š How to Foster AI Adoption: From Isolated Feature to a Core Experience
Explore how Notion, Airtable, Canva, Miro, and more are adding AI on top of the Core experience.
Hello everyone š Iām Kate Syuma, and welcome to Growthmates.news ā the newsletter where we explore inspiring and practical growth stories from products we love. Join the community of 5,000+ Product, Design, and Growth people from companies like Amplitude, Intercom, Miro, Atlassian, Grammarly, Framer, and more.
Last year, companies like Notion, Miro, Airtable, Canva, and more started adding AI experiences. In 2025, we will see more products adding AI to their core product value. But how do we make sure AI experiences are discoverable? How do you onboard users and make sure they adopt them? This is your chance to look at best practices and apply tips to foster AI feature adoption.
This post is brought to you by CommonRoom ā a platform to run go-to-market intelligently. It helps you capture every buying signal and lead ethical and personalized conversations across every touchpoint of the modern buying journey.
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Today, we will talk about how to foster AI features adoption, and how to take a HOLISTIC look at them.
Website ā How to go beyond generic AI positioning and provide free value;
Pricing ā How to differentiate AI in pricing;
Onboarding ā How to introduce AI in the first experience;
Repeated usage ā How to start forming a habit with AI experience;
Summary ā Why AI features adoption needs a HOLISTIC approach.
Now, letās dive into each of these touch points with plenty of examplesš
1. Website š Go beyond generic AI positioning and provide free value.
I like describing the importance of the product website in this way:
Website is where we āSay Hiā to all of our potential users. And unfortunately āGoodbyeā as we lost most of them right away.
This is why itās so important how we communicate the value of AI on the website from all perspectives, so it should be:
Clear: Copy & Messaging play a huge role in communicating the value in the website. Now, we need to apply that to how we communicate about AI features ā speaking a familiar language and words that buyers and end-users would use.
Visually delightful: Studies show that "aesthetics and visual design play a role in positive perception and delight." For B2B SaaS, it's important to show the product value in an intuitively clear way, showing the product interface and examples of use cases.
Memorable: Short-Term Memory says that āthe human brain is not optimized for the abstract thinking and data memorization that websites often demandā. But we can be creative
š Give your AI a personality ā Notion.
Notion is the product that I love for their creativity. They are always going the extra mile from ordinary strategies, and it pays off.
So, they gave their AI experience a face! And they start fostering familiarity with that AI personality from their website's first interaction.
But itās not just appearance ā itās a thoughtful, contextual communication about AI capabilities across 3 key use cases:
Building collaborative docs ā AI assistant to edit, draft, and translate;
Organizing workflow ā AI automation;
Search in documentation ā AI to answer questions and find things faster.
As human beings, we capture simple things way better than complex topics that are over-communicated. Itās in line with Notionās high-quality principles ā they just put a catchy and memorable quote from Forbes. Keep it simple š
š Full page dedicated to AI positioning ā Airtable.
Itās nice when youāre talking about your AI capabilities contextually across your Website Home Page, but for broader discoverability ā take an extra mile and create a dedicated AI Landing Page.
Airtable is going that extra mile and creating a delightful landing page to introduce AI features like
Airtable Cobuildder;
5 Business processes + Airtable AI (use cases);
3 Templates to get started with AI.
Miro AI ā "Fast-track innovation with Miro AIā
Notion AI ā āMeet the new Notion AIā
Canva AI ā āFree online AI Image Generatorā
Airtable AI - āTransform your operations with Airtable AIā
Framer AI - āDesign better sites with AIā
Intercom Fin AI - āThe first AI agent that delivers human-quality serviceā
Dovetail AI - āData to insights like magicā
Loom AI - āHit record and Loom AI will do the restā
Common Room (RooomieAI) - āGenerate more pipeline with generative AIā
š Provide value for free with AI ā CommonRoom.
Your distribution channels go beyond product websites and AI Landing pages. CommonRoom tried to understand what value they could provide to their audience and ICP for free. In addition to communicating the power of AI to complement the core value āRun go-to-market intelligently and capture buyers signals,ā they created an additional Free resource AND Free value ā RoomieAIā¢ prompt library.
For their ICP (Sales Reps, Founders), itās important to save time on each email creation ā having a gallery of prompts and example messages can definitely make their job easier.
The " Company-generated " content can become āUser-distributedā to kick-start the Community-led Growth loop. If relevant people love this Library, they will share it with co-workers and bring you new, highly relevant customers.
āļø Key Takeaway: 3 things you can do to foster AI adoption from the Website.
