November 9, 2023

Become AI Native: What It Means (& How to Do It)

What does the term “AI native” mean?

The term “AI native” is a moving target, and, like everything else in the world of artificial intelligence (AI), the phrase is continuously evolving. Part of the confusion comes from the fact that “AI native” has been used to describe products and companies differently. 

Let’s clear the air by examining how “AI native” has been used in both contexts and see how it should be defined today.

AI native products

Last year, VentureBeat ran an article in which the author, Luis Ceze, CEO at OctoML, made a distinction between products that are “AI-native” and others that are “AI-based.”

Here’s how Ceze makes this distinction:

AI Native refers to products with AI embedded into their core. In other words, if AI wasn’t a part of the product, the product wouldn’t exist. 

AI-based refers to existing products that implement AI to offer new features to users. It’s basically an add-on. 

This is just one of the use cases in which products are AI native.

You’ll find it used earlier in the same context, such as in this post back in 2018 and from this source in 2016

AI native companies

In recent years, a wave of AI native products have hit the market, allowing companies to implement new technology for growth. This has expanded the working definition of “AI native”. Now it’s no longer only about products, but how businesses operate too. 

AI native companies refers to businesses transitioning to an AI-based strategy to improve sales, marketing, customer support, or any other department where this technology can be leveraged. 

According to, “AI native is the concept of having intrinsic trustworthy AI capabilities, where AI is a natural part of the functionality, in terms of design, deployment, operation, and maintenance.” In other words, a company becomes AI native when AI gets permanently baked into the business’s DNA. 

How defines the term “AI native” 

When given a choice, sometimes the best answer is both

As generative AI has become more readily accessible to businesses over the past few years, our team believes the term “AI native” applies to teams implementing AI in both products and operations. 

In fact, we recently hosted a webinar on becoming AI native in which’s Solutions Engineer, Shikhar Singh, defined AI native in the following way: 

“Being AI native means being able to leverage technology to do any job that you can think of. It means getting the focus on strategic work and driving business outcomes that you actually care about as opposed to getting drowned in the mundane things that you probably weren't excited about when you signed up for your job.”

That’s why we’ve worked hard to build a product to help companies transition from being curious about AI to being AI native. And in a moment, we’ll look at that process in more detail.

But first, it’s important to understand where your business (or you personally) currently stands regarding AI maturity. 

Becoming AI native is a marathon, but it’s starting to move like a sprint

To know where you want to go with AI, you first have to know where you are. That way, you can outline an efficient strategy to implement, test, and monitor AI in your current workflows. 

One of the best resources for that is Gartner’s AI Maturity Model AI Maturity matrix

Gartner’s AI maturity level explained 

Level 1: Awareness

At this stage, the business needs to create awareness of AI's potential and possibilities. This can involve educating employees about AI, identifying industry trends and use cases, and exploring how AI can improve the business's products or services. 

The key is to start discussing AI solutions and identifying areas where they could be applied.

Ways to increase your organization’s AI awareness level
  • Host a lunch and learn about the basics of AI
  • Encourage employees to use their education budget on something related to AI
  • Internally distribute training documents and other learning resources 

Level 2: Active

Once the business has identified potential AI use cases, it can start experimenting with the tech. This may include building small-scale AI prototypes, conducting pilots or proofs-of-concept, and testing different AI models. 

The goal is to identify the most promising use cases for AI and determine the business value of implementing them.

Level 3: Operational

Now that a business has identified its most promising AI use cases, it can start deploying AI at scale. This involves integrating AI into the organization's systems and processes, such as sales, marketing, customer service, and supply chain management. 

The goal here is to demonstrate the effectiveness of AI and generate positive results.

Easy operational use cases to test and implement today:

Note: We’ve seen many teams get stuck in steps one and two, never reaching the Operational phase. A good starting point is Chat by, which lets you implement generative AI immediately, regardless of your technical experience. 

Level 4: Systematic

At this stage, the business has successfully deployed AI across the organization and uses it as a core part of its business strategy. This means scaling up AI initiatives, aligning them with the organization's strategic goals, and developing an AI roadmap that guides future investments. 

The goal here is to leverage AI to create new business opportunities and revenue streams. At this level, you’re starting to see AI positively impact your day-to-day operations. 

Whether that means your sales team is getting more leads through cold outreach or marketing is driving more organic traffic with AI tools, the potential for scaling results should be clear early on. 

Level 5: Transformational

At this final stage, the business has fully integrated AI into its operations and business models, driving significant new revenue streams. Here, you’ll be using AI to transform the business's products and services, create new business models, and unlock new channels for revenue. 

The goal is to become an AI-native business where AI is integral to the organization's products and decision-making processes.

Here’s a quick snippet of the impact AI has on as we’re living within the Transformational stage.

Three real-world examples from an AI native company

Regardless of how you define “AI native,” meets the mark without question. Our product relies on AI at its core, and our team uses that product to supercharge growth. 

