There are 58,000 AI companies in the world today. 17,000 of them are based in the U.S.

That’s a lot.

Marketers tend to keep up with technology more than most. I’d guess that half the people reading this are already using ChatGPT on a daily basis. We see the potential to erase frivolous work and give ourselves the space to focus on the meaningful tasks in our work. We see the opportunity to do more, faster.

There is a baseline of this newfound efficiency that will be beneficial across the board. We can all have an AI bot write a pretty darn good first draft of meta tags, product descriptions, blog posts and thank you notes. That is a sea change that will lift all ships.

But ultimately, our goal should be to leverage AI to gain competitive advantage for our businesses. And that does not come from using the same tools as everyone else in the same ways they use them. You don’t see companies earning market share because they use email. 

The opportunity to unlock business advantage will come from using AI better than your competitors use it. That means having the best tools and the best operations around them.

The biggest challenge for marketers in mastering AI will be choosing the right tools for the right jobs.

Not all AI is created equal. Different bots use different large language models (LLMs). And since they learn differently, they respond differently. I’m sure many of the curious out there have gone through the exercise of typing the same prompt into multiple Generative AI platforms.

For instance, when I asked several of them, “In 15 words or less, what is the best way to get competitive advantage using Gen AI?”, here’s what I got back.

ChatGPT4: Leverage AI for unique data insights, automation, personalized services, and improved decision-making efficiency.

Claude: Improve decision-making with personalized, data-driven insights from assisted AI.

Bard: Use Gen AI to create unique value for customers.

Pi.ai: Synthesize and analyze data, drive innovation, and optimize processes. 

Perplexity gave me 122 words … and 6 sources.

Ah. Now, we’re getting somewhere. Many Gen AI bots hallucinate. When they don’t have information in their data set, they make something up. Or if they have conflicting information, they guess what is correct.

So, Perplexity can’t count to 15. But it quotes actual sources so I can verify the answers it gives me. What matters more?

Jasper.ai gave me 506 words. It is even worse at counting. But it also asked if I wanted it to be a blank document, a new blog post, new from a template or new art. So, if my goal is counting, Jasper is an abject failure. But if my goal is to create a statement of work or project brief or anything else that fits in a template, it may be the best solution.

The use case completely changes the perspective on what “best” means. Jasper also lets me choose the tone of voice to use in its response (I chose “smartass”) and even read all the content on Traction’s website to create our own branded tone of voice.

While much of the world is focused on changing their job title on LinkedIn to “prompt engineer,” a far better investment of time might be identifying the use cases you need to solve for, then researching the best tools to achieve them.

This problem will only accelerate. Former Canva and Uber growth marketing executive Sunil Subhedar predicted the growth of smaller, more niche LLMs that deliver less costly and more impactful nuanced industry applications. Despite some limitations, small language models are set to excel, because they're being trained with really top-notch data that helps them work better and smarter.  

Small language models don't use up much energy and they're better at adhering to privacy, which is why areas such as health care, finance, cybersecurity and education are about to get a big boost. It's like having a super-focused expert on your team, ready to make things a lot easier while being secure.

That means identifying the perfect tool for your specific problem may become harder and harder just as the value unlocked by AI becomes greater and greater.

Sunil also predicts that multimodal LLMs will be game changers with the ability to seamlessly blend and make sense of the words we speak, the images we share and the numbers we juggle. When these capabilities are united with agent-based generative pre-training transformers, AI doesn't just assist but takes the wheel, steering tasks to completion with a newfound level of independence—freeing us from remedial tasks to focus on what truly matters in our professional and personal lives.

All of this exists today. Who knows what will exist in three weeks, let alone three years?

Finding the right tool on the menu of potential solutions can cause analysis paralysis. But don’t let it stop you. The best step forward is to order something that looks good and give it a try.