What Growth Marketing Looks Like in an AI-Disrupted World

Growth marketing has always been the most data-driven, experiment-obsessed corner of the marketing organization. More so than almost any other corner of the marketing world, Growth lives and dies by metrics: customer acquisition costs, click-thru-rates, conversion rates, retention rates, customer lifetime value, and so on. It's also been the focus of the vast majority of marketing automation investment over the years. On the surface, all that makes Growth the most obvious candidate for AI disruption and transformation. Feed the AI machine more data, run more experiments faster, automate everything you can, optimize in real-time, watch your numbers soar.

And to a significant degree, that's happening. But the real story of AI's impact on growth marketing is more complex and more consequential than just "better optimization" or "AI-driven automation." It's reshaping the fundamental operating model of growth teams, redefining what "experimentation" even means, and forcing a serious reckoning with what happens when everyone has access to the same AI-powered playbook.

For a comprehensive look at the current state of play, BCG's recent report on how AI will transform marketing and their follow-up on agentic marketing are worth the read.

The Growth Playbook Is Being Rewritten

Before we look at where things are heading, it's worth surveying the landscape of where AI is already deeply embedded in growth marketing workflows: paid media, conversion optimization, personalization, email marketing, audience segmentation, lifecycle and retention marketing, and attribution and analytics. In short, if you run a growth function, AI is almost certainly already a core part of your daily workflow, whether your team consciously (or officially) adopted it or not.

Some examples:

• Paid Acquisition & Performance Marketing: This is where AI's impact has been most dramatic and visible, and the market is flooded with AI wrappers and startups trying to automate or enhance. According to BCG, early adopters of agentic AI in marketing are already tripling ROI on campaign spend while freeing up 15-20% in costs (though I would treat those self-reported numbers by early adaopters with extreme caution). Paid media from Google and Meta have essentially shifted paid media from manual bid management and audience targeting to AI-driven optimization where the algorithm decides who sees what, when, and at what price. The growth marketer's role is rapidly shifting from campaign operator to strategic architect - something that will quickly become a recurring theme across marketing roles I suspect.
• Experimentation & Conversion Rate Optimization (CRO): AI-powered testing platforms are running experiments at a pace and scale that was unthinkable even two years ago. Where a growth team might have managed a handful of A/B tests per month, and often on very expensive platforms, AI can now generate, deploy, and analyze dozens of variations simultaneously across channels, for a fraction of the cost, dynamically adjusting in realtime. Again, the self-reported gains on this front from various sources are impressive so far.
• Personalization at Scale: This may be AI's most transformative contribution to growth marketing, and an opportunity that garners significant attention in CMO circles (partly because it sounds cool to the CEO, to be honest). What used to require complex manual segmentation, static rule-based triggers, and endless content customization is now happening dynamically, with AI LLMs adjusting content, offers, and timing based on individual behavioral signals in realtime.
• Lifecycle & Retention: AI is also proving its value in the often-overlooked back half of the growth equation, which is often a shared accountability between Marketing, Product and Customer Success. Predictive churn models identify at-risk customers before they disengage, AI-driven engagement sequences adapt their approach based on individual responses, and dynamic calculations guide customer marketing investments in ways and at speeds that are upending even previously sophisticated models.

The AI-Intentional Growth Model

Here is where I think the important conversation needs to happen, and where the "AI-first" narrative that dominates growth marketing circles needs some nuance - and caution. As I've written previously, the distinction between AI-enabled, AI-augmented, and AI-first matters. And growth marketing, given its deep roots in data and experimentation, might seem like the natural home for a true AI-first operating model.

But here's a big issue: when everyone has access to the same AI-powered optimization engines, the same bidding platforms, the same predictive analytics, all based on the same best practices ingested by the major LLMs, the competitive advantage shifts away from the tools themselves and toward the strategic and creative thinking that directs them. AI's real opportunity is about wholesale reinvention and not just automation of the current mix of tools and processes, which everyone is trying to do, and risks commoditizing growth strategies for many companies.

That's why I believe the AI-intentional model remains the better framework for growth marketing leaders (all marketing leaders, really). This means deliberately evaluating where AI creates genuine advantage versus where it simply creates parity. It should be deployed to enhance and empower your human talent, not just to attempt to automate them away. The former is the key to winning in an AI-dominated marketing world; the latter leads to a sea of sameness that your prospects and customers will quickly tire of.

In this model, the growth team evolves in important ways. The team likely gets leaner but more senior, with fewer "operators" and more "strategists" who can design AI systems, interpret complex inputs, provide creative feedback, and make judgment calls the LLMs can't. New hybrid roles emerge, particularly around AI agent orchestration, where growth marketers build, train, and oversee autonomous systems rather than manually executing campaigns. Growth teams that figure out how to orchestrate these systems effectively, while knowing when to intervene, and when and how to value the distinctively human contributions, will have a genuine competitive advantage over others who simply automate away creativity in the name of cost efficiencies.

The Uniquely Human Work of the Growth Marketer

If AI handles the optimization, the testing, the personalization, and increasingly the execution itself, what's left for the human growth marketer? Quite a lot, actually, and I would argue the most important parts.

