AI Personalization

Beyond Generative AI: How to Choose a Strategic Solution

Erica Dingman

Why AI?

Every tech solution on the market has been boasting its latest AI enhancements, and why you need it to deliver best-in-class content that engages your customers. The constant push for AI can turn into white noise for marketers, but when you slice away all of the promotions and buzzwords, there’s an undeniable element of truth. AI in its current iteration is still relatively new, but it’s quickly become a necessity.

In fact, 54% of US marketing executives say that AI currently contributes to their workflow, and the industry is projected to reach $36 billion in revenue by the end of 2024—small potatoes to the $107 billion it’s slated to reach by 2028.

The direction that martech is headed is clear. But if marketers want to be leaders in AI, they need to do more than simply hop on the generative AI train and automate a few tasks. They must pair generative AI with other emerging technologies that drive value across their workflow, from content to analytics. To start that journey, marketers can begin with these simple steps to effective AI adoption.

Understand Your AI Options

Everyone has an AI “aha” moment, a time when AI’s rapid power truly surprised and delighted us. Whether that was discovering Chat-GPT was a fantastic source for recipes, or generating something silly and fun like an elephant made of leaves.

Leaf covered elephant

But how do AI’s incredible results actually happen? Whether it’s via predictive AI, deep learning, generative AI—or a combination of these models and more—knowing what essential AI terms actually mean  is critical to understanding which solutions to explore:

Generative AI is the most popular type of AI, typically used to create text, images, and videos for promotions, advertising, and campaigns.

Unsupervised Learning generates valuable insights from large datasets, such as understanding customer preferences, identifying similar groups of customers, and monitoring analytics data.

Supervised Learning automates decision-making based on inputted data, determining next-best actions, recommending products and offers, and making deployment decisions.

Clearly, there’s far more potential to AI than its generative iteration. For marketers specifically, being able to conduct accurate, in-depth analysis or make strategic, data-driven decisioning at scale is arguably even more valuable than automating images and text. With this understanding in mind, marketers can begin the next step in their AI adoption journey: choosing a vendor that offers greater value than what’s available through the typical open-source, generative tools.

Choose the Right Vendor

To choose the right AI vendor, you’ll need to take several present and future factors into consideration. From flexibility to robust data capabilities, this is a quick list of what to watch out for when choosing an AI solution:

Integrations and Flexibility

To choose the right AI vendor, you first need to analyze your existing martech ecosystem. Find an AI that not only fills a need that your current tools cannot accomplish, but fits in smoothly with your existing investments.

No one wants to rip-and-replace all of their existing solutions to make way for AI. If you already have long-standing investments as most marketers do, seek out an agnostic AI solution that can integrate smoothly into your existing tech stack and adapt to add-ons as needed.

Data Infrastructure

No matter the tool, the right data framework is critical. The AI you choose should be able to activate high-quality, relevant data—such as real-time, zero-party, and first-party data—into enticing content.

For real-time data, the AI must be able to pull from multiple sources and immediately transform it into content, all while using the data to train and enhance the AI model. In the case of zero- and first-party data, the AI must be able to access it from common repositories like CDPs, CRMs, and data warehouses. Whatever the type of data source, the AI should be able to easily access and activate it.

Brand Integrity and Transparency

There’s nothing more valuable and sensitive than customer data, so choosing an AI that protects it is non-negotiable. The AI should avoid commingling client data with additional sources, and must be built with data privacy compliance in mind.

Additionally, how the AI treats data and information should be crystal clear. As the marketer, you need to be fully aware of how your AI creates content and reports its results for the sake of your brand and your customers.

With all of these factors in mind, it’s abundantly clear that whatever AI you choose, a proprietary solution is the necessary choice. Don’t be fooled by flashy AI features that are just another version of GPT; look for proprietary AI that has robust rules and regulations in place and delivers real value to your content outputs.

Identify Your Pain Points

You need to walk before you can run. Before trying to apply AI to every phase of your workflow, identify your key pain points and areas for improvement. For example, do you want to improve productivity, content output, or campaign performance? From those broad buckets, drill down even further to specific programs, such as batched emails or optimizing the longevity of your creative assets.

Whatever you choose, be sure to define your goals and objectives from the get-go and be ready to test, iterate, and test again. Just like any other tool, the longer you use AI, the more effective it will ultimately be.

You’re Ready to Start the AI Journey

By keeping these steps in mind, you’ll be able to adopt AI efficiently and effectively into your existing workflows and messaging. To discover more about how you can leverage AI’s capabilities, explore the related resources below.