How Notion, Canva, and Other SaaS Tools Are Rebuilding Their Business Around AI Features

Almost every popular software product now promotes AI features: writing assistants inside note-taking apps, image generation inside design tools, summaries inside email and meeting software. Behind these features lies a business question with a common answer: how SaaS companies monetize AI features without driving customers away. Using recognisable tools such as Notion and Canva as examples, this case study explains the main monetisation patterns, why companies choose them and what they mean for businesses paying for software.

Pricing and packaging change frequently. The descriptions below are general and based on publicly available pricing pages and company announcements at various points; check current pricing directly before making decisions.

Why SaaS companies are rebuilding around AI

For established SaaS companies, AI is both an opportunity and a threat. It can make products more useful and justify higher prices, but it also lowers barriers for new competitors and introduces new costs, since every AI request consumes computing resources. Companies must decide whether to give AI away to stay competitive, charge separately to cover costs, or reshape their entire pricing structure.

Customer expectations add further pressure. As AI assistants become common, users increasingly expect similar capabilities inside every tool they use. A product without AI features may look outdated, even if its core functionality is excellent. That pushes companies to add AI quickly, sometimes before they have worked out the best way to price it.

Pattern 1: AI as a paid add-on

One common approach is to sell AI as an optional add-on on top of an existing subscription, often priced per user per month. This lets companies earn additional revenue from customers who value AI while leaving the base price unchanged for others. Notion, for example, initially offered its AI capabilities as a paid add-on to its plans, a widely discussed example of the Notion AI business model at the time. Add-ons make AI revenue visible and measurable, but they can feel like an extra charge for features customers increasingly expect.

The add-on approach also gives companies useful data. By tracking how many customers buy the add-on and how heavily they use it, they learn which AI features deliver real value. Insights from the Notion AI business model and similar add-on experiments across the industry have informed later decisions to bundle, reprice or restructure AI offerings.

Pattern 2: Bundling AI into higher tiers

Another approach is to include AI features in premium plans, sometimes alongside a price increase justified by the added value. This encourages customers to upgrade and simplifies pricing. Several companies have moved from add-ons toward bundling over time; Notion reportedly changed its packaging to include AI in certain business plans, and large productivity suites have folded AI assistants into their plans with adjusted prices. Bundling can increase average revenue per user while reducing the friction of separate purchases.

Bundling also signals that AI is becoming a core part of the product rather than an optional extra, a message companies use to differentiate themselves from competitors.

Pattern 3: Usage credits and limits

Because AI has real per-use costs, many products include a limited number of AI uses or credits in each plan, with more available on higher tiers or for purchase. Design tools, for instance, often allow free users a small number of AI generations, with higher limits for paying subscribers. Canva AI monetization has involved offering AI features within its Magic Studio set of tools, with access and limits varying by plan. Credit systems protect margins from heavy users while letting casual users try features.

Credits also let companies introduce new, more expensive AI features, such as video generation or advanced research tools, without raising prices for everyone. Canva AI monetization and similar approaches in design and content tools show how credits can balance generous access for casual users with protection against very heavy usage.

Pattern 4: Price increases justified by AI

Some companies have raised subscription prices for existing plans, citing new AI capabilities as part of the added value. Canva, for example, drew public attention when it changed pricing for some team plans, with the company pointing to expanded features, including AI tools. Such increases can boost revenue but risk customer backlash, especially among price-sensitive small businesses who did not ask for AI features.

Pattern 5: Separate AI products

A few companies launch standalone AI products or assistants that work across their platform, priced separately. This approach suits companies whose AI capabilities are substantial enough to stand alone or appeal to different buyers. It also allows experimentation without disrupting core pricing.

Standalone products also let companies reach customers who do not use their core platform, potentially opening new markets beyond their existing user base.

SaaS AI upsell strategy: why it matters

A SaaS AI upsell strategy matters because AI changes the cost structure of software. Traditional SaaS enjoyed very high gross margins, since serving an extra user cost little. AI features introduce variable costs that grow with usage. Companies that give unlimited AI away at a flat price risk eroding margins; companies that charge too much risk losing customers to competitors offering similar features cheaply. Finding the balance is one of the central strategic challenges in software today.

Getting the SaaS AI upsell strategy right also affects customer perception. Customers who feel AI is being used as an excuse for price increases may look for alternatives, while those who see clear value in AI features may happily upgrade. Clear communication about what AI delivers is therefore as important as the price itself.

AI feature pricing SaaS products use: key considerations

When setting AI feature pricing SaaS products must consider the cost of serving AI requests, the value customers receive, competitors' pricing, the risk of heavy users, customer expectations that AI should be included, and the simplicity of the overall pricing structure. Many companies have adjusted their approach several times as costs fell and competition increased, showing how fluid this area remains.

What this means for businesses buying SaaS

For small businesses, AI monetisation changes software budgets. Subscriptions may rise, add-ons can accumulate across several tools, and credit limits may affect how teams use features. Review which AI features your team actually uses, whether they justify upgrades or add-ons, and whether overlapping tools provide similar capabilities. Our framework for evaluating AI tools helps avoid paying for unused features.

It is worth checking whether AI features are switched on by default and how data is handled. Some products enable AI features automatically, which may raise data-handling questions for businesses with strict policies. Review admin settings and data terms, particularly for tools that process customer or employee information.

Negotiating and managing costs

Businesses with several users can sometimes negotiate pricing, especially on annual plans. Assign AI add-ons only to team members who benefit from them, rather than buying for everyone. Monitor credit usage to avoid surprise charges. Periodically reassess whether a general AI assistant could replace multiple AI add-ons across different tools.

Keep a simple record of which tools include AI features, what each costs and who uses them, and review it before renewals.

Lessons for SaaS founders

For founders building software, these patterns offer lessons. Understand your AI cost per user before setting prices. Consider starting with usage limits to protect margins. Communicate the value of AI clearly when changing prices. Avoid surprising customers with sudden increases. And watch competitors closely, since AI features can quickly become expected rather than premium. Our guide to the cost of adding AI features covers the cost side in detail.

The broader trend

Over time, AI features that once commanded premium prices may become standard parts of software, much as cloud storage and mobile apps did. Companies will likely compete on how well AI is integrated into workflows rather than on whether it exists. Monetisation may shift from explicit AI charges toward overall plan value, with usage limits managing costs behind the scenes.

For buyers, this suggests patience can pay off: features that seem expensive today may become cheaper or included as standard over time.

Summary: how SaaS companies monetize AI features

To summarise how SaaS companies monetize AI features: they use paid add-ons, bundling into higher tiers, usage credits, AI-justified price increases and standalone AI products, often adjusting their approach over time. Notion and Canva illustrate several of these patterns. For businesses, the key is to understand which AI features genuinely add value and to manage subscriptions actively as pricing evolves.

Frequently asked questions

Why do SaaS companies charge extra for AI?

AI features have real per-use computing costs, unlike most traditional software features, so companies seek pricing that covers those costs.

Is AI usually an add-on or included in plans?

Both approaches are common, and many companies have shifted from add-ons toward bundling AI into higher tiers over time.

What are AI credits in software subscriptions?

Limits on how many AI actions you can use per period, with more available on higher plans or for purchase.

How can small businesses control AI software costs?

Assign AI add-ons only to users who need them, monitor usage, review overlapping tools and reassess subscriptions regularly.