April 9, 2024

Embracing the Future: Why You Need AI-Native Solutions

Artificial Intelligence (AI) has transitioned from a futuristic concept to a fundamental component of successful business operations.

With the capacity to analyze vast amounts of data, automate processes, and enhance decision-making, AI is reshaping industries like healthcare, telecom, and consumer goods as well as redefining customer experiences both online and off.

Now, organizations are faced with an important choice: adopting AI-native solutions or retrofitting existing systems with bolt-on AI features. Choosing AI-native solutions is not merely a preference but a strategic imperative for companies aiming to harness the full power of AI. 

The Rise of AI Adoption in Businesses

As Henry Bristol et al. at McKinsey writes, “AI has brought the Fourth Industrial Revolution to an inflection point, and [businesses] must choose a path forward: innovate, accelerate, or follow fast.” 

Their 2023 State of AI Survey strengthens this finding, revealing that approximately half of all organizations have adopted AI in at least one business function, and one-third have adopted generative AI (gen AI) less than a year after these tools debuted. 

This uptick in AI adoption is a strategic, sweeping response to the changing business environment accentuated by the COVID-19 pandemic—the necessity for remote work, real-time data analysis, and cost efficiencies. The crisis acted as a catalyst for the shift towards digital solutions and driving an unprecedented demand for AI capabilities. 

However, overall adoption has remained steady, signaling that the companies already implementing AI in their business are the ones reaping the benefits of further AI developments.

Businesses are increasingly leaning on AI for its predictive power in scenarios ranging from consumer behavior forecasting to supply chain disruptions. This landscape is further encouraged by rapid advancements in sophisticated machine learning models, breakthroughs in natural language processing, and the democratization of AI tools. 

Which industries are benefiting from AI the most?

While tech, media, and telecom industries are leading in heavy adoption rates, here are some other industries benefiting from AI advancements:

  • Manufacturing: With more data access, businesses can apply artificial intelligence and machine learning models for improved operational efficiency, product quality, and predictive maintenance.
  • Finance: Through real-time data analysis, AI helps detect fraud issues and market fluctuations. 48% of professionals in the risk space reported some revenue increase as a direct result of AI adoption, according to McKinsey. 
  • Information Technology: AI in IT primarily revolves around automating repetitive tasks, scaling business operations, and enhancing cybersecurity for larger enterprises in major cities around the world.
  • Other Industries: AI capabilities like natural language processing, computer vision, and robotic process automation are being deployed across various sectors, doubling from 1.9 in 2018 to 3.8 in 2022. These capabilities facilitate better customer engagement, data analysis, operational efficiency, and much more.

Most importantly?

The organizations that are the quickest to adopt new advancements in AI are the ones to reap the biggest rewards (including financially outperforming competitors by 2.3x). And the distance between the leaders and the laggards is big—and only getting bigger, thanks to the compounded effect of embedding AI within the organization. (Or, as we show below, becoming AI native.)

As this trajectory is unlikely to slow down, it insists on a new chapter in business where AI is not just optional, but fundamental to business success.

Defining AI-Native and AI-Based Solutions

The term “AI native” is a moving target, and, like everything else in the world of AI, the phrase is continuously evolving. Some confusion has come from the fact that “AI native” has been used to describe both products and companies

When what we should really be distinguishing between is AI native and AI as an add-on. It’s similar to the way Luis Ceze, CEO at OctoML differentiates between AI native and “AI-based” in a VentureBeat article.

“If AI is not the reason it exists; it’s not AI-native. Plain and simple,” says Ceze.

AI native refers to products, services, and companies that only function because AI is crucial to their core functioning and product. In other words, if AI wasn’t a part of the equation, the product or service simply wouldn’t exist. 

AI native companies are using an AI-based strategy to improve sales, marketing, customer support, or any other department where this technology can be leveraged. In other words, a company becomes AI native when AI gets permanently baked into the business’s DNA. 

TikTok is a great example of an AI native company (apart from Copy.ai), where AI is central to both the user and the creator experience, as well as the key to its operations engine.

AI-based refers to existing products that implement AI to offer new features to users. It’s basically an add-on—and you see it everywhere: “Now with AI!”

An example is YouTube, which “merely uses AI as a medium to drive consumption, but it’s not central to the user experience” according to Ceze.

“AI native is the concept… where AI is a natural part of the functionality, in terms of design, deployment, operation, and maintenance.” - According to Ericsson.com

Copy.ai is an example of an AI native company: not only would our tools (like Workflows or AI Sales OS) not exist without AI, we also wouldn’t be able to accomplish all we do without AI powering a massive part of our operations.

