Outdated playbooks lose their edge with every new shift in the marketing landscape. I’ve been a marketer for over two decades, so I’ve watched new playbooks rise and fall against every new innovation being hailed as the next big thing. I remember rolling my eyes every time I heard the phrase “mobile-first” used in the months after Apple released the first iPhone.

But the truth is these inflection points do matter, because they change marketing completely. AI is one of them, and not because the vendors selling it say so. So, I won’t tell you why AI will rewrite the old marketing playbooks — I’ll show you how it’s already happening.

Digital marketers are balancing a juggling act of more channels to optimize, disconnected data sources, shrinking budgets, and an ever changing goalpost. They come to me wondering what it’ll take to come out on top of the growing pressure to deliver. Here’s what I tell them: Being AI-native is critical to thrive now, and will become even more so in the future.

Of course it’s not so simple as just “being AI-native”. Marketers are being bombarded with AI from every direction, and figuring out how to truly extract value from AI is an uphill battle. The promise of AI won’t come without a steep learning curve, but the payoffs of AI era of advertising will be long-lived. From now on, we marketers will be able to put our talents to work where they’ll deliver the greatest impact.

The Digital Marketer’s Dilemma

Since marketing departments started being taken seriously around the 60’s and the era of the hard sell started to die off, the pressure for results has grown. So the emphasis on ROAS and CAC you see marketing leaders talking about today isn’t anything new. But it is a new flavor of the old problem and is unique to this moment in time.

There’s a consistent set of hurdles marketers are running into on a daily basis. And because they’re interconnected and compounding, they create something singular, which I’ll call the “digital marketer’s dilemma”.

• ROAS ceiling: CFOs are demanding to see the dollars earned from their marketing investments, lighting a fire under advertisers to demonstrate ROAS. But we’re already hitting a limit on what performance marketers can do to find efficiencies.
• Channel sprawl: From TikTok to connected TV, audiences are now scattered across so many platforms. It’s a real struggle to break through on each of the myriad individual channels to reach and resonate with target audiences.
• Data overload: Oceans of data from each channel also means finding actionable truth is more difficult, and time spent data-munging leaves less time for uncovering real insights. And when marketers lag behind insights, even the smartest optimization tactics can fail.
• Limited bandwidth to experiment: Despite the expectation for marketers to discover the next new thing that will work, they’re time-poor and pressure on results leaves little time or will to test novel approaches that could unlock growth.

Taken together, these challenges pose a real dilemma for profitability, slow marketers down and obscure growth opportunities. And these challenges aren’t going to go away – in fact, I’d bet they’re only going to intensify. So there’s no option but for marketers to change their approach to solving these issues.

What AI-Native Marketing Looks Like Today

To me, being AI-native just means that AI is a foundational consideration, not a bolt-on. So it’s more of a mindset than a set of qualifications. So there’s a continuum of AI-nativity. It’s not black and white.
I’ve seen firsthand what is possible when marketers fully embrace AI from strategy to execution. The AI-native teams we work with today at Pixis use real-time signals in every stage of execution – from audience targeting to bidding strategies to campaign optimization – to drive more accuracy and consistency in performance. As AI optimizes these aspects of advertising, marketers can do what they do best: lead strategy, power creativity and build connections

One team I worked with had just 10 people managing over $100 million in ad spend, entirely in-house. They used AI to open up incredible opportunities for speed, scale, efficiency and creativity. Watching the transformation unfold in real-time showed me that AI proficient marketers won’t just stay ahead of competition; they’ll define the future of the industry.

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Transforming AI’s Potential to Performance Results

So, how can performance marketers seize these opportunities? To truly unlock AI’s potential, marketers need a clear strategy, rooted in data and insights, that’s designed for action. Thankfully, they can get a head start by allowing AI to be their partner in crafting that very strategy.

1. Unlock valuable data: What was our brand’s best performing campaign this quarter? When you give ChatGPT a spreadsheet of results and ask it this question, it might point you to the one with the lowest average cost per conversion. But if there were only two conversions, that’s not helpful. The human prompter would need to direct the LLM to consider significance, make sure  the LLM has all the data it really needs to do so… and still double-check the results.

LLMs like ChatGPT impressed us all when they launched. But I don’t think I’m alone when I say I’ve also been a little disappointed to realize just how much prompting, direction, structured data, and context I need to provide to get a quality response.

But not every AI is like ChatGPT (or Claude, or Gemini).

AI platforms purpose-built for marketing should integrate with your organization’s data directly from multiple sources (i.e. ad platforms, attribution systems, website analytics). With a unified view, you’ll come away with a more informed decision that you can use to improve future campaign outcomes.This isn’t a vague vision of the future that requires the invention of a new technology. Nor is it an advanced use-case for organizations that can invest millions in custom AI implementations. This is happening today.

2. Discover insights: Most marketers are sitting on a goldmine of data – they just don’t have the time or resources to manually analyze it. Some AI advertising models (think Google’s Performance Max or Facebook’s Advantage+) skip the need for analysis all together, just taking actions to improve outcomes. It goes without saying that while we appreciate those outcomes, these black boxes also mean we get little to no insight from their results.

Take immi, a health food Ramen brand, which used AI to identify microsegmentations and new audiences it couldn’t have even thought to test on its own. AI didn’t just identify target audiences, but it uncovered key lifestyle needs and preferences of customers. The result? New personas emerged, CAC dropped, and they were able to increase their ad budgets and add new channels faster.

Even if the team at immi had thought to test these new audiences, uncovering the insights manually would’ve taken weeks. Their AI platform did it in hours, driving smarter, more strategic decisions.
The idea that AI can see around corners isn’t sci-fi. But you do need to make sure your AI platforms have the right context and data to do their work well.

3. Take action: Insights are only as good as what you do with them.

Most advanced performance marketers (or at least, those with enough tech budget and implementation bandwidth) use an automated bid management solution to reallocate ad spend to better channels, campaigns, ad sets or creatives daily.

Usually the rules that govern those moves are input ahead of time by the user. The reliance on user pre-emptive user input becomes a major limiting factor when an AI platform is suddenly delivering new, actionable insights in real time.

So the obvious next step is to allow your AI to make those moves on your behalf. And while Performance Max and Advantage+ may make the reasoning – or even the moves themselves – a mystery, I’m seeing marketers use solutions that give them the best of both worlds:

AI that can act on their behalf in real time, depending on their direction, but without requiring them to think of and input rules for every eventuality ahead of time.

Smarter, Future-Proof Marketing Starts With AI

In the early days of my career, when performance marketers hit a wall – stagnant growth, inefficient campaigns, unclear results – the default fix was to fill the gap with a new hire or agency partner. More people meant more hands to analyze, test, and optimize. This headcount-led growth model isn’t as viable in today’s current climate of tighter budgets and leaner teams.

For a while, demands to “do more with less” were met with the implementation of new automation-based systems: tools that take codified rules and processes and do more of those things faster. But with adoption of such tools at a high, the competitive edge is gone there, too.

AI is proving to be transformational in ways that automation falls short. If automation is about doing more with less, AI is about getting rid of the quality/quantity dichotomy completely. It’s not an exaggeration to say it’s a paradigm shift, just like the internet and mobile-first were.
I’m seeing AI empower marketers to work smarter and make real progress toward outcomes – analyzing context, delivering insights, offering recommendations, and executing on them. Marketers that embrace AI as part of their everyday approach are already outperforming, and they’re set up to continue to outstrip competitors with future-proof strategies.

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