But don’t take our word for it. Here’s the data on how we’ve scaled as a company:

  • 7 million+ users
  • 28 months
  • 36 employees 

Our team at is small but mighty. When you look at the number of employees vs. the number of users, the growth rate is surprising–even to us, if we’re being honest.

For example, another popular SaaS product, Notion, has 30+ million users. However, they have over 400 employees and started back in 2013. 

So while Notion’s user base is four times more than, their team is 10x larger and has been around for nearly 5x longer

How are we getting such fast results? That’s easy; we’re the biggest users of our own product. 

Here are three ways our team uses to scale growth. 

1. Cold sales outreach 

Before AI was readily accessible, sending cold emails and LinkedIn messages to prospects was time-consuming and tedious for SDRs. They would have to research prospects and gather information. Then they’d create personalized messages by hand. 

This process is often full of rejection and leads to employee turnover (38% of sales staff leave within their first year).

With, sending cold emails and LinkedIn messages to prospects is significantly faster.'s LinkedIn URL scraping feature enables teams to gather relevant information about prospects in seconds: chat and how to use it for cold sales outreach

This has saved our team valuable time and resources by allowing us to create personalized messages at a larger scale (without sacrificing quality).

Did you know? You can automate this process even further with Workflows

2. Prospect research

Back in the day (*ahem… six months ago), sales teams had to manually sift through a prospect's social media content to learn more about them. This process involved visiting each social media platform and reading through their profiles and posts to gain insights into the prospect's interests, pain points, and professional background.

If you’ve ever had a role like this, you understand how painstaking this process can feel. 

Our team uses a particular prompt built into Chat by to scrape LinkedIn profiles and gather key information on prospects:

how to use chat for prospect research

We can then summarize that information into bullet points to see a person’s professional interests and experience:

From there, our sales team can validate the information to craft more compelling offers that increase the efforts of our cold outreach strategy. 

And with Workflows, users can now do this at scale by pulling information from hundreds of LinkedIn profiles simultaneously.   

3. SEO

Whether you’re creating blog posts or landing pages, longer-form content can be a beast to tackle. From finding the right keyword clusters to generating outlines to writing a first draft, most marketing teams struggle to produce more than a handful of posts each month. 

Now, our team uses Chat by to help with every step of the process. 

For landing pages 

Use a pre-written prompt to generate the first draft of your landing page. The prompt ensures you’ll have each section written, such as:

  • Hero
  • Subheader
  • Call to action
  • Tagline
  • H2
  • Supporting paragraph 

You can then modify the output to your liking. 

One of the biggest benefits our team has found was the ability to whip up different versions of copy to test quickly. This allows us to optimize each of our landing pages so that when organic traffic starts flowing in, the page is ready to convert. 

Paired with Infobase, you’ll be producing ready-to-publish landing pages in a matter of minutes.

For blog posts

We don’t think blog posts should be 100% AI-driven. But we also don’t think they need to be 100% human-written, either. 

The best is when AI meets your human creativity to achieve something BIG. 

Our marketing team uses Chat by to brainstorm content ideas and keyword clusters. This gives us a springboard to start playing with our more advanced SEO tools and verify which post topics would be best to pursue. 

Then we like to use the Blog Outline prompt to generate the first draft of an outline. But, from there, we do even more manual research on Google to make sure the outline matches the intent of the keyword we want to target. 

With the outline created, we move to the post's first draft.  

This is where the features of Chat by shine, mainly because it’s plugged into the web. That means it can provide fresh and relevant links when researching sections of your posts. 

This gives our team (and our users) more confidence in the generated output than when we’ve tried similar tools that aren’t synced to the web (such as ChatGPT, for example). 

Again, and not to sound like a broken record here, but we never publish anything without manual intervention. Our team takes what generates and polishes it up, often leading to higher-quality posts in less time than it used to take. 

But look, that’s been our story. Now, we want to focus on yours. 

Let’s look at how your business can become AI native. 

How to become AI native

To become AI native, companies need to embrace AI technologies and leverage them to drive significant improvements in their operations. 

Here are some essential steps to take to become AI native.

1. Develop a clear AI strategy

Start by outlining your organization's AI goals and objectives. Determine which areas of your business can benefit the most from AI adoption and establish a roadmap to guide your efforts. 

Be sure to align your AI strategy with your overall business strategy to make sure your AI initiatives support your broader objectives.

And in case you were wondering, this step aligns with the Awareness stage of Gartner's AI Maturity Model. 

By outlining your organization's AI goals and objectives, you begin understanding how AI can be applied within your business. In other words, your business is becoming AI-aware

Key takeaway: To successfully integrate AI into your business, identify your organization's AI goals and objectives. Assess which areas can benefit the most from AI and create a strategic roadmap that aligns with your overall business strategy.

2. Build internal AI expertise

Invest in training and development to cultivate AI knowledge and skills within your organization. When possible, encourage team members to attend AI-related workshops, conferences, and online courses to stay updated with the latest developments and best practices in the field. 

