Should Your AI Feature Be Priced as an Add-On or Included in Your Plan? 5 Key Elements for Building a Decision Framework

The rise of AI has rapidly driven new business models, such as usage-based pricing, and sparked significant shifts in the billing software ecosystem that supports them. Another emerging trend, though less discussed, is the development of add-ons as a way for SaaS businesses to charge customers.

An add-on is a priced element added on top of existing plans. These can vary based on what they provide, such as:

1. Professional services like white-glove onboarding or API implementation

2. Additional features, especially AI-driven, ones that incur costs (e.g., LLM costs)

Incorporating add-ons into billing and sales can add complexity and may not always be the most efficient approach. So, how do you decide if a new feature or service should be billed as an add-on or included in your plans?

This guide offers a decision framework to help you choose the best approach for integrating new features—especially AI features—either by including them in existing plans (potentially adjusting plan prices) or by offering them as standalone add-ons.

Is the feature core to the value prop and aligned with the product strategy?

The first question to consider is whether the feature is core to your product or simply enhances it. Does it directly serve the product's value proposition—helping customers achieve their desired outcomes faster? Or does it improve the user experience without necessarily impacting the main goals users have for the product?

☝️ If the feature directly supports the value proposition and aligns with your product strategy, it might be best to include it in your plans. However, if it primarily acts as a facilitator, that’s a strong reason to price it as an add-on.

For example, consider Notion AI. Notion’s core value is facilitating collaboration across teams. A core feature that supports this is its connected database, which allows tasks to be shared across different team spaces in one workspace.

Notion AI, on the other hand, enhances collaboration by autofilling content with summaries and insights. This improves the experience by providing information more quickly, but it doesn’t directly fulfill Notion’s primary purpose of enabling team collaboration.

Hence why they price Notion AI as an add-on:

Notion AI’s is priced as an add-on

Another example is Tomorro’s Oro AI, an add-on described as an “ally” to the product's core function of contract collaboration. Oro AI supports the product by automating data extraction and content generation, but it’s not essential to the product’s primary goal, so it’s priced separately.

This explains in my opinion why their price this feature as an add-on:

Tomorro’s Oro AI is priced as an add-on

On the contrary, Surfer, which helps users generate SEO-optimized content, includes its AI-driven “rank-ready” article generation within its plans. This feature directly aligns with Surfer's value proposition of making it faster to create optimized content. This justifies why they decided to make this feature embedded as part of the core offering, even though its usage is limited depending on the plan.

Surfer's AI feature to generate articles is included within the various plans

Can you use this feature as a way to stand out from competitors?

As with many pricing strategies, you can choose to include certain features within your plans, even if competitors offer them as add-ons.

This can make sense if your pricing is higher or if you want to avoid negative perceptions around extra charges for new features. For instance, Coda.ai includes its AI capabilities within its plans. This could be a deliberate strategy to set itself apart from Notion, where similar features might come at an additional cost.

Coda chose not to price their core AI feature as an add-on

Make sure to align pricing of your feature with your Go-To-Market strategy

If a feature isn’t central to your value proposition or product strategy, it’s reasonable to consider offering it as an add-on.

However, it’s also crucial to align this decision with your go-to-market strategy. For example, if your goal is to drive adoption of your Enterprise plans, it’s often better to include the feature within the Enterprise plan rather than making it an add-on available across all plans.

This is common practice with features like SSO SAML, which are typically aimed at Enterprise customers and are best included in higher-tier, sales-served plans. ClickUp, for instance, takes this approach, bundling SSO SAML into its Enterprise offering rather than selling it as an add-on.

Clickup’ SAML SSO feature is included with the Enterprise plan

On the other hand, if your focus is on a "land and expand" strategy—closing customers quickly, even at lower ARPA, with plans to upsell later—then offering features as add-ons can be effective.

In this model, customers can start with a core offering and then add features as their needs grow, allowing for a flexible, scalable relationship. Gleam.io, for example, uses this approach, offering a pricing model where customers can select various add-ons, much like a personalized menu.

