AI-ify: Why (And How) Brands Are Creating Their Own AI Tools

If you haven’t seen it yet, you will soon. 

The world of branding is undergoing a transformative shift, with artificial intelligence at its core. From personalized customer experiences to data-driven decision-making, brands are no longer just utilizing AI—they’re creating their own bespoke tools tailored to their customers’ unique needs.

This isn’t just a fleeting trend; it’s a revolution that’s reshaping the business landscape. In this article, we’ll delve into the ‘why’ behind this movement and provide a comprehensive guide on the ‘how’ for brands eager to embark on their own AI journey. 

Welcome to the era of AI-ify, where brands are not just adapting to AI but actively shaping its future.

The AI Tool Pyramid: Types of AI Tools

The journey through AI-ification can be visualized as a pyramid consisting of four distinct but interconnected levels.

1. Tool Enhancement: This foundational level involves merely modifying existing tools with AI features. It’s an entry point that spices up conventional tools with a dash of AI, offering improved utility and functionality without any radical changes.
2. Tool Replacement: As brands progress, they replace existing tools entirely with AI-powered versions. This stage signifies a leap from simply enhancing to full-on substitution with AI tools, harnessing more sophisticated AI capabilities.
3. Tool Creation: The next level involves the creation of entirely new tools powered by AI. Here, AI is no longer supplementing or replacing but innovating, embodying the creation of tools that wouldn’t exist without AI.
4. Platform-Level Innovation: The apex of the pyramid is where brands leverage AI to create entirely new types of platforms. It represents the most advanced stage of AI-ification, where AI drives systemic changes and births unprecedented platforms.

This pyramid is dynamic and allows brands to ascend from one level to the next. It is a roadmap for companies eager to leverage AI, providing a clear path from using AI as a supportive element to it being the driving force of innovation.

The AI tool pyramid serves not just as a guide but also as an indicator of how forward-thinking a brand is in its approach towards AI. For a brand at the foundational level, using AI merely as an enhancement, it might be considered as keeping up with the times.

However, as brands ascend the pyramid, replacing old tools with AI-powered versions, creating new AI tools, and eventually fostering platform-level innovation, they demonstrate an increasing level of sophistication and originality. They showcase a commitment to driving change rather than merely adapting to it. Hence, the positioning of a brand on this pyramid can provide a tangible benchmark to gauge its progressiveness and whether it is truly on the cutting edge of technology and innovation.

Basic AI Use: Tool Enhancement

The Tool Enhancement stage is the entry point into the world of AI for many brands. In this stage, existing tools or processes are augmented with AI capabilities to increase efficiency and functionality. 

For instance, a company might incorporate machine learning into its customer service operations to handle routine queries, freeing up staff to handle more complex issues. Or a brand could utilize AI algorithms to enhance product recommendations on its ecommerce platform, increasing the likelihood of customer purchases.

The upside of this approach is vast. By integrating AI into existing tools, brands can deliver a better user experience without having to reinvent the wheel. The learning curve is relatively flat, as users are already familiar with the existing tools. 

Costs are also generally lower at this stage, as tool enhancement often requires less resource investment than creating new tools from scratch. Of course, the most important benefit is improved customer satisfaction, as AI tools are often better equipped to respond more quickly and accurately than a team can.

On the downside, the Tool Enhancement stage, while valuable, only scratches the surface of what AI can achieve. Brands may be limited by the capabilities of the existing tools they are enhancing and may not be fully harnessing the power of AI. 

Relying on AI for tool enhancement can also bear the risk of over-reliance on technology, possibly neglecting the human aspect of certain roles and tasks. Companies at this stage must be cautious not to view AI as a panacea but as an enabler—a means to an end rather than an end in itself.

The Next Level: Tool Replacement

The Tool Replacement stage represents a significant step up from the previous level. Here, brands transition from merely enhancing existing tools with AI capabilities to replacing them entirely with AI-powered versions. This level signifies a leap from simply enhancing to full-on substitution, thus harnessing more sophisticated AI capabilities.

An example of this can be seen in the retail sector, where brands replace traditional inventory management systems with AI-powered versions. These AI tools have the ability to forecast demand and manage inventory autonomously, reducing human error and freeing up staff for more strategic tasks.

The advantages of this approach are considerable. Tool replacement often leads to increased efficiency and accuracy, as AI-powered tools can perform tasks faster and more precisely than their human counterparts. Moreover, these tools can operate 24/7, leading to continuous productivity. Such tools also have the potential to analyze vast amounts of data in real time, delivering actionable insights that enable better decision-making.

