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Why the Per-Seat Business Model Faces Challenges in the Age of AI

The rise of AI is shaking up many industries, and one area where the impact is particularly significant is in SaaS companies that rely on the per-seat business model. Traditionally, these companies charge customers based on the number of users, or seats, accessing their software. But with AI’s ability to handle the work of multiple human employees, this model is facing serious challenges. AI can take on tasks at scale, reducing the need for multiple human users—and by extension, the number of seats needed.

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Published onSeptember 16, 2024
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Why the Per-Seat Business Model Faces Challenges in the Age of AI

The rise of AI is shaking up many industries, and one area where the impact is particularly significant is in SaaS companies that rely on the per-seat business model. Traditionally, these companies charge customers based on the number of users, or seats, accessing their software. But with AI’s ability to handle the work of multiple human employees, this model is facing serious challenges. AI can take on tasks at scale, reducing the need for multiple human users—and by extension, the number of seats needed.

AI Replacing Multiple Human Seats

One of AI's most disruptive effects is its ability to handle tasks that would typically require multiple people. In a per-seat model, each additional employee using the software equates to an additional charge. But when an AI system can perform the work of several employees, this dynamic changes. AI doesn’t occupy multiple seats—it’s often just one seat, if any, but it can scale its workload exponentially.

Take customer service, for example. Before AI, a company might need 20 customer service agents, and each of them would require a seat in a tool like Intercom or LiveChat. The SaaS company would charge based on those 20 agents. But if a single AI tool can handle the workload of those 20 agents, the company now only pays for one seat—or potentially none, if AI integrates outside the standard user framework. This scaling effect is fundamentally at odds with the per-seat model, reducing the total number of paying seats and, by extension, reducing the revenue of the SaaS provider.

Live Chat Tools: The Perfect Example

Live chat tools like Intercom, Help Scout, and LiveChat are some of the most impacted by AI’s rise. These platforms traditionally thrived on the need for customer support teams to communicate with users in real-time, charging businesses per seat or agent using their software.

With AI-driven chatbots and customer service tools, companies no longer need large teams of agents to manage support. AI can handle thousands of interactions simultaneously, and it learns from each interaction to improve responses over time. This efficiency dramatically reduces the need for human agents. Consequently, the number of seats required drops drastically, eroding the primary revenue stream for these SaaS providers.

Consider a mid-sized company that used to have 50 customer service agents. Each agent would need access to tools like Intercom, generating substantial revenue for the SaaS provider. Today, that same company might only need 5 agents for complex queries, while an AI chatbot manages 90% of the interactions. In this scenario, the SaaS provider’s revenue from that customer shrinks considerably. AI’s efficiency is a double-edged sword for these companies, providing value to their customers while threatening their business model.

The Dilemma of Changing the Business Model

Recognizing the challenges posed by AI, many SaaS companies may consider adapting their pricing models to stay competitive. Yet this shift presents a significant dilemma. Moving away from the per-seat model could help align their pricing with the new reality, but it would also hurt their current revenue structure.

A company could introduce usage-based pricing, charging based on the number of interactions handled by the AI, or the total volume of data processed. While this could potentially capture the value AI brings to businesses, it risks alienating long-time customers who are used to paying per seat. For customers accustomed to fixed costs tied to the number of users, usage-based pricing might seem unpredictable and more expensive. This can lead to pushback, cancellations, or even the adoption of competitor solutions that remain affordable.

Another possible approach is offering tiered subscription plans where AI-driven capabilities are part of a premium package. This may encourage businesses to pay more for enhanced services while preserving some revenue streams. However, the transition could still lead to a temporary or even permanent revenue drop as companies optimize their AI investments and reduce their reliance on human workers. The SaaS provider may be forced to face the reality of lower subscription numbers, even if AI allows their remaining customers to extract more value.

A Struggle to Maintain Original Revenue

For traditional SaaS companies that stick with the per-seat model, the challenge will be maintaining their original revenue in an AI-dominated world. As more companies adopt AI to automate processes, fewer seats will be needed across industries. The per-seat model, which once ensured predictable growth with the expansion of a customer’s workforce, will no longer be effective. Companies may find their existing customers shrinking their seat count year after year as AI continues to improve.

This situation creates a revenue gap that’s hard to fill. While AI offers incredible efficiency and productivity, it’s bad news for the companies relying on the headcount of a customer's team to drive their revenue. Even worse, competitors with more flexible pricing models could swoop in to attract customers looking for AI-friendly solutions.

SaaS companies face the choice of either evolving their pricing strategy or losing market share to more adaptive players. The pressure to innovate is immense, and the financial hit during the transition could be substantial.

The per-seat business model, which has served SaaS companies well for many years, is now under threat due to AI's ability to replace multiple human workers. Nowhere is this more apparent than in industries like customer service, where live chat tools such as Intercom, Help Scout, and LiveChat are seeing fewer seats required as AI takes over many tasks. Transitioning to new pricing models could be necessary, but it will likely hurt the company’s original revenue streams.

As AI continues to evolve, SaaS providers must rethink their approach to pricing or risk falling behind. Those that adapt may find new revenue opportunities, but the road ahead won’t be easy, especially for those tied to the traditional per-seat business model.

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