How Copy.ai defines the term “AI native” 

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 Copy.ai’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 an AI native offering that helps companies improve in every go-to-market area—not just in individual silos.

The Case for AI-Native Solutions

Bolt-on AI solutions are often perceived as quick fixes, allowing businesses to leverage AI capabilities without the need for substantial overhauls. However, they commonly fall short of expectations. Being externally added to the existing system architecture, their lack of an integrated foundation often leads to disjointed operations, limited functionality, and missed strategic opportunities.

Choosing AI-native solutions is crucial for companies that are serious about leveraging the full potential of AI. Here's why:

Seamless Integration and Scalability

AI-native solutions, on the contrary, are designed from the ground up for deep, seamless integration with your existing business ecosystem and tech stack. They interact harmoniously with your databases, tools, and software, eliminating fragmented data flow and operational bottlenecks commonly faced with bolt-on AI.

“The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage.” — Paul Daugherty, chief technology and innovation officer, Accenture

Moreover, AI-native platforms offer substantial scalability advantages. As your business grows and evolves, so too does your AI system because it’s built on flexible architecture. 

It's like getting a custom suit tailored to your body, adapting and growing as you do—without the need for extensive reconstruction when you go up or down a size.

Advanced Capabilities and Performance

The ground-up approach of AI-native solutions often outperforms bolt-on AI in terms of capabilities. They can offer advanced options such as predictive analytics and personalized customer experiences, both of which can be crucial in driving business growth.

For instance, predictive analytics enables robust forecasting and aids in proactive decision-making while personalized customer experiences cater to individual user needs, thereby boosting customer satisfaction and loyalty.

"Ultimately, for AI to make a sizable contribution to a company’s bottom line, organizations must scale the technology across the organization, infusing it in core business processes, workflows, and customer journeys to optimize decision making and operations daily.” - Jacomo Corbo, co-founder and chief scientist, QuantumBlack 

As highlighted by McKinsey, AI-native organizations realized four critical outcomes: driving revenue protection and growth, transforming the cost structure, providing a frictionless customer experience, and meeting new workplace demands. 

Long-Term Cost Effectiveness

On the surface, adopting AI-native solutions might seem more expensive compared to upgrading existing systems with bolt-on AI. However, the cost implications over the long term tell a different story.

Alex Singla, Senior Partner and Global Leader of QuantumBlack, AI by McKinsey, emphasizes that "To ensure a strong return on investment and unlock value, companies must balance the immediate gains with the development of long-term foundations needed to scale AI."

AI-native solutions can reduce long-term operational costs by improving efficiency and fostering automation. Though the initial investment might be higher, the eventual returns more than compensate for it.

In essence, AI-native solutions are not just about adopting new technology; they're about embracing a future where AI is integral to business strategy and execution. By choosing these solutions, companies position themselves to take advantage of all the operational efficiencies and opportunities of AI, and realize the benefits before their competitors.

The Current AI-Adoption Scale

To know where you want to go with AI, you first have to know where you are. 

The Gartner AI Maturity Model is one of the most helpful in understanding how to assess not just where your company is with AI adoption, but where the solutions and partners you’re considering are at—so you can choose the most AI native solutions.

Copy.ai AI Maturity matrix

Gartner’s AI maturity level explained 

Level 1: Awareness

Most companies today fall under this level, where their businesses are barely benefitting from AI.

At this stage, the business is just focused on creating awareness of AI's potential and possibilities. 

Level 2: Active

In the active phase, businesses start experimenting with AI through prototypes and tests to uncover valuable AI applications—as well as determine their business value.

Level 3: Operational

After pinpointing key AI applications, businesses can deploy AI integration at scale into key operations.

Simple applications include automating sales outreach, content creation for SEO, and mass-producing product descriptions. 

Many teams stall before this stage, but platforms like Chat by Copy.ai can offer an easy inroad to embedding generative AI within your organizational processes.

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—like getting more leads through cold outreach or an increase in organic traffic thanks to automated SEO workflows.

Level 5: Transformational

At the transformational stage, AI is deeply woven into the fabric of the business, reshaping products, services, and business models. 

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 how Copy.ai functions as an AI native business:

Three real-world examples from an AI native company

Copy.ai epitomizes the "AI native" label, with a product built on AI technology to propel company growth. Our product is build with AI at its core, and our team uses that product to supercharge growth.

Here’s the data on how we’ve scaled as a company:

  • 7 million+ users
  • 28 months
  • 36 employees

Compared to another popular SaaS tool, Notion, which was founded in 2013, has 30+ million users, and 2-300 employees, Copy.ai is small but mighty.

