AI’s soaring costs are reshaping SaaS pricing, monetisation strategies: Nicole Segerer, Revenera

Artificial Intelligence (AI) is reshaping the Software-as-a-Service (SaaS) industry, not just in how companies build and deliver software but in how they make money from it. As AI-driven features become more common, software providers face a new challenge, how to price and monetise these capabilities without driving up costs or losing customers. Many are shifting to usage-based and hybrid pricing models to stay competitive. 

Revenera, a US-based company specialising in software licensing and monetisation, is helping SaaS businesses navigate this shift. In a conversation with TechCircle, Nicole Segerer, SVP & General Manager, Revenera, discusses AI’s impact on software pricing, operational efficiency, and customer insights. She also highlighted the growing role of India in AI development and why SaaS companies are moving away from in-house monetisation tools in favour of automated solutions. Edited Excerpts:

Where do you think AI is heading in the SaaS landscape? 

I have a global perspective, but I believe the view from India isn't much different. Over the past few years, there's been significant progress in structuring and making data more accessible. This has enabled AI advancements, and India has become a key hub for strategy and development, both for us and many other software companies. What we’re doing aligns with what most companies in the industry are pursuing. 

We’re leveraging the data in our SaaS solution to help customers gain insights through AI. This includes learning from past data, building predictive models, speeding up data access, and answering questions. That’s the generative AI aspect. Then there’s the agentic AI side, where we improve operational efficiency by automating workflows and reducing human intervention. India plays a crucial role in our AI development, with deep expertise in this space. 

Another area Revenera is involved in is AI monetisation. As software companies develop AI solutions, they need to figure out how to make them profitable. The industry is undergoing a major shift, extending the broader cloud transformation of the last decade. SaaS companies already have high cloud expenses, and adding AI solutions increases costs, especially for highly transactional models requiring significant compute power. 

This is driving a shift in software monetisation. Companies are adopting token-based or usage-based pricing to support a consumption-driven model for AI. Since profitability is key, few companies can afford to operate at a loss. To sustain AI offerings, they must find ways to monetise effectively, and that’s where Revenera helps, by enabling these models for our customers.

What challenges do enterprises face when shifting to SaaS, and how does your company help? 

When companies move from traditional on-premise software to SaaS, they face two key challenges. 

First, what should their SaaS application look like? This means defining its features and capabilities. Some companies simply transition their on-premise software to the cloud, but more often, SaaS solutions involve innovation and new functionality. This shift includes technology transitions, building cloud-native features, and adapting to a different software environment. Revenera helps software companies gain insights into how their solutions are being used, which is crucial for this transition. 

Many traditional software companies don’t have clear visibility into how their on-premise solutions are used. Without that data, moving to SaaS becomes risky. Understanding usage patterns is essential for a successful transition, and that’s where we help. 

The second challenge is monetisation. Pricing models that worked for on-premise software often don’t fit SaaS. On-premise solutions typically use per-device or floating models, where multiple users share access. SaaS pricing is usually different—often based on named users or usage-based components that limit access to certain resources. SaaS vendors also adopt tiered pricing models, such as “good, better, best,” where features are bundled into different subscription levels. Managing, provisioning, and enforcing these models is critical, and Revenera provides automation to handle this. 

Engineering resources are always limited, so companies prioritise their developers for core innovation. Instead of building platform capabilities from scratch, they rely on solutions like Revenera to manage entitlements, licensing, usage tracking, and monetisation. 

How is the rise of AI-powered SaaS solutions changing software monetisation? 

Right now, AI monetisation is still evolving, and many companies are looking to industry leaders for direction. I see three main approaches emerging. 

First, some companies don’t monetise AI directly. They integrate AI features at no extra cost, betting that enhanced functionality will attract more users and drive overall growth. This is common in the B2C space, where platforms use AI to improve user experience and gain a competitive edge, leading to more paying customers. 

In the enterprise space, there are two dominant models. One is treating AI as a premium feature, similar to Microsoft’s Copilot, where AI capabilities justify a higher price. The other is a consumption-based model, where customers pay per AI-driven outcome — such as completed transactions, successful recommendations, or generated orders. This model is gaining traction because charging per outcome tends to be more acceptable to end users. 

