor thin margin. By implementing PROS Gen IV AI, they achieved real-time pricing for over 6,000 SKUs, resulting in a 2% margin uplift and enhanced pricing precision. Read the full case study here.
AI's analytical capabilities allow businesses to personalize and tailor pricing strategies for each unique customer. Rather than leveraging segmentation, businesses can implement personalized offers and pricing strategies that maximize revenue and profitability.
Furthermore, AI can help businesses identify and address margin leakage. By analyzing historical sales data and identifying patterns, AI can pinpoint areas where margins are being eroded, such as through excessive discounting or inefficient pricing practices.
Beyond margin and revenue, a study by Forbes has also shown that the integration of AI into pricing models can lead to a 20% increase in customer lifecycle value. These improvements are achieved by refining customer and product segmentation (we can discuss the use cases and validity of segmentation in a future blog post), enhancing data quality, and leveraging both quantitative and qualitative insights to make informed pricing decisions that impact far beyond the initial negotiation period.
Where will we end up? A middle ground?
The impact of AI on B2B pricing is not a zero-sum game. While AI can drive prices down through competition and cost savings, it can also enhance margins through improved pricing strategies. The key for businesses is to strike a balance between these two outcomes. McKinsey finds 5-15% revenue potential and 20-40% time saving potential from the adoption of Generative AI solutions in distribution.
To achieve this balance, businesses must adopt a holistic approach to AI-driven pricing. This involves not only leveraging AI to optimize costs and stay competitive but also using AI to gain deeper insights into customer behavior and market dynamics. By doing so, businesses can implement pricing strategies that drive both competitiveness and profitability.
As AI continues to evolve, businesses that embrace its capabilities and strike the right balance will be well-positioned to thrive in the competitive B2B landscape. As this BCG report suggests, there is a long road of opportunity ahead as it relates to AI investments and value.
About the Author
Tom Gorin is the Vice President of AI Strategy & Adoption at PROS. With a PhD from MIT and extensive experience in profit optimization and revenue management, Tom brings a wealth of knowledge to the field of pricing and airline economics. Tom also has over 20 years of experience in managing and leading teams of professionals, and over 10 years of experience in the software industry focusing on big data analytics, sales effectiveness, and pricing and revenue management optimization.