15-07-2025
Pricing AI In SMB SaaS: Balancing ROI And Affordability
Itzik Levy is the CEO and Founder of vcita, the partners-focused SMB business management platform.
It's been over two years since generative AI went mainstream and several months since agentic AI claimed the throne. Early on, the race was all about being first to market with anything powered by AI. The goal was simple: find a solid use case and ship it fast.
Fast-forward to today, and the landscape is beginning to shift. AI is no longer just a shiny add-on; it's a layer of real functionality that comes with real costs. Some costs are usage-based and others are upfront. Many providers absorbed those expenses early on, but with the hype cooling, pressure is growing to prove ROI.
When serving the SMB market, monetizing AI is especially tricky. Most SMBs simply can't justify steep add-on costs. Many SMBs are hesitant about using it in their daily workflows and need to build trust gradually. This creates a delicate balance: how do you deliver AI that is trusted, drives value and allows monetization?
In this article, I'll share what we've learned at vcita and provide best practices for monetizing AI without compromising your product's trust and affordability.
Common Models For Pricing AI Features
Among SaaS players, several patterns are gaining popularity:
It may feel natural to include AI features as part of your core product offering without charging extra. For example, Zoom bundles its generative AI assistant with all paid accounts at no additional cost, aiming to make AI easy and accessible. Similarly, HubSpot offers its AI Content Assistant and ChatSpot tools for free to all users, reserving premium features for higher-tier plans.
While you'll initially absorb the cost of providing AI, these tools can significantly boost the perceived value of your product. Over time, this added value can justify a higher price—not just to recoup expenses, but to reflect what the product is now worth to customers.
Another model offers AI as a premium add-on, requiring customers to pay an extra fee to unlock AI capabilities. This approach treats advanced AI functionality as a value-added upsell.
Many large vendors have gone this route, including Microsoft's new Copilot for Microsoft 365, which is priced per user. Salesforce similarly rolled out Sales GPT and Service GPT as add-ons with a cost per user.
With the premium add-on model, AI costs are offset by new revenue and customers can pay for advanced capabilities. It can make the business case for AI features very clear: if the feature truly saves time or money, some segment will pay for it. However, the result could also be low adoption of the AI features, and if competitors start bundling similar features for free, a standalone fee becomes difficult to justify.
This model charges based on how much customers use AI—measured by outputs, API calls or tasks completed. The appeal is that it directly ties cost to consumption: your clients pay in proportion to the value they get.
A clear example is Intercom's AI customer service bot. Intercom requires at least one paid seat on its platform and then charges per resolution the AI agent handles.
For SMB customers, pay-as-you-go pricing can be attractive if it offers flexibility and a low entry cost. On the flip side, unpredictability in bills is a major concern for SMBs.
There's also the cognitive load of monitoring usage. You'll need the infrastructure for selling and billing for these quotes, providing transparency on consumption and defining fallback behaviors for the scenarios where quotas are not renewed. None of these is mission-impossible, but none can be built overnight.
Best Practices For Using AI For SMBs
It has been two years since we launched our AI solution for SMBs. As we continue to enhance and expand our product, we develop a deeper understanding of where SMBs get the best value from AI, and how best to monetize.
Since many of us share the mission of empowering SMBs with technology, I wanted to share three key lessons we've learned so far:
Many SMBs are still figuring out what AI means for them. Invest in product guides and other educational assets that help users understand the time saved or ROI gained. When customers understand the benefit, they're more likely to pay for it or upgrade.
Set pricing based on outcomes, not just features. If your AI saves users 5-10 hours a week, make sure your price reflects that. At vcita, beta testing and user interviews help us understand and validate our product's propositions and confidently communicate AI's impact.
As AI continues to evolve, strategies will likely shift as well. This article is a snapshot of our approach as of 2025. What does the future hold for the commercialization of AI products? Even AI can't predict that. Our best option is to remain flexible and respond fast.
Balancing ROI With Accessibility
Looking ahead, maintaining two versions of your software—one with AI and one without—just isn't sustainable. It can increase complexity, slow down innovation and divide focus. We believe AI will soon be a core part of every SaaS platform, embedded in its infrastructure like any other essential component. It won't be an add-on; it'll be how software works.
That said, not every AI feature should carry a premium price. Basic, value-enhancing AI will likely be included by default. Only advanced capabilities that deliver clear, measurable ROI to SMBs should come at a cost. In the SMB segment, one principle remains firm: value must match price.
The SaaS companies that win in the age of AI will be those that build with empathy, price with clarity and align revenue with customer results. Help your customers grow with AI and you'll grow with them.
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