However, the Tool Replacement stage also has its share of challenges. The initial cost of replacing existing tools with AI-powered versions can be high, and there may be resistance from employees who fear job loss or are uncomfortable with adopting new technology. 

Additionally, while these AI tools might offer more advanced capabilities than enhancements, they might still be underutilizing AI’s full potential. At this stage, AI is functioning within the boundaries of existing roles and processes rather than creating entirely new ones.

Another issue to consider is that of dependence on AI. While AI tools can significantly enhance operations, overreliance on them can lead to complacency and a lack of human oversight, potentially resulting in unforeseen problems. Furthermore, AI tools, like any technology, are not immune to failure or malfunction, so it’s crucial to have contingency plans in place.

The black box problem can also be a major issue at this stage. Companies just beginning to replace old tools with AI-powered ones can see AI as a “black box” they don’t understand, and they can run into issues when it gives strange outputs for reasons that aren’t immediately apparent. That can slow down the very processes AI is meant to quicken.

Breaking New Ground: Tool Creation

The Tool Creation stage marks a significant shift in AI utilization, where brands create entirely new tools powered solely by AI. Brands are no longer confined to improving existing tools or replacing them but are now innovating and creating tools that would not exist without AI.

For example, in the healthcare sector, AI has birthed new tools like predictive analytics systems that can forecast disease outbreak patterns or patient deterioration rates. In the financial industry, AI has given rise to robo-advisors, which provide automated, algorithm-driven financial planning services with little to no human supervision.

The benefits of this stage are abundant. It represents a step towards fully exploiting AI’s potential as not just a supplementary or replacement tool but as an innovative agent birthing tools that were previously inconceivable. It allows brands to leapfrog competitors by providing unique, value-added services that set them apart. Furthermore, these new tools can drastically improve efficiency, accuracy, and cost-effectiveness, delivering better user experiences and driving customer loyalty.

From a branding perspective, this has obvious benefits as well. If you have unique AI-powered tools, you’re positioned as a clear market leader. Your competitors are forced to try and duplicate your efforts at their own significant cost while you move forward by innovating and creating even more great tools.

However, the Tool Creation stage also presents its own set of challenges. The development of new AI tools can be a costly and time-consuming venture with no guaranteed return on investment. It may also require specialized talent and resources that are not readily available within the organization.

Moreover, these new tools can face resistance from customers and employees who are accustomed to traditional methods and wary of change. The black box problem grows more prominent here, as these new tools can be complex and difficult for users to understand. This lack of transparency can lead to mistrust and skepticism.

Finally, the creation of new AI tools can raise ethical and regulatory concerns. For instance, AI tools that handle sensitive data must comply with data protection regulations. If not properly implemented, these tools could inadvertently breach privacy norms or lead to discriminatory practices. Brands venturing into the Tool Creation stage must be prepared to address these challenges head-on.

The Cutting Edge: Platform-Level Innovation

The Platform-Level Innovation stage represents the pinnacle of AI utilization. Here, brands leverage AI to create entirely new types of platforms. The key players at this level are usually AI-first companies like OpenAI—entities that have AI at the heart of their business model and are at the forefront of AI innovation.

AI-first companies are usually born out of a conviction that AI can redefine the landscape of an entire industry. They are typically able to tackle the most challenging aspects of AI: comprehending the subtleties of human language, learning independently from sparse, unstructured data, and even exhibiting creativity.

OpenAI, for example, has developed GPT, a language prediction model that can write essays, answer questions, translate languages, and even generate Python code. It’s an entirely new kind of platform that even leading tech companies struggle to emulate.

The Platform-Level Innovation stage brings numerous advantages. It allows a company to create entirely new markets and value networks, disrupt existing ones, and propel the company to market dominance. That much is obvious—it’s why McKinsey estimates that AI could have a total value of up to $4.4 trillion. The brand reputation also sees a significant boost, as the company is viewed as a leader, innovator, and disruptor.

However, the challenges at this stage are equally substantial. The AI models used to create these new platforms are often complex and require significant computational resources, leading to high upfront costs. The platforms must also be continuously monitored and updated to ensure they remain effective and accurate.

Additionally, these companies face significant responsibility in terms of the ethical implications of their technology. They need to ensure that their AI-powered platforms do not perpetuate biases, violate privacy norms, or contribute to social inequality.

Finally, the unique nature of these platforms often puts them in uncharted regulatory waters. This can lead to legal uncertainties and potential disputes as lawmakers scramble to catch up with the rapid pace of AI innovation.

Why Build Custom AI Tools

No matter what level of the pyramid you’re looking at, there are distinct advantages to AI-ification. Automating mundane tasks or eliminating manual labor can free up employees to focus on more complex and meaningful work. By leveraging algorithms that can learn from previous actions, organizations can become smarter and better equipped to make decisions quickly and accurately.

