The landscape of enterprise software is undergoing a seismic shift as artificial intelligence moves from a buzzword to the core of operational strategy. To understand this evolution, we are joined by Vijay Raina, a seasoned specialist in enterprise SaaS technology and software architecture. With years of experience guiding organizations through digital transformations, Raina offers a unique vantage point on how AI is not only changing the tools we use but fundamentally rewriting the economic rules of the software industry. From the transition toward consumption-based pricing to the dramatic acceleration of software development lifecycles, his insights provide a roadmap for navigating this disruptive era.
The discussion explores the current global demand environment and the rapid adoption of AI within employee experience strategies. It delves into the structural changes in SaaS billing models, where traditional seat-based metrics are giving way to outcome-oriented measurements like sessions and managed assets. Furthermore, we examine the internal productivity gains realized through AI, the strategic push into the “agile enterprise” market against legacy giants, and the centralization of customer experience functions to maintain a nimble, high-growth trajectory.
The landscape for enterprise software has been quite turbulent lately due to global tensions, yet there seems to be a massive appetite for new technology. How are you seeing organizations integrate AI into their employee experience strategies from the very start?
Despite the geopolitical noise and the general uncertainty that comes with rapid innovation, the demand for sophisticated Employee Experience (EX) tools is remarkably resilient. We are seeing a trend where nearly 70 percent of new customers in the EX space are opting to purchase AI capabilities right at the onset of their contracts. It is no longer an afterthought or a secondary upgrade; it has become the primary driver for those looking to modernize their internal operations. Organizations entered this year with their strongest pipelines ever because they recognize that mastering AI is the only way to navigate external pressures they cannot control. They are looking for ways to empower their workforce immediately, moving beyond the trial phase into full-scale implementation.
For a long time, the software industry relied on charging per user, but that seems to be changing. How is the rise of AI consumption-based metrics specifically altering the way SaaS companies structure their pricing?
The traditional model of billing per “seat” is naturally evolving into a more nuanced, outcome-based framework. As AI agents begin to handle tasks that were once exclusively the domain of human agents, the value shifts from the number of people logged in to the volume of work actually performed. We are now seeing models based on the number of sessions an AI agent completes, the total number of assets being managed, or even the volume of incidents successfully resolved. This transition ensures that the pricing is directly tied to the tangible results the software delivers to the business. As AI adoption deepens, I expect to see the mix of revenue shift significantly toward these consumption metrics, creating a much tighter alignment between cost and actual utility.
Productivity is a major promise of AI, but many companies struggle to quantify it. What kind of tangible gains are being seen internally within development teams, and how does this change the relationship between roles like product managers and engineers?
Internally, the impact of AI on the software development process has been nothing short of transformative, with development cycles now running about 30 percent faster than they did previously. We are witnessing a reality where complex product requirements that used to take weeks to draft are now being generated from simple prompts and translated into functional code in a fraction of the time. This efficiency is blurring the traditional lines between product managers and engineers, creating a significant overlap in what each role can achieve. While we track things like token consumption to monitor usage, the real metric of success is the ability to redirect these massive productivity gains into entirely new projects and innovations. It allows teams to move from the “grind” of coding into the high-level strategy of architecture and design.
The competition in the enterprise space is fierce, especially when going up against established legacy players. What is the strategy for capturing the “agile enterprise” market and winning deals over long-standing incumbents?
Our strategy focuses on what we call “agile enterprises”—those companies that require robust, enterprise-grade capabilities but want to avoid the bloat and sluggishness of traditional corporations. We have been increasingly successful in winning over customers from larger rivals like ServiceNow and BMC because we offer a faster, more modern alternative. Enterprise customers are now driving a disproportionate share of growth because they are tired of the complexity associated with legacy systems. By providing a platform that is powerful yet flexible, we can win these high-stakes deals. Our recent success in securing two of our largest deals to date proves that there is a massive hunger for software that works as hard as the companies using it.
There has been a lot of talk about consolidating operations to stay competitive. How does centralizing the sales and engineering functions for the Customer Experience vertical in a specific hub change the “feel” of the business?
Centralizing the entire Customer Experience (CX) vertical in India—including sales, marketing, product, and engineering—is a strategic move to recapture a “start-up feel” within a large organization. By anchoring these functions in one place, we can move faster, communicate more effectively, and innovate with a level of agility that is often lost in decentralized models. This internal alignment allows the core CX business to remain nimble and focused on high growth. Meanwhile, the field organization can focus its energy on products like Freshservice, which are tailored for the complex needs of larger, global organizations. This dual approach ensures that we can serve the high end of the market without losing the innovative spark that built the company.
Legacy providers often use their size to try and price out competitors through heavy discounting. How can a modern SaaS provider remain competitive when faced with these aggressive tactics from incumbents?
In the world of enterprise software, the ultimate differentiators are speed and value, and that is where the legacy giants often struggle. While a typical migration for a legacy system might drag on for nine months to a year, we can complete that same process in less than three months. This speed provides an immediate financial advantage to the customer, as they reduce administrative overhead and operational costs much sooner. Aggressive discounting can only go so far if the underlying software is slow to implement and expensive to maintain. By focusing on enterprise-grade capabilities and continuous AI innovation, we provide a value proposition that makes the long-term cost of ownership much lower, regardless of an initial discount from a competitor.
What is your forecast for the future of the SaaS industry over the next few years?
My forecast is that we will see a “Great Decoupling” where software value is no longer tied to human headcount but to the autonomous resolution of complex business problems. We will likely see the Freshservice model—which currently boasts an annual recurring revenue of $600 million—become the blueprint for how AI-first products dominate the market. As AI continues to drive innovation across product portfolios, the traditional SaaS growth rates will be eclipsed by companies that can successfully transition their customers to outcome-based models. The focus will shift entirely away from the “tool” itself and toward the speed at which that tool can generate measurable business growth and efficiency.
