Mastering AI Marketing

(This post was originally published in Ad Age)

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, datadriven 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.

[Image by MidJourney]

Key Takeaways

Move Beyond Baseline Efficiency to Competitive Advantage (CA): While common Generative AI platforms (like ChatGPT) provide a beneficial baseline of efficiency (e.g., writing meta tags), true competitive advantage requires leveraging AI better than rivals, focusing on superior tools and operational strategies.

Use Cases Define the "Best AI Tool": The definition of the "best" AI platform is entirely dependent on the specific use case. Marketers must recognize that Not all AI is created equal; different bots utilize different Large Language Models (LLMs) and thus respond and perform differently across tasks.

Prioritize Niche Solutions Over General Prompting: Strategic time investment should be focused on identifying specific business use cases and researching the optimal niche AI tools to solve them, rather than solely focusing on generic "prompt engineering".

Prepare for Specialized and Multimodal LLMs: The future of AI marketing involves an accelerated growth in smaller, more specialized niche Small Language Models (SLMs) designed for nuanced industry applications (e.g., finance, healthcare), alongside emerging multimodal LLMs that seamlessly synthesize words, images, and numbers.

Frequently Asked Questions About Mastering AI Marketing and Tool Selection

Q1: How can marketers leverage AI to gain a competitive advantage?
A1: While common Generative AI tools offer a baseline of widespread efficiency (e.g., writing first drafts of meta tags or product descriptions), true competitive advantage comes from using AI better than rivals. This requires focusing on the superior tools and establishing the best operational strategies around them. The goal is to unlock business advantage by treating AI not as a novelty, but as a source of market differentiation.

Q2: Why do different Generative AI bots provide different answers to the same prompt?
A2: There is significant variation in performance because not all AI is created equal. Different Generative AI bots utilize different Large Language Models (LLMs), which means they learn differently and, consequently, respond differently. For example, some models may struggle with counting or hallucinate when lacking information, while others, like Perplexity, prioritize quoting verifiable sources. The use case completely changes the perspective on what tool is considered "best".

Q3: What is the biggest challenge for marketers mastering AI today?
A3: The biggest challenge for marketers in mastering AI is choosing the right tools for the right jobs. With tens of thousands of AI companies existing today, the sheer number of potential solutions can cause "analysis paralysis". A better investment of strategic time, rather than focusing solely on "prompt engineering," is identifying the specific business use cases that need to be solved and then researching the optimal tools to achieve those outcomes.

Q4: What are the emerging trends in specialized AI tools for marketing?
A4: Experts predict the accelerated growth of smaller, more specialized Small Language Models (SLMs) designed for nuanced industry applications (e.g., healthcare, finance, cybersecurity). These SLMs are trained on top-notch data, making them better and smarter in specific, niche applications. Furthermore, multimodal LLMs are predicted to be game changers, with the ability to seamlessly blend and make sense of words, images, and numbers.

Q5: What is the long-term future outlook for AI in marketing tasks?
A5: The future involves highly sophisticated systems, specifically Autonomous AI Agents, which will eventually move beyond simply assisting marketers to actually "taking the wheel". These agents, united with multimodal LLMs, will steer tasks to completion with a high level of independence, freeing marketers from remedial tasks to focus on strategic work.