Gleam offers a “menu of add-ons” to price their product

Does the feature serve the core persona?

When a feature is designed for a specific persona within your ideal customer profile (ICP), it often makes sense to include it in a plan suited to that persona. For example, SSO SAML is typically bundled within Enterprise plans, catering to the needs of larger customers.

However, creating separate plans for each persona isn’t always feasible for SaaS companies. In such cases, offering the feature as an add-on is a practical solution. This approach allows customers to select features that meet their unique needs without requiring a new plan tier.

Zoom illustrates this well. It provides a "Large Meeting" add-on, enabling users to host up to 1,000 participants. This feature isn’t limited to Enterprise customers; smaller companies hosting large events can also benefit from it. By offering it as an add-on, Zoom adds flexibility, meeting specific use cases without forcing customers into higher plans.

Another example is Zoom’s "Zoom Compliance Manager" add-on, designed for industries like fintech and regtech, where compliance features are essential. This add-on gives companies in regulated industries the specific tools they need without restructuring the entire pricing plan to fit those specific needs.

Zoom’s pricing page offers add-ons tailored to specific use cases and personas.

How much control do you want over your margin after releasing this new feature?

Throughout this article, I’ve frequently mentioned AI features as add-ons, as they’re the most common case I’ve encountered in my analysis of pricing pages. However, the same logic applies to video-based features, SMS features, or any other service built on top of a third-party API. These features share a common trait: they bring significant costs to the business.

If the use of a feature scales proportionally with the plan size, customers on higher-tier plans will likely use more of it, increasing your costs. In these cases, as long as you’ve set usage limits, you can track costs effectively and plan accordingly.

But sometimes, a feature may see higher usage among customers on lower-tier plans. Embedding such a feature in these plans can shrink your margins—or, in some cases, even lead to losses. While some businesses can offset these costs with higher margins on other customers, this approach can be risky and isn’t always sustainable.

Take Klaviyo’s SMS feature, for example. It’s included within their plans, but they can’t easily predict SMS costs by plan tier. Some customers may never use SMS, while others may use it heavily, with costs varying by country. Here, offering SMS as an add-on makes sense. Pricing it separately—whether as credits or pay-as-you-go—enables Klaviyo to protect its margins and avoid losses on unpredictable usage.

Klaviyo offers their SMS feature as an add-on making it simpler to monitor the corresponding costs

Recap

Decision framework for including your AI feature within your existing plans or as an add-on

1. Is the feature core to your value proposition and aligned with product strategy?

✅ If yes, include it in your plans, even if it means raising prices.

❌ If no, and it acts more as an enhancement, consider making it a paid add-on.

2. Can this feature help you stand out from competitors?

✅ If yes, take a different approach than your competitors. Example: Coda includes Coda AI in plans, while Notion prices Notion AI as an add-on.

❌ If no, follow competitors' pricing strategy.

3. Make sure to align pricing of your feature with your Go-To-Market strategy

Ensure the pricing approach supports your sales goals. Does it aid in closing more Enterprise deals? Does it support a “Land and Expand” strategy?

4. Does the feature serve your core customer persona?

✅ If yes, that’s a strong reason to include it within plans.

❌ If the feature mainly serves a smaller, specific persona, it’s better suited as an add-on.

5. How much control do you want over your margin after release?

✅ If you’re open to some margin flexibility, embedding the feature within plans may work.

❌ If you prefer tighter margin control, consider an add-on with usage-based pricing.

Bonus

Keep in mind that your decision to price a feature as an add-on or include it within a plan doesn’t have to be permanent. Flexibility is key as your product and company evolve.

For instance, you may initially price a new feature as an add-on to capture usage data, measure costs, and assess customer willingness to pay. Later, with enough insights, you might choose to integrate it directly into a plan.

Similarly, if your product strategy shifts, a feature previously embedded in a plan may no longer align with your goals. In these cases, having a flexible pricing implementation—one that decouples pricing logic from the code—becomes valuable. This approach makes it easier to test, adjust, and refine your pricing structure as needed.