The concern raised by Harvard's analysis of AI's impact on marketing applies acutely to growth teams: if AI absorbs the entry-level execution work, where does the next generation of growth leaders learn the fundamentals? The risk of a "great hollowing out" of the growth marketing pipeline is real and worth serious consideration by every marketing leader.

But the human work that remains is both essential and undervalued in a world obsessed by AI-driven efficiencies:

• Strategic planning and design: The most valuable thing a growth marketer does isn't run the experiment; arguably it's deciding which experiment to run and why. Identifying the right growth levers, understanding the connection points between acquisition, activation, retention, and monetization, framing hypotheses and challenging assumptions. This is fundamentally creative, strategic, and human work that requires judgment that AI doesn't have.
• Cross-functional orchestration: Growth marketing doesn't operate in a vacuum. The most effective growth teams work at the intersection of Product, Dev, Analytics, and Sales (and within Marketing orgs, they similary fuse the inputs of Product Marketing, Brand, Communications, MOPS, and other teams to bring them to bear in the pipeline engine). Building those relationships, translating needs between functions, negotiating priorities, and maintaining alignment across teams with competing goals requires human skills such as persuasion, empathy, and political savvy. These are the same skills central to what I call enabling leadership in the Disruption-Fluent Marketing Framework.
• Brand stewardship and judgement: AI-powered growth tools will optimize relentlessly for the metrics they're given. But not everything that improves short-term conversion rates is necessarily good for the brand, the business, or the customer. Privacy-invading levels of personalization (moving from "oh cool, they know me" to "oh wow, that's creepy and invasive"), for example, could easily get taken too far by an AI that is laser-focused on the optimization tasks in front of it, not fully aware of the wider context and considerations ranging from cultural to political to legal.
• Creative and messaging differentiation: In a world where every competitor can run the same AI playbook, the brands that break through will be the ones with genuinely distinctive creative, positioning, and storytelling. The growth marketer who can combine AI-powered distribution and optimization with genuinely compelling, human-crafted creative will outperform the one who delegates it all to the GPT of the moment.

The Tensions Growth Leaders Have to Navigate

I emphasize "tensions" as a concept for leaders to manage; it's the first dimension of my Disruption-Fluent Marketing Framework for this reason. When growth marketing leaders consider their AI-intentional adoption strategy, several tensions demand careful navigation.

Optimization vs. Differentiation. AI makes everyone better at optimization, which means optimization alone stops being a competitive advantage. When every competitor uses the same GPTs, the same models, the same personalization engines, the competitive edge in performance market evaporates. The brands that win will be the ones who combine AI-powered efficiency with genuinely human-led strategy, creative, and customer experience. When too many brands use the same AI-driven best practices, differentiation disappears into an amorphous blob.

Speed vs. Learning. AI enables faster experimentation cycles, but faster doesn't always mean better. There's a real risk that growth teams start optimizing for velocity of experiments rather than depth of insights. Running 50 simple tests just because you can isn't more valuable than running 10 well-designed ones that generate genuine insight that shapes future thinking. The growth marketing leader's job is to ensure the team is learning, not just churning and iterating.

Efficiency vs. Resilience. AI-driven growth systems, baked into specific LLM models (Claude 4.5 vs ChatGPT 5.2, etc.), represent a point brittleness to be concerned about. When a single LLM manages your primary acquisition channels and that underlying model makes a significant shift, your whole growth engine might stall out. The most experienced growth leaders I know are thinking carefully about hedging their bets, diversification to insulate their engines from any one major platform or model shift, and maintaining strong human talent alongside AI capability.

Short-Term Metrics vs. Long-Term Value. AI optimizes brilliantly for what you tell it to optimize for, e.g. cost per acquisition, conversion rate, click-through rate. But the growth strategies that build durable businesses, such as brand development, fostering communities, investing in customer trust, influence and word-of-mouth, are harder to measure and harder for AI to optimize toward. Same goes for brand stewardship, especially in this politically charged times.

Growth is where the money, and AI, is

Growth marketing is, in many ways, the canary in the coal mine for AI's transformation of the broader marketing organization. Because it's so data-driven and so many of its tools and workflows are ripe for automation, growth is the marketing function where AI adoption has been fastest and the impact most visible. It's why every CMO's inbox is flooded with AI vendors focused on their growth engine. But it's also the function where the limitations and risks of over-indexing on AI are becoming most apparent.

The successful growth marketing leaders will be the ones who embrace AI as an extraordinarily powerful tool for execution and optimization while doubling down on the inherently human capabilities - strategic and creative thinking, brand judgement and context - that no GPT can replicate.

The successful growth marketing leaders will be the ones who embrace AI as an extraordinarily powerful tool for execution and optimization while doubling down on the inherently human capabilities - strategic and creative thinking, brand judgement and context - that no GPT can replicate. In the Disruption-Fluent Marketing framework, this is the essence of managing leadership tension: not choosing between innovation and operational excellence, but navigating between them with intention.