Whalesbook
Software companies are facing pressure to switch from traditional subscription fees to outcome-based pricing due to the rise of AI. This transition is complex and may hurt short-term profits, leading some experts to suggest that certain companies might consider delisting from public markets to navigate the change without constant quarterly pressure from investors.
What Happened
The software industry is undergoing a major shift in how it charges customers. For years, the standard Software-as-a-Service (SaaS) model involved charging clients a fixed fee based on the number of users or "seats." However, the rise of Artificial Intelligence (AI) is changing the value of software.
Industry leaders, including Dheeraj Pandey, CEO of DevRev, have highlighted that as AI agents begin to perform tasks that were previously done by humans, the traditional per-seat subscription model is becoming outdated. Instead of paying for a user license, enterprises are increasingly demanding to pay for the actual results or outcomes the software delivers. This shift forces software vendors to move toward outcome-based pricing, where costs are linked to consumption or specific results achieved by the AI, rather than just the number of employees using the platform.
Why This Matters For Investors
This change represents a fundamental transformation in how software companies generate revenue. For publicly traded companies, this creates a difficult situation. Transitioning a business model is rarely smooth or immediate. It often leads to a period of revenue uncertainty or margin pressure as companies abandon reliable subscription income in favor of new, untested pricing structures.
Public markets typically prioritize predictable, quarter-over-quarter growth. If a company’s revenue fluctuates during this transition, investors often react negatively, causing stock price volatility. Experts suggest that some firms might find it easier to manage this multi-year transformation as private companies, where they are not held accountable to short-term earnings targets and can focus on long-term strategy without the risk of seeing their stock price plummet during the transition.
The Shift to Outcome-Based Pricing
To understand this shift, consider the difference. In a traditional model, a company pays for 100 software licenses for its staff. With outcome-based pricing, the company might pay only for the number of customer complaints resolved by an AI agent. While this is better for the customer—who only pays for value received—it changes the vendor's economics. Revenue becomes variable, making it harder for financial analysts to forecast earnings with the same level of accuracy they had when models were based on fixed user counts.
Historical Context
This is not the first time the software industry has faced a disruptive pivot. Decades ago, companies had to shift from selling perpetual software licenses (where a customer paid once for a product) to the subscription models that dominate today. That transition was painful and often confusing for investors, yet it ultimately led to higher valuations for companies that successfully adapted. The current move to AI-driven, outcome-based pricing is being viewed as a similar, albeit faster, evolutionary step. The companies that successfully pivot to delivering measurable results are likely to see their business advantages grow, but the journey to get there may be volatile.
Risks And Concerns
Investors should be aware that this transition is not without danger. The primary risk is margin compression, where the cost of AI compute and integration services eats into profitability before the new pricing models can fully offset the decline in subscription revenue. Additionally, there is a risk of execution failure; if a company cannot prove its AI delivers meaningful outcomes, it may struggle to justify its pricing, leading to customer churn. Furthermore, while the idea of going private offers companies more flexibility, it is an extreme step and not a guaranteed fix for business model challenges.
What Investors Should Track
Investors monitoring SaaS companies should pay close attention to management commentary regarding pricing strategies during earnings calls. Watch for metrics beyond just revenue, such as net revenue retention and changes in average contract value. Keep an eye on how companies are bundling AI features—are they adding them for free, or are they successfully monetizing them? The ability of a company to explain its long-term roadmap while navigating short-term friction will be a key signal of its strength during this industry-wide transformation.
