Inside Cegid’s Quote-to-Cash transformation

Cegid has always been in the business of reinvention. The company is a leader in cloud management solutions for finance (ERP, treasury, tax), human resources (payroll, talent management), accountancy, retail and entrepreneurship. With a solid full cloud business model, Cegid provides long-term commitment to its customers, superior and distinctive experiences and helps companies of all sizes accelerate their digital business transformation, locally and worldwide.

Cegid combines a forward-thinking and pragmatic approach of the business with strong capacity to innovate, an in-depth expertise in new technologies such as artificial intelligence, and an understanding of regulations and compliance.

In today’s rapidly changing world, Cegid makes more possible by helping customers unleash their potential thanks to innovative and purposeful business solutions. Bolstered by its strong international ambition, Cegid sells its solutions in 130 countries.

Providing management software for over 750,000 customers, the tech giant pioneered the shift from on-premise software to modern SaaS models in Europe. That transformation wasn’t just about technology; it forced a complete rethinking of how software is priced, packaged, and delivered.

Today, however, a second transformation in software is underway: stand-alone AI services. It’s undoubtedly a huge opportunity, but it’s also fraught with questions: What’s the actual demand? How much are customers willing to pay? Do flat-rate subscriptions still make sense, or should you charge by usage and API calls? How do you differentiate your AI offering from the tech giants?  

The company’s new AI offering, Cegid Pulse, are AI-driven intelligent agents that let customers automate tasks, find real-time insights, and even facilitate natural language interactions in retail stores.

As Cegid CEO Pascal Houillon recently told our Subscribed conference:

Spearheading this shift is Mélanie Septe, Senior Vice President of Pricing, who has played a pivotal role in shaping Cegid’s customer-centric approach. 

“You know, I’m a French woman,” says Mélanie Septe. “And it’s a time of revolution. Fortunately, I think the greatest ideas have emerged during revolutions.”

This isn’t an easy model to get right. As Mélanie notes, AI shatters the traditional subscription model. There are no “users” in the conventional sense. No seats to count. No easy way to measure consumption. So how do you charge for intelligence?

For Cegid, this is more than just a pricing challenge—it’s a full-scale business transformation. Below, we explore five hard-earned lessons from Cegid’s AI-powered monetization revolution.

1. Software was simple. SaaS was complex. AI? It’s an entirely new game.

When Cegid first moved to SaaS, pricing revolved around per-seat, per-month models. That worked—until it didn’t. As customer demands shifted, so did pricing. Annual contracts, usage-based tiers, and value-based pricing all became part of the mix.

Now, AI has broken the old models. It doesn’t matter how many people use it—it’s about the value AI delivers. Cegid realized quickly that sticking to old pricing frameworks would limit adoption and revenue potential.

Cegid eventually landed on an outcome-based pricing strategy for their AI offering, but as we’ll see, that was a result of a huge amount of experimentation to determine how and why their customers used their new service. In short, they had to determine their value metric before they could accurately price it. 

Surprisingly, outcome-based pricing is currently only used by about 6% of companies with GenAI offerings, but we predict a huge shift towards these kinds of AI pricing strategies in the future. Cegid is at the forefront of this shift.

Key takeaway: Be prepared to burn your old playbook. The pricing models that got you here won’t take you forward. You’re probably going to have to pursue a hybrid model that looks very different from the current ChatGPT, Perplexity, or Anthropic flat consumer rates.

2. Taming the impossible triangle: Balancing cost, adoption, and value

Pricing AI is like trying to solve a puzzle where the pieces keep changing shape. The Subscribed Institute’s Michael Mansard calls it “The Impossible Triangle”—where cost, adoption, and perceived value must all align. As Mélanie notes: 

“Price AI too high, and adoption suffers. Price it too low, and you erode profitability. Customers need time to recognize AI’s value—but they also don’t want surprises in their bill.”

Cegid experimented relentlessly—testing invoice-based models, transaction-based pricing, and usage-driven fees. Some worked. Others didn’t. The key was staying flexible enough to pivot without overhauling their entire billing system.

With Zuora’s dynamic pricing engine, Cegid can:

• Test new pricing structures in real-time—without disrupting customer experience
• Automate contract modifications—adjusting AI pricing as customer needs evolve
• Optimize revenue forecasting—aligning financial planning with actual AI usage

 

Key takeaway: Iterate. AI pricing is new territory—don’t lock yourself into a model that might not work in 12 months.

3. Order-to-Cash is now a strategic differentiator

Pricing models are only as strong as the infrastructure supporting them. Cegid knew that to embrace AI monetization, it needed a financial operations stack that could adapt to new business models—without introducing friction for customers.

For over a decade, Zuora has been the foundation of Cegid’s monetization strategy. Initially, it supported the company’s transition from license-based software to SaaS subscriptions. But as AI entered the equation, Zuora’s dynamic billing, revenue recognition, and CPQ integration became even more critical.

By integrating Salesforce CPQ with Zuora, Cegid was able to:

• Sync quote-to-cash data in real-time—reducing manual errors and eliminating revenue leakage
• Provide flexible billing options—usage-based, invoice-based, and outcome-driven models
• Ensure revenue compliance and automation—removing the burden of manual accounting

 

Key takeaway: AI doesn’t just change how software is built—it changes how it’s bought. A modern order-to-cash system must be dynamic, scalable, and built for experimentation.

4. AI monetization requires a unified back office and front office

Monetization isn’t just a Finance problem—it’s a cross-functional challenge. Pricing, Sales, and Customer Success all need to align on how AI is packaged, billed, and communicated.

Cegid’s key insight? A seamless back office fuels a great customer experience.

By leveraging Zuora’s billing and revenue automation, Cegid ensures:

• Finance teams have real-time visibility into customer contracts and usage
• Sales teams can customize pricing models without breaking accounting rules
• teams can proactively address churn risks by monitoring AI adoption trends

“The alignment between our front office and back office is what makes this work,” says Mélanie. “Zuora gives us the agility to experiment with new monetization models, without breaking our core business operations.”

Key takeaway: A modern finance stack doesn’t just automate—it unlocks growth.

5. The next phase: AI-powered subscription growth

Cegid has successfully navigated one transformation—from software to SaaS. Now, it’s embracing its next innovation—AI-driven monetization.

This shift isn’t just about pricing differently—it’s about thinking differently.

“As much as I want to believe pricing is a science,” Mélanie notes, “AI pricing is as much a leap into the unknown as it is data-driven. We’re figuring it out in real time.”

Zuora continues to play a critical role, ensuring Cegid can scale AI-driven monetization models while maintaining revenue integrity.

Key takeaway: AI is reshaping the future of SaaS monetization. Companies that embrace financial agility will have the edge.

Transformation is never easy—But always worth it

Cegid understands what it takes to lead a transformation. It has done it before.

As more SaaS companies rethink their pricing models for AI, Cegid’s approach serves as a blueprint for navigating the uncertainty—while ensuring long-term revenue growth, customer adoption, and financial stability.

Because at the end of the day, it’s not just about selling AI—it’s about building a business that’s ready for what’s next.