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

So, how are we getting such fast results? That’s easy. We're the biggest users of our own product, and the proof that AI native architecture works.

Here are three ways our team uses Copy.ai to scale growth:

1. Cold Sales Outreach

Traditional methods were inefficient; SDRs manually researched and crafted messages leading to high turnover. Now, Copy.ai shortens prospecting time with features like LinkedIn URL scraping, enabling faster, larger-scale, personalized outreach without compromising quality. Workflows further automate all parts of cold sales outreach.

2. Prospect Research

Sales teams previously spent significant time manually analyzing prospects' social media. Copy.ai's prompt technology streamlines this by extracting and summarizing LinkedIn profile details. The team verifies this to strengthen cold outreach, and Workflows permit massive scale operations.

3. SEO

Generating SEO-optimized long-form content is challenging and time consuming. Copy.ai assists from inception to draft creation:

  • Landing pages: Drafts are quickly produced using specific prompts. The team can craft various versions for A/B testing, then pair with Infobase to publish ready-to-use pages.
  • Blog posts: AI and human creativity combine to produce content that's strategically brainstormed and SEO-aligned. Chat by Copy.ai offers support from ideation to draft execution, plugged into the web for fresh data, resulting in content that's more reliable than competing tools.

The bottom line: Copy.ai's innovative use of its own AI tool has streamlined sales processes, content creation, and organizational bottlenecks, allowing for significant growth. By sharing this methodology, Copy.ai encourages other businesses to integrate AI native solutions.

How to Choose AI Native Solutions

To become AI native, companies need to embrace AI technologies and leverage them to drive significant improvements in their operations. When you choose an AI native solution like Copy.ai, you start seeing impacts of it in every area of your go-to-market engine. 

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. 

Maybe you want to create efficiencies for your sales team by handing them a massive data engine that can assess, analyze, and provide insights on sales calls, emails, and overall sales goals. (We’ve got good news for you if that’s your goal: AI Sales OS is here.)

By outlining your organization's AI goals and objectives, you become AI-aware

2. Build internal AI expertise

When you invest in training and development to cultivate AI knowledge and skills within your organization, you help your team 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. But small-to-medium teams may immediately realize the place for efficiencies where AI can help—and may not need to skill up too much in this step—especially when working with a tool like Copy.ai’s Chat.

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

4. Scale AI adoption with an AI native platform

Once you’ve validated AI technologies through experimentation, move to implement them across your organization. Regularly monitor the impact to make sure your efforts are giving you the results you want.

At this stage, your organization is actively deploying AI solutions and integrating them into standard processes and workflows.

How to get started 

The easiest place for companies to become AI operational is with AI Sales OS or AI Marketing OS by Copy.ai.

AI Sales OS can help you sales teams accomplish this in the next 10 minutes

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

At the same time, your marketing team could use AI Marketing OS to: 

  • 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 

What’s incredible about our innovative (and the world’s first) GTM AI platform is that it puts intuitive AI in your company’s hands from day one, across all go-to-market areas—while simultaneously eliminating the tool bloat that most organizations deal with.  

Which is especially important, because most teams get stuck in the first two stages of Gartner’s Maturity Model (Aware and Active)—and never truly become operational, or AI native. 

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.   

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. 

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. 

“Right now, people talk about being an AI company. There was a time after the iPhone App Store launch where people talked about being a mobile company. But no software company says they’re a mobile company now because it’d be unthinkable to not have a mobile app. And it’ll be unthinkable not to have intelligence integrated into every product and service. It’ll just be an expected, obvious thing.” — Sam Altman, co-founder and CEO, OpenAI 

Choose AI native for your company, today 

As the world of artificial intelligence continues to evolve, businesses that don’t keep up with the power and of AI will simply be left behind in the dust. 

By understanding where you (and the solutions you’re considering using) stand on Gartner's AI Maturity Model before implementing new AI-driven tools or processes, you'll set your company on a path toward success in this rapidly changing landscape.

One of the most effective ways to embed AI native solutions in your business is by leveraging our comprehensive GTM AI platforms for sales and marketing team. 

Our platforms offers a wide range of AI native capabilities, from research and ideation to content creation, translation, data analysis, and transcription. Copy.ai allows your team to hit the ground running, even if you have limited experience with AI—or your organization is not as mature as others on the AI spectrum.

The future of growth is here, and it's time to see all the benefits, growth, and success that companies see (almost immediately) from adopting AI native solutions. Take the first step by trying Copy.ai and experience the power of AI natives solutions firsthand. 

Your stakeholders will thank you for it.

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