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For pricing departments, artificial intelligence (AI) is no longer a far-flung idea—it's an essential technology shaping the future of pricing. At Sapphire 2025, AI dominated nearly every conversation and vendor showcase. Whether in the expo hall or breakout sessions, AI was emphasized as both an enabler and a driver of pricing transformation. Vendors have made it clear that AI is not optional. It's embedded in nearly every pricing software platform, from optimization tools to quoting engines, and is becoming the foundation for competitive differentiation in pricing.

A few years ago, companies talked about digitizing spreadsheets or moving from cost-plus models to value-based pricing. Now, the conversation has leapfrogged into how to use AI to synthesize internal and external data sources and deliver real-time, predictive pricing recommendations. It's a fundamental shift in what's expected from pricing teams and technology. So, in this article, we outline the most important conversations about AI and pricing.

 

Lessons from Sapphire 2025

The SAP Sapphire conference this year covered a wide range of topics. But one of the most prominent throughlines between all different conversations was AI. So, to loop you in, here are six of the most discussed emerging uses of AI in pricing:

 

1. AI as the Catalyst for Transformation

The biggest shift seen this year is how AI is becoming the centerpiece—not just an add-on—for pricing transformations. Previously, digital transformations moved incrementally: upgrade the ERP, improve master data, and clean up the price waterfall. AI flips this; companies now start their transformation with AI-driven projects because these offer the fastest value realization.

The use of generative AI to analyze patterns, recommend prices, and guide sales teams means companies can capture quick wins early. Pricing software companies showed how their customers are reducing pricing decision times from weeks to minutes by embedding AI across their platforms. 

The bottom line is that AI lets companies move faster and smarter than traditional system upgrades or process changes ever could.

 

2. Tapping into Internal and External Data

Traditionally, pricing relied on internal data: ERP records, historical transactions, and customer segments. But the latest AI tools, layer in external signals too—competitor pricing scraped from websites, commodity price indexes, product specification guides, social media signals, and even public market indicators. This new data blend powers more accurate and adaptive pricing.

This shift—from static internal data to dynamic internal and external data—is enabling companies to become market-responsive rather than reactive.

 

3. Speedy Prototypes: 90 Days to a Working Model

Another major change is speed. Pilot projects with AI can be designed, built, and tested in as little as 90 days. In the past, pricing implementations could take 5-10 months—or more—before anything could be tested. Now, with AI driving modular, scalable solutions, companies can spin up a working prototype quickly.

This opens up a new world of possibilities. For example, a manufacturer struggling with tariff adjustments could build an AI-driven pricing alert system within a few months—not a full platform overhaul, but a focused, high-value pilot. These early wins can build organizational momentum, boost leadership confidence, and prove the technology's value before full-scale deployment.

 

4. Confidence via Staged Deployment

One reason pricing transformations have historically stalled is the fear of breaking things—rolling out a new agreement or quoting tool and not having the sales team trust the guidance that was provided or pushing back on a new approval process. AI reduces that risk by enabling staged deployment: companies can test AI-driven recommendations in specific regions, product lines, or customer segments before full release.

This staged approach allows leadership and sales teams to see value early. When early pilots demonstrate clear results—like reduced quote turnaround or improved win rates—stakeholders gain confidence to scale the solution. AI tools are designed to be modular and expandable, not monolithic, which makes this progressive rollout possible.

 

5. Discovering Hidden Opportunities

AI doesn't just optimize prices—it finds revenue opportunities that human analysts might miss. For example, AI can scan CRM data to spot open quotes or opportunities that sales reps have neglected. It can detect when a key account hasn't been touched in 90 days or when a quote was sent, but no follow-up occurred.

AI surfaces these gaps automatically, feeding sales teams warm opportunities that can immediately boost the pipeline. This capability bridges the gap between pricing and sales execution—AI isn't just setting prices; it's guiding reps to close deals more effectively.

 

6. Proactive Inflation and Tariff Alerts

AI can also solve some of pricing's thorniest problems: managing supplier cost changes, tariffs, and inflation impacts. Rather than waiting for quarterly reviews or supplier updates, AI-powered systems can monitor cost drivers continuously.

For example, if steel prices rise 8% based on global index data, the AI alerts the pricing team—and even recommends specific products or regions that need list price adjustments. This prevents margin erosion from creeping cost increases and ensures pricing keeps pace with market realities.

 

Why It Matters Today

This evolution matters because it solves the three core challenges of pricing transformation:

  • Speed to value: 90-day pilots that deliver measurable results fast.
  • Confidence building: Small, safe deployments that reduce risk and build trust.
  • Revenue growth: Pipeline expansion from surfaced opportunities and price/margin optimization.

For companies wrestling with tariffs, inflation, or competitive price pressure, AI means they can react quickly, optimize continuously, and capture missed opportunities that manual processes simply overlook.

These AI-driven approaches also ease the burden on overworked pricing teams—allowing them to focus on strategy rather than fire drills. And with vendors increasingly making AI central to their platforms, the barrier to entry is lower than ever.

 

Understanding AI and Pricing in 2025

Sapphire 2025 made one thing clear: AI isn't an experiment anymore; it's the new standard for pricing excellence. The smartest pricing organizations are starting small—with 90-day pilots and staged rollouts—but aiming big: full AI-driven pricing transformations that deliver speed, insight, and profit.

If your pricing team isn't already building AI into its plans, you're at risk of falling behind. The time to act is now. Reach out to our pricing solution implementation team for a free consultation. We will offer expert guidance on the best way to integrate AI into your pricing strategy

 

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