SaaS pricing is also shifting. Traditionally, SaaS applications charge a flat subscription fee. But as AI increases costs, this model alone isn’t sustainable. The likely future is a hybrid approach — combining a base subscription with additional charges based on AI-generated transactions or results. 

How will India shape the future of AI-driven analytics for SaaS companies? 

India is at the forefront of tech innovation. In recent years, there has been a surge in startups and consulting firms driving industry growth. India has become a key player in this space, not just in development and engineering but also in strategy and product management. 

A decade ago, many companies relied on India for development while keeping headquarters elsewhere. Now, Indian startups are emerging with unique business models and creative ideas. More companies, including ours, are expanding beyond development to include product management and strategy teams in India. India’s role in the industry is growing, and it is a crucial market for us and many others. Does that answer your question? 

India’s GCCs are evolving beyond cost centers into innovation hubs. How is your company leveraging this shift? 

Our company has long considered India a key hub, particularly for product development and innovation. This role continues to grow as we expand our headcount in India each year. 

In my team specifically, I’ve made significant changes in recent years by shifting product management to India and building dedicated innovation teams. These teams now include customer-facing roles, product management, strategy, and R&D, creating a more complete setup that drives innovation. 

A stable, capable team in India enhances innovation, and this strategy has proven effective. We plan to continue on this path as it delivers strong results. 

Are there any expansion plans for India GCC? 

Our company’s expansion depends on business growth. As our business grows steadily year over year, we expand by adding more people to existing teams or to new product innovation efforts. Most of this investment happens in my division, Revenera, with a significant focus in India. Many of our innovation projects are fully run out of India, where we have a strong network of partners. Like any software company, we run proof-of-concept and innovation projects, and we plan to continue doing so. As our company grows, we will keep expanding our teams in India. 

What trends will shape SaaS governance and monetisation in the next 3–5 years? 

SaaS monetisation, governance, and compliance are becoming increasingly complex. We just discussed why, covering different monetisation models, AI monetisation, and hybrid approaches like combining subscriptions with usage-based pricing. 

In the early days of SaaS, many startups built their own monetisation and governance systems. But that often led to significant technical debt, requiring too much time, energy, and resources for something that should be a straightforward platform function. 

Looking ahead, we’re seeing a shift, just like we did years ago in the on-premises software world. More SaaS companies are opting for off-the-shelf solutions instead of building these capabilities in-house. The focus is shifting toward innovation rather than maintaining custom-built monetisation systems. This isn’t about reducing headcount but about directing talent toward core innovation rather than operational infrastructure. 

At Revenera, we’re seeing increasing demand from SaaS companies realising that their homegrown monetisation solutions lack the flexibility they need. Monetisation models, pricing, and packaging in SaaS change frequently. Unlike on-premises software, which was often static, SaaS companies need to roll out new models or adjust existing ones quickly. That requires a fully automated platform.

This trend isn’t limited to Revenera’s space, it’s happening across industries. Companies are moving away from building everything in-house and instead investing in proven solutions that let them focus on growth. Expect this shift to continue in the coming years. 

What's next for Revenera in terms of AI investments? 

We’re focused on helping our customers monetise AI while enhancing our solutions based on their needs. Many customers prefer a token-based drawdown model, and we have a solution for that, which we continue to refine. 

Beyond monetisation, we’re also developing AI-driven insights for our customers' products. Revenera helps software companies manage customer entitlements and licences, tracking what customers have purchased, what they’re allowed to use, and what they actually use. With AI, we can analyse churn risks, identify upsell opportunities, and forecast trends. We can also benchmark product adoption and software usage against industry standards. Our AI council is actively working on use cases, currently in the prototyping stage. We plan to release AI functionality later this year, likely focused on predictive models using our data. 

Lastly, AI improves the customer experience by making software easier to use. Simple in-app bots can speed up access to documentation, automate processes, and improve resolution times. While this isn’t groundbreaking, it’s essential for efficiency and usability, something every software company, including us, is investing in. 

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