Go beyond generic AI positioning ā make it memorable, fun, and give it a personality;
Create a dedicated landing page for the AI experience;
Create free AI resources to provide free value that is relevant to your ICP.
2. Pricing ā time to differentiate AI.
āMake AI a product theme, and weave it into your packaging.ā
ā Prising SaaS and āGood better bestā.
As we consider the AI experience holistically, we should also consider how it will be positioned in Pricing across all tiers. If your customers come from one of the AI-based landing pages, they will definitely check the price of your offering.
There are many options for presenting AI features on Pricing. Letās look at a couple of the most common examples.
š Option 1: AI credits for different plans ā Miro.
Some companies add āAI creditsā to each of their existing plans to simplify the decision-making process. Miro shows a limit of AI credits per month for each plan, giving users a starting point for adopting the AI features.
Of course, this approach has pros and cons. Letās look deeper into them:
š Pros:
Ease of adoption: Fits seamlessly into the current pricing tiers, making it easy for existing customers to try AI without a major commitment.
Lower barrier to entry: Users donāt need to make an extra purchase to access AIāthey can start using credits immediately.
š Cons:
Reduced discoverability: AI might be seen as ājust another featureā and not get the attention it deserves.
Limited perceived value: Users may not fully understand the potential of AI from a simple ācredits/monthā mention.
Revenue Potential: Bundling AI credits into existing plans may limit opportunities for additional revenue from AI-specific features.
So, what else you can do?
š Option 2: AI as an add-on ā Notion.
While AI is still a new concept, even for tech-savvy SaaS users, we need to integrate it smoothly into the workflow. When making a purchase decision, balancing the willingness to pay for AI (from the user side) and making it a cost-effective investment (from the business side) is still complex.
For that, you can start adopting AI experience as a separate āadd-onā. Look at how Notion is showing it on the pricing page:
Simple and clear pricing for members;
Integrations and apps connections;
List of endless use cases.
Airtable is using a similar approach, but it also shows the Free vs Paid options for AI, trying to activate users first with AI experience.
This entire approach when AI is positioned as a standalone offering also has pros and cons.
š Pros:
More clear positioning: AI is highlighted as a free/premium feature, making its value stand out with more context around use cases.
Higher intentionality ā Higher adoption: Users who pay for the add-on will likely be more invested in exploring and adopting AI capabilities.
Flexibility for business: This option allows businesses to offer AI as an optional feature, appealing to users who may not want or need AI initially.
š Cons:
Higher barrier to entry: Users may hesitate to pay for an additional feature without seeing its value first or completely miss that out.
Adoption challenges: Users who donāt opt for the add-on may never try the AI features, limiting overall adoption.
Complexity in Pricing: Businesses need to strike a balance between affordability and profitability when pricing the add-on.
āļø Key Takeaway: Credits vs Add-on?
Option 1 (Credits): Best for encouraging widespread adoption while keeping AI part of the core product. If your goal is to introduce AI as a natural extension of the product with lightweight enhancements rather than full-scale differentiators.ā go for it!
Option 2 (Add-On): Best for highlighting AI as an experience that is highly innovative and valuable on top of the core product. If your users are pretty tech-savvy and are more willing to pay for AI as a premium experience ā consider this option.
After users just made a decision to use your product with AI, we have the most interesting job just getting started ā Onboarding them into the product AND an AI-based experience. Letās dive deeper into the Airtable example in the next chapter.
3. Onboarding ā First experience with AI.
š Customise your Onboarding for AI ā Airtable.
When I checked the first Onboarding experience of many SaaS recently, I didnāt notice they added any different instructions to users who start with AI. This is quite disappointing, as the users have already shown the intent to start using AI experience. Hence, we need to do an extra job and onboard them to both ā your core product value AND AI-added value.
I was pleasantly surprised to uncover that Airtable is customizing onboarding for users who show AI intent (registered from the AI landing page).
š Onboard new users with AI ā Airtable.
For those who signed up from the AI landing page, Airtable is capturing user intent andĀ personalizingĀ the first experience by suggesting that they āBuild an app with AI.ā
After that, the user completes a flow with a āco-builderā whoās trying to understand the user preferences even deeper.
First, they gather relevant profiling information (Company name, industry, who are your end-users). Hereās a reminder from
on why you should ask profiling questions during onboarding.My favorite part starts here: users can customize their preferences and see the app preview. In that case, I created the app to analyze User feedback, and pre-made examples were pretty relevant and easy to customize for my needs.
š Introduce AI to existing users ā Notion.