But remember, the depth of your team’s technical knowledge will depend on your specific needs/goals.

For example, larger companies like Microsoft or Google might use advanced AI models to learn more about their massive audience. Often, as the problem AI is used to solve becomes more complex, the need for AI expertise increases.  

But smaller teams with more limited needs may not need to spend too much time on this step, especially when working with a tool like (more on that in just a moment). 

Building internal AI expertise corresponds to the Active stage in Gartner's AI Maturity Model. As your organization gains knowledge and skills related to AI, you will be better prepared to implement pilot projects and proofs of concept. 

Key takeaway: Foster AI expertise within your organization by investing in training and development. Encourage team members to attend workshops, conferences, and online courses to stay up-to-date on AI advancements.

3. Experiment and learn

Begin with pilot projects to test and validate AI in your organization. Use these experiments to learn about the benefits, challenges, and potential ROI of AI solutions to optimize your operational processes. 

Then, refine your approach based on the results and continuously seek new ways to leverage AI in your business.

Experimentation is another central component of the Active stage of Gartner's AI Maturity Model. Experiments provide valuable insights into the benefits and challenges of AI deployment, which will help your team as it becomes AI operational. 

When one of your experiments works, you can bring it to key decision-makers as a proof of concept. 

Key takeaway: Start with pilot projects to test and validate AI in your organization. Use these experiments to learn about the benefits, challenges, and potential ROI of AI solutions to optimize your operational processes. 

4. Scale AI adoption

Once you’ve validated AI technologies through experimentation, move to implement them within your organization. Integrate AI into your existing processes and workflows and regularly monitor the impact to make sure your efforts are giving you the results you want.

Scaling AI adoption aligns with the Operational stage in Gartner's AI Maturity Model. 

At this stage, your organization is actively deploying AI solutions and integrating them into standard processes and workflows. It demonstrates a clear commitment to AI and is an exciting moment for any company refusing to get left behind. 

Key takeaway: After validating AI technologies through experimentation, integrate AI into your existing workflows where applicable. 

How to get started 

The easiest place for companies to become AI operational is with Chat by

Chat by is a chatbot that ultimately lowers the barrier of entry with AI technology. You can ask Chat for help with the following: 

  • Research
  • Ideation
  • Content creation and personalization
  • Copywriting 
  • Translations
  • Summarizations 

And much more. Then, whatever you need will be generated like magic: 

This is important because most teams get stuck in the first two stages of Gartner’s Maturity Model (Aware and Active) but never truly become operational. 

Chat by puts intuitive AI in your hands from day one. 

In the next ten minutes, your marketing team could: 

  • Write the first draft of an entire SEO-friendly blog post 
  • Repurpose that article into a YouTube script and social posts for five different channels  
  • Create fresh ad copy to test for your PPC campaigns 
  • Translate marketing content for your international audience 

And at the same time, your sales team could:

  • Generate personalized sales emails from a prospect’s LinkedIn URL 
  • Create tailored cold outreach messaging for LinkedIn 
  • Summarize training calls (from platforms like, for example) to improve performance 
  • Research a new lead by scraping information about them off the web 

Now, without any previous knowledge of AI, you can transform your growth strategy and immediately implement one of the most revolutionary tools at your disposal.   

That said, describing what Chat by feels like would be like trying to describe the color blue: it’s infinitely easier if you go see for yourself. 

Become AI operational with Chat by today

5. Foster a culture of innovation

Encourage a culture of experimentation and continuous improvement within your organization. Empower your employees to explore new ideas, challenge assumptions, and embrace AI-driven decision-making. 

This will help your organization adapt to the rapidly evolving AI landscape and maintain a competitive edge.

Fostering a culture of innovation is a key aspect of the Systematic and Transformational stages in Gartner's AI Maturity Model. It’s what will encourage your team to unlock new growth potential as your team openly experiments and optimizes your strategy. 

Key takeaway: Adding AI into your daily ops is an ongoing, iterative process at the beginning. Build a culture that encourages curiosity, experimentation, and optimization wit AI tools. 

Move toward becoming AI native today 

As the world of artificial intelligence continues to evolve, businesses need to stay ahead of the curve to stay competitive. By understanding where you currently stand on Gartner's AI Maturity Model and implementing AI-driven solutions accordingly, you'll set your company on a path toward success in this rapidly changing landscape.

One of the most effective ways to start your journey toward becoming AI native is by leveraging an AI as a service platform like

This intuitive chatbot offers a wide range of AI-driven capabilities, from research and ideation to content creation and translation. With a user-friendly interface, Chat by allows your team to hit the ground running, even if you have limited experience with AI. 

The future of growth is here, and it's time to join the ranks of AI-native companies. Take the first step by trying Chat by and experience the power of AI-driven solutions firsthand. 

Your stakeholders will thank you for it.

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