How to Foster AI Adoption Through a Multi-Channel Strategy

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 you make sure AI experiences are discoverable? And, how do you onboard users and make sure they adopt them? This is your chance to explore best practices and apply tips to foster AI feature adoption.

In this article, I will talk about how to foster AI feature adoption through different channels, and how to take a holistic look at them.

1. GTM: How to build the groundwork for AI adoption.
2. Website: How to go beyond generic AI positioning and provide free value.
3. Pricing: How to differentiate AI in pricing.
4. Onboarding: How to introduce AI in the first experience.
5. Repeated usage: How to start forming a habit with AI experience.

Now, let’s dive into each of these touch points with plenty of examples👇

1. GTM: Setting the stage for AI adoption 

Launching AI features isn’t just about announcing them, it’s about making sure users see the value and integrate them into their workflows. A well-executed GTM strategy ensures a smooth rollout, builds excitement, and encourages action. 

Companies that succeed in AI adoption don’t just hype up AI. They position it as a problem-solver. This means gradual rollouts, clear messaging, and use-case-driven education. Let’s explore two key GTM tactics that have worked for leading SaaS products. 

📌 Launch AI-powered features in controlled phases: Notion

A phased release allows companies to:

• Gather feedback before a full-scale launch.
• Identify and fix issues early.
• Generate buzz among early adopters.

Before making Notion AI widely available, Notion introduced a waitlist system. This approach helped them:

• Collect early feedback on AI-generated content quality.
• Create demand through exclusivity – users felt a sense of urgency to try it.

By refining the product with real user insights, Notion ensured a more polished launch and smoother adoption.

📌 Communicate value, not just AI hype: ClickUp

Users don’t adopt AI features simply because they exist, they need to understand why they matter. A successful GTM strategy highlights clear benefits rather than just claiming the product is “AI-powered.”

ClickUp introduced ClickUp AI with a strong value proposition: “The World’s Only Role-Based AI Assistant.” 

Instead of vague AI claims, ClickUp focused on tangible productivity gains, showcasing:

• Real tasks AI could automate.
• A dedicated AI landing page with video demos showing AI in action.

This strategy helped users immediately grasp how AI could fit into their daily workflows.

⭐️ Key takeaways: 2 Ways to foster AI adoption from GTM campaigns

• A phased rollout ensures a more refined product and a stronger launch impact.
• Focus on real-world benefits instead of just stating that your product now has AI.

2. Website: Go beyond generic AI positioning and provide free value

I like describing the importance of the product website in this way:

The website is where we “Say Hi” to all of our potential users. And unfortunately, “Goodbye” as we lose most of them right away.

This is why it’s so important how we communicate the value of AI on the website from all perspectives. It should be:

• Clear: Copy and messaging play a huge role in communicating the value on the website. The same approach should be applied when communicating AI features: using language that resonates with both buyers and end-users.
• 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, showcasing the product interface and examples of use cases.
• Memorable: Short-term memory says that “the human brain is not optimized for the abstract thinking and data memorization that websites often demand.” But we can be creative.

📌 Give your AI a personality: 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.

They gave their AI experience a face! And they start fostering familiarity with that AI personality from their website’s first interaction.

But it’s not just appearance: it’s a thoughtful, contextual communication about AI capabilities across 3 key use cases:

1. Building collaborative docs: AI assistant to edit, draft, and translate.
2. Organizing workflow: AI automation.
3. Search in documentation: AI to answer questions and find things faster.

As human beings, we capture simple things way better than complex topics that are over-communicated. It’s in line with Notion’s high-quality principles: they just put a catchy and memorable quote from Forbes. Keep it simple 👇

📌 Full page dedicated to AI positioning: Airtable

It’s nice when you’re talking about your AI capabilities contextually across your website home page, but for broader discoverability. Take the 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 Cobuilder.
• 5 business processes + Airtable AI (use cases).
• 3 templates to get started with AI.

Some more examples from dedicated AI landing pages:

• Miro AI: “Fast-track innovation with Miro AI”
• Notion AI: “Meet the new Notion AI”
• Canva AI: “Free online AI Image Generator”
• Airtable AI: “Transform your operations with Airtable AI”
• Framer AI: “Design better sites with AI”
• Intercom Fin AI: “The first AI agent that delivers human-quality service”
• Dovetail AI: “Data to insights like magic”
• Loom AI: “Hit record and Loom AI will do the rest”
• Common Room (RoomieAI): “Generate more pipeline with generative AI”

📌 Provide value for free with AI: 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 “Run go-to-market intelligently and capture buyers signals,” they created an additional Free resource AND Free value: RoomieAI™ prompt library.

For their ICP (Sales Reps, Founders), it’s important to save time on each email creation. Having a gallery of prompts and example messages can definitely make their job easier.

The “company-generated” content can become “user-distributed” to kick-start the community-led growth loop. If relevant people love this library, they will share it with co-workers and bring new, highly relevant customers.

⭐️ Key takeaways: 3 Things you can do to foster AI adoption from the website

1. Go beyond generic AI positioning: make it memorable, and fun, and give it a personality.
2. Create a dedicated landing page for the AI experience.
3. Create free AI resources to provide free value that is relevant to your ICP.

3. Pricing: Time to differentiate AI

Make AI a product theme, and weave it into your packaging.
– Rob Litterst, PricingSaaS and Good better best

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 the pricing page. Let’s look at a couple of the most common examples.