Adoption is not just about new user experience ā itās about all your existing and ādormantā users who are using the product just for a tiny potential. However, companies often underestimate theĀ onboarding of existing users for new features.
When Notion released its AI functionality, they prompted the users to interact with it and suggested various use cases (Ask a question, Brainstorm ideas, etc.)
How could it be even better?
Avoiding overlapping popups (like tooltip and full-screen banner at the same time) ā it creates banner blindness, and users are more likely to skip this;
Personalizing suggestions ā avoiding generic āask a questionā and giving a more tailored suggestion like āKate, improve your User Research template in Notion.ā
Make time + place for contextual adoption ā prominent popups are good for the app launch but can be interruptive in other use cases. This is why Iām a fan of contextual recommendations ā more about this in Chapter 4.
š Add value to the first experience with AI ā Loom.
Previously I shared Loom story about adding AI experience, which presents a valuable AI addition to the core value. When Loom team realized that new users were struggling to get their videos viewed, they turned to AI to tackle the issue. Many creators were recording and sharing videos without adding titles or context, leaving viewers confused and disengaged. To solve this, Loom used AI to make the process seamless and more impactful for both creators and viewers.
Hereās how they did it across 3 core scenarios:
AI-Generated Titles: Immediately after recording, AI automatically created clear and concise titles, giving viewers a one-second glimpse of the videoās purpose. This drastically increased the likelihood of engagement.
Chapters: For longer videos, AI added chapter markers to help viewers jump to the most relevant parts, reducing friction and making the experience more user-friendly.
Summaries: Brief AI-generated summaries offered an at-a-glance understanding of the video, helping viewers decide if it was worth their time.
By automating these tasks, Loom removed the burden from creators and ensured videos were polished and easy to navigate. Creators could focus on recording, while viewers got the clarity they needed to engage with the content.
šÆ Results:
Higher view rates and improved engagement across the board;
Increased āVideo First Viewsā (VFV) = Activation Metric, as users were more likely to watch and interact with videos;
A smoother, more enjoyable user experience for both creators and viewers.
One more brilliant move from Loom that I recently found is the introduction to AI value-based features on a Free plan (after the Free trial expired).
Instead of showing an interruptive upgrade trigger, Loom embeds contextual information and value-focused sections to reactivate interest in exploring AI features.
āļø Remember ā upgrade decisions donāt happen ad-hoc. Users donāt just say āyesā the first time they see the option. Users need to:
Feel the need multiple times;
Build motivation through repeated encounters;
Understand what theyāre gaining.
But also, users canāt remember everything youāve shown them. Thatās why the way you organize and present features is so important.
āļø Key Takeaway: treat AI onboarding Holistically
This approach shows the power of integrating AI to enhance onboarding and drive value from the very first interaction. Remember, most users (ā40-60%) leave after a poor first onboarding experience.
We donāt want the users to leave without even exploring the full potential of the product. We want them to stay, experience the core + AI value, and keep using it in tandem. But how to re-engage users with AI functionality if they missed it across all the previous steps? Letās see in the last (but not the least) chapter š
4. Repeated usage ā Forming a habit with AI experience.
Before providing more examples, let me remind you of some theory. If we want to create a habit-forming experience with the product (both the Core and AI experience), we need to understand how behavioral psychology works.
š āCREATEā Framework and Hooked Model ā Grammarly example.
Iām now reading āDesigning for Behaviour Changeā by Stephen Wendel, and hereās what I found:
āEach time people think about taking the action, the process repeats: a cue leads them to think about it, they react intuitively, and so on. Thus, repeated actions require multiple passes through the CREATE Action Funnel. However, the funnel is subtly different each time. This is especially true when the person is deciding whether to take the action a second (or third, etc.) time."
āDesigning for Behavior Changeā by Stephen Wendel.

Another framework that I really love is the āHooked Modelā by
and how it explains the 4 necessary components of the habit-forming experience.To illustrate that in action, letās take Grammarly as an example. It shows premium suggestions as a āVariable reward = Core value.ā
Trigger (internal): as a user, I want to sound more professional.
Action: I write an email to my client.
Variable Reward: Grammarly gives premium suggestions.
Investment: I continue using Grammarly.
If you can design an experience where AI adds value to the CORE product workflow ā this is your way of re-engaging with AI features:
Find the right Internal Trigger: whatās the core motivation of your user, and how can your AI be helpful?
Uncover the right Action: how the user address this motivation in your product ā how do you suggest AI at that point?
Design Variable Reward: What value does AI provide each time?
Motivate into Investment: Why will the user get back to this experience with AI?