I’ve tested 30 different AI tools over the last two weeks and am more convinced than ever that the marketing industry is going to be changed forever.

It won’t all change in 2023.

But change is coming.

— Ross Simmonds (@TheCoolestCool) January 2, 2023

Here are a few of the reasons why you should look at AI-ifying:

1. Tailored Solutions

You and your clients have unique needs. Whether you’re building a tool for internal or external use, having a tailored solution is the best way to solve it as directly as possible.

From a branding perspective, this has unique benefits, too. If you build a custom AI tool for clients, they know that you’re genuinely looking out for their best interests. AI-ification establishes you as the go-to problem solver for their needs, as well as a company that’s willing to lay down the resources to solve sticky issues.

1. Brand-Building as Innovators

Innovation is a hard reputation to beat. Apple spent significant resources developing the iPhone and used it to build a brand around innovation. Even though the company isn’t always at the bleeding edge anymore—just look at the unique features offered by competitors—it retains its reputation as an innovative company.

In the same way, you can set your own brand’s reputation as innovative by embracing AI while it’s still in its early stages right now. Companies with AI tools are seen as more advanced, which gives them a boost of credibility and trust. Putting your company in a position to take advantage of AI is a great way to build your reputation as an innovator.

1. Data Security

Building your own AI solution also has data security advantages. While some companies are trying to jump on the AI trend by simply implementing AI tools created by other vendors, that can present problems from a security perspective.

That’s because it’s difficult to tell what information an AI tool is taking from your system and using for its own dataset. If you work in healthcare, as a government contractor, or in other information-sensitive industries, that could cause a problematic breach of security guidelines. 

But by building your own tool, you can control what information it uses and where it goes. It’s the only way to be completely certain that the tool’s owner (you!) is treating the data the way it needs to be treated.

How to Implement Your AI Tool

AI tools can be unpredictable when it comes to their behavior. That’s why launching an AI tool is very different from launching a traditional product. With the former, you don’t have a tried-and-tested system that can be improved over time. Instead, you have to make sure that the AI tool is ready to go from day one and is able to handle whatever comes its way. 

Here are a few different ways that companies have chosen to implement their AI tools:

Closed Beta 

If you give closed beta access to your AI tool, you pick a select set of users and give them access to the tool before it’s ready for a wider release.

A closed beta can give you access to crucial user feedback. This stage helps identify and rectify bugs, adjust to unexpected user behaviors, and collect initial testimonials, which aids the AI model in evolving through real-world interactions, enhancing its accuracy and dependability. 

Despite its merits, it’s time- and cost-intensive, and implementing feedback quickly is crucial. For effective AI tool beta execution, select a feedback-rich user sample, communicate the beta nature openly, have a sturdy feedback analysis and implementation system, and keep participants updated on modifications inspired by their feedback.

Open Beta

An open beta, similar to a closed beta but open to the public, allows a wider audience to test the AI tool, providing invaluable data and diverse user interactions. Typically, anyone is able to opt in to access the beta.

Suited for AI due to the vast data collection potential, it aids in refining the tool’s response and adaptability. However, it may reveal flaws to a larger audience, affecting brand image. 

One of Foundation’s own Senior Content Marketing Specialists, Enzo Carletti, recommends that “transparency and positioning are the two public relations pillars to focus on.” Those pillars help you address two core audiences: laypeople and people with a high degree of competency with technology.

“The high-competency folks will look for holes and data misuse. Transparency and clearly outlined policies will save you headaches with them,” Carletti says. “For laypeople, it’s important to nail the positioning. They should feel like they understand how your product will help society, not hinder it. Without a clear narrative to sell, you’ll be forgotten as soon as the next copycat app hits the market.”

General Availability

Of course, another way to implement an AI tool is to simply release it into general availability. As you might expect, this can have drawbacks as well: Without a closed or open beta stage, you may miss crucial user feedback.

This can also take much longer since you need to be sure that you’ve fully polished the tool before you launch it to the public. However, waiting to show the tool to any users until it’s done could have the advantage of giving your brand a more polished, professional appearance.

How to AI-ify Your Marketing

As AI tools become ubiquitous, marketers are constantly asking how they can embrace AI. While we aren’t always the ones building new AI tools, it’s important that we know what kinds of tools our companies are launching, how to market them, and their implementation strategies. 

That’s why Foundation is always looking to stay on the forefront of how companies are addressing AI in marketing. With our weekly breakdowns, we’re constantly looking for ways to catch the industry at its cutting edge. Check out our piece on how marketers can use AI in 2024 for more!