📌 Option 1: AI credits for different plans – Miro

Some companies add “AI credits” 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. Let’s look deeper into them:

👍 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 don’t need to make an extra purchase to access AI; they can start using credits immediately.

👎 Cons

• Reduced discoverability: AI might be seen as “just another feature” and not get the attention it deserves.
• Limited perceived value: Users may not fully understand the potential of AI from a simple “credits/month” 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?

📌 Option 2: AI as an add-on – 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 “add-on.” 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.

👍 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 → 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.

👎 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 don’t 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.

⭐️ 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 – 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 – consider this option.

After users just made a decision to use your product with AI, we have the most interesting job just getting started, onboarding them into the product AND an AI-based experience. Let’s dive deeper into the Airtable example in the next chapter.

4. Onboarding: First experience with AI

📌 Customise your Onboarding for AI: Airtable

When I checked the first onboarding experience of many SaaS companies recently, I didn’t 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: 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).

For those who signed up from the AI landing page, Airtable is capturing user intent and personalizing the first experience by suggesting that they can “Build an app with AI.”

After that, the user completes a flow with a “co-builder” who’s trying to understand the user preferences even deeper. First, they gather relevant profiling information (company name, industry, who are your end-users). 

Here’s a reminder from Elena Verna 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 the pre-made examples were pretty relevant and easy to customize for my needs.

📌 Introduce AI to existing users: Notion

Adoption is not just about new user experience: it’s about all your existing and “dormant” users who are using the product just for a small potential. 

However, companies often underestimate the 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 banners at the same time. It creates banner blindness, and users are more likely to skip this.
• Personalizing suggestions. Avoiding generic “ask a question” and giving a more tailored suggestion like “Kate, improve your user research template in Notion.”
• Make a time + place for contextual adoption. Prominent popups are good for the app launch but can be interruptive in other use cases. This is why I’m a fan of contextual recommendations.

📌 Add value to the first experience with AI: Loom

Previously I shared Loom’s story about adding AI experience, which presents a valuable AI addition to the core value. When the 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.

Here’s how they did it across 3 core scenarios:

1. AI-generated titles: Immediately after recording, AI automatically created clear and concise titles, giving viewers a one-second glimpse of the video’s purpose. This drastically increased the likelihood of engagement.
2. 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.
3. 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.

🎯 Results

• Higher view rates and improved engagement across the board.
• Increased video first views (their 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.

❗️Remember: Upgrade decisions don’t happen ad-hoc. Users don’t just say “yes” the first time they see the option. Users need to:

• Feel the need multiple times.
• Build motivation through repeated encounters.
• Understand what they’re gaining.

But also, users can’t remember everything you’ve shown them. That’s why the way you organize and present features is so important.

⭐️ 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 (≈40-60%) leave after a poor first onboarding experience.

We don’t 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? Let’s see in the last (but not the least) chapter 👇

5. Repeated usage: Forming a habit with AI experience

Before providing more examples, let me remind you of some theories. 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.

📌 “CREATE” framework and hooked model: Grammarly example

I’m now reading “Designing for Behaviour Change” by Stephen Wendel, and here’s what I found:

Each 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.
– Stephen Wendel, Designing for Behavior Change

Another framework that I really love is the “Hooked Model“ by Nir Eyal and how it explains the 4 necessary components of the habit-forming experience.

To illustrate that in action, let’s take Grammarly as an example. It shows premium suggestions as a “Variable reward = Core value.”

• 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, this is your way of re-engaging with AI features:

• Find the right internal trigger: What’s the core motivation of your user, and how can your AI be helpful?
• Uncover the right action: How the user addresses this motivation in your product – 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.

📌 Discoverability of AI features at the right TIME and PLACE

In my 7+ years of experience with product-led growth, the most common issue I’ve seen is 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 can’t 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)

👍 Example 1: Notion – 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 (“press space”)
• Adding an entry point to the toolbar: embedding AI into regular workflow

👍 Example 2: Canva – AI for quick actions

Canva’s “Magic” aggregates all AI features inside the product. In addition to contextually providing it, it creates one entry point (=quick access) with recommended actions.

While the “quick access” entry point is a good solution for future scalability, 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 of WHEN and WHY AI is useful and a more tailored first experience with how AI is solving the job better than they solved it before (like “Magic Write” or “Magic Images”).

It all reminds me of the concept of “Behavioural Design Change” when we need to onboard users into new patterns and behaviors.

⭐️ Summary: AI features adoption needs a HOLISTIC approach

Adopting AI into your product strategy can be complex, but a structured framework simplifies the process. 

Here’s how successful companies approach key stages of AI adoption:

1. GTM: Set the stage up for adoption of AI features

• A phased rollout through a waitlist helps build anticipation about the new release. It also gathers feedback that can refine the product before a full launch. 
• The messaging should focus on real-world benefits, instead of just using AI as a buzzword. 

2. Website: Make AI benefits clear and accessible

• Use simple, relatable messaging, like Notion’s contextual AI use cases (e.g., editing, automation).
• Create a dedicated landing page to showcase features, as Airtable does.
• Offer free resources like CommonRoom’s AI prompt library to deliver immediate value.

3. Pricing: 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.

4. Onboarding: 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.

5. Repeated usage: 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.