Ask yourself these four questions and try to design the AI experience using the Hooked Model. Next, we need to ensure that your users will repeatedly uncover the experience you deliver.
š Discoverability of AI features at the right TIME and PLACE.
In my 7+ years of experience with product-led growth, the most common issue Iāve seen isĀ poor feature discoverability. This is a real burden, as your team worked hard to create value and launch a new AI experience, and most often, users simply canāt see that.
This is why, instead of local optimizations and adding annoying entry points to every part of the product, we need to wear ourselves in the shoes of a user and think:
What are the flows where AI adds the most value? (= the right PLACE)
When do users need that AI feature the most? (= the right TIME)
š Example 1: Notion ā AI Discoverability in Core flows.
Remember the overlapping popup we discussed earlier? Here, Notion is doing a better job by providing more contextual and relevant entry points for starting interactions with AI.
Building new patterns with quick access to AI (āpress spaceā)
Adding an entry point to the toolbar ā embedding AI into regular workflow
š Example 2: Canva ā AI for quick actions.
Canva's āMagicā aggregates all AI features inside the product. In addition to contextually providing it, it creates one entry point (= āQuick accessā) with recommended actions.
While the āQuick accessā entry point is a good solution for future scaleability, AI is still a pretty new concept that B2B/B2C productivity SaaS are building on top of their core values. Users need more relevant explanations ofĀ WHENĀ andĀ WHYĀ AI is useful and a more tailored first experience with how AI is solving the job better than they solved it before (like āMagic Writeā or āMagic Imagesā).
It all reminds me of the concept of āBehavioural Design Changeā when we need to onboard users into new patterns and behaviors.
Thereās still a lot of work to be done to foster AI adoption in a relevant and contextual way. And it inspired me to dive even deeper and re-explore the concept of Product-led Growth through a new lense.
For 6+ years, I was responsible for the entire Growth funnel at Miro, and during the last year, I advised 10+ companies and collected plenty of first-hand examples from companies youāve seen in this post. To give everyone access to that knowledge and help create your own growth roadmap that drives impact and user delight, Iām launching the āUser-Centric Product-Led Growthā course starting this March š
š Growth teams face many challenges in achieving that, like:
How do we uncover new growth opportunities to impact Activation, Habit-forming, and Upgrades?
What behavioral principles can help create the most user-friendly and ethical solutions?
How do we prioritize these opportunities in a diverse roadmap?
Finally, how do we receive a buy-in to implement meaningful product changes and drive PLG?
Youāre welcome to bring your real challenge and practice for 3 weeks with me when weāll explore how to build a diverse roadmap combining behavioral psychology and Growth strategies. Youāll get real-world examples from products like Notion, Canva, and Miro, practical frameworks, and get direct feedback on Growth flows improvements from me and peers on live sessions.
š P.S. Promo āearly-birdā is valid till February 10 ā everyone who is joining this first cohort will get access to the emerging Growthmates community and will get feedback from like-minded peers and me directly. The outcome ā your Growth roadmap šÆ
āļø Summary: AI features adoption needs a HOLISTIC approach.
Adopting AI into your product strategy can be complex, but a structured framework simplifies the process. To take it further, you can apply the framework I described here ā 6 Steps of Holistic Activation.
Here's how successful companies approach key stages of AI adoption:
1ļøā£ Website ā The first impression matters. Make AI benefits clear and accessible.
Use simple, relatable messaging, like Notionās contextual AI use cases (e.g., editing, automation).
Create a dedicated landing page to showcase features, as Airtable does.
Offer free resources like CommonRoomās AI prompt library to deliver immediate value.
2ļøā£ Pricing ā Pricing models impact adoption.
AI Credits: Miro includes AI credits in tiers, encouraging trials but risking limited discoverability.
AI Add-Ons: Companies like Notion and Airtable position AI as a premium feature, appealing to power users with clear use cases.
3ļøā£ Onboarding ā Tailored onboarding ensures users experience value early.
Airtable personalizes AI flows for new users by highlighting relevant tasks and preferences.
Notion re-engages dormant users with prompts showcasing new AI capabilities.
Loom delivers instant value through AI features like auto-generated summaries.
4ļøā£ Repeated Usage ā Building habits around AI features is crucial.
Grammarly integrates AI seamlessly into workflows using behavioral frameworks like the Hooked Model.
Ensure AI features are discoverable at the right time and place to boost engagement.
This is all for today, dear readers. If you found this helpful ā please share your reaction and leave some comments š It would give a huge support for me to continue creating this!
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With best regards,
Kate Syuma