Marketing teams are tired. Not because they’re lazy, but because they’re trying to do more work than humans were built to do. Every new AI tool promises salvation: faster content, better targeting, smarter insights. The reality is that automation creates as many problems as it solves when applied with the grace of a walrus. 

Stay with me. 

Tools scale infinitely. Human attention doesn’t. 

New tools won’t solve your problems if they’re applied with meat-hands. They need to be surgically inserted and integrated with bespoke training and application, or else they lead to more headaches and frustration within your teams. 

The prevailing narrative suggests that we can automate our way out of capacity issues. That if we just connect more systems, buy the right AI assistant, or rebuild workflows around automation, we’ll finally “do more with less.” But most teams are already at the breaking point. The problem isn’t output. It’s energy, focus, and clarity.

At Catalyst, we’ve seen this firsthand. Teams layer automation on top of disorganization and call it innovation. They build complex systems that no one fully understands. They chase faster campaign cycles without slowing down to ask if the work is actually effective or sustainable.

Automation doesn’t cure burnout. It often amplifies it.

When every part of your process is designed for speed, you lose the human context that gives marketing meaning. Creative teams stop thinking about storytelling and start thinking about throughput. Strategists stop testing ideas and start feeding dashboards. Before long, everyone is just feeding the machine.

What Automation Should Actually Do

There’s a better way to think about automation. It isn’t about doing more. It’s about doing less, but smarter.

Automation should remove friction, not humanity. It should make space for deep work, not fill every spare minute with another task queue. The point of AI isn’t to replace people. It’s to give them their time and attention back.

So instead of asking, “How can we automate more?” teams should ask, “What’s worth automating, what deserves our attention, and (most importantly) how can we layer automation in efficiently?”

Here’s what that looks like in practice.

First, automate the predictable. Repetitive tasks, handoffs, data pulls, and quality checks are great candidates for automation. Anything that drains time but doesn’t require judgment should be handed to the machines. That’s the baseline efficiency everyone should expect in 2025.

Second, protect the human layer. The parts of marketing that require intuition, empathy, and creativity should stay human-led, even if they’re AI-assisted. Storytelling, positioning, and brand strategy don’t benefit from being rushed. The more those processes are mechanized, the less distinct your brand becomes.

Third, reset expectations and integrate with care. Leaders need to stop selling their teams the idea that automation equals capacity. It doesn’t. It’s leverage, not magic. If you use that leverage to pile on more work, you’ll get temporary gains and long-term burnout. If you use it to focus on higher-quality output and strategic thinking with conscientious integration, you’ll build resilience.

The Culture Problem, Not the Tool Problem

“Do more with less” has become a mantra for modern marketing, but it’s a dangerous one. It assumes that efficiency and effectiveness are the same thing. They’re not. Efficiency helps you move faster. Effectiveness makes sure you’re headed in the right direction. One without the other is chaos.

Automation is a tool. Burnout is a culture problem. You can’t fix the second with more of the first.

If you want a future-proof marketing team, start by rethinking what “productive” actually means. The best teams in 2026 won’t be the ones who automate everything. They’ll be the ones who automate wisely and know when to slow down.

What zero-click search means for your PPC and SEO, and how to pivot as user behavior changes

Let’s tell it like it is: The old journey to conversion in Google Ads is now broken. More impressions no longer guarantee more clicks, and more clicks no longer show up on your site the way they used to. When an AI summary appears on the results page, the share of users who click a traditional result drops from roughly 15% to about 8%. Treat this as baseline reality, not a seasonal dip. [1]

This isn’t a fluctuation. Across U.S. Google searches, only about 36% of users click on the open web. The addressable traffic that can reach your site is smaller before you set a budget. Be prepared to plan the next two quarters for fewer total clicks and a higher bar for each page view you earn. [2]

The shrinking click pool and what it does to cost

The Search path used to look linear: Awareness, research, click, evaluate, convert. AI Overviews completely crush that path. Today, with the help of AI, the results page does the research and presents a short list of likely answers. By the time a user reaches a paid or organic link, they are validating a decision, not fishing for basics. Semrush shows these summaries rising on both commercial and navigational searches, not just informational ones. And that’s where money changes hands. [3]

Here’s the Ad Auction reality—Google’s pricing system rewards three things: the likelihood an ad will get clicked, the relevance of the message to the query, and the quality of the landing page experience. When the total click pool shrinks, the expected click-through rate falls across the board. A lower expected CTR weakens the Quality Score, which often pushes CPC higher even when your ad position holds. That’s a structural change, not a sign that your team forgot how to run Google Ads. [4]

Not all clicks are equal anymore

Protecting click volume used to be rational, but that reflex burns budget in this AI-powered zero-click environment. BrightEdge reports total impressions are up around 49% in AI Overview environments, while CTRs fell more than 30%, meaning people see more information and click less. The clicks that do break through come from users who believe the destination will finalize a choice. Fewer clicks. Higher intent. Fight for those, not for noise. [5]

Your job isn’t to chase every impression; now it’s your job to ensure your business or clients look like the obvious next step after the AI-Overview summary.

What to prioritize now

Paid and organic search no longer operate in silos. In Google Ads, authority signals help your brand earn a mention in the summary. Relevance signals help your ads show next to it. Google confirms that Search, Shopping, and Performance Max ads can appear adjacent to AI Overviews when the copy and landing page tightly match intent and content. Build for that reality. [6] [7]

Decision-stage clarity. Do the following, consistently:

• Build pages and ads around the tasks people still click for. Give clear comparisons, pricing that maps to company size and use case, integration guidance that shows real systems, security reassurance at the top of the fold, and a clear action path to a trial or demo.
• Remove detours. If the ad promises a solution to a specific problem, the landing experience should prove it above the fold. This protects ad quality and reduces the need to buy efficiency with bigger bids.
• Shift how you price outcomes. A qualified meeting or a trial is more valuable than a generic form-fill. Treat it that way. Google’s guidance on value-based bidding allows weighting so automation leans into the moments that move pipeline, not the ones that pad lead counts. [8]

Measurement that leadership will trust

Clicks are no longer the primary signal. Prove value, not volume. Keep the metrics few and board-ready.

Directional signals to steer weekly, not judge quarterly:

• CPC is at a steady position with core relevance indicators. If clarity improves, price pressure should ease. [4]
• Give an absolute top impression rate and click share on priority terms. Shows whether you appear above the fold when it matters and whether you win those moments.

A quick B2B software example

If your primary CTA is trial or demo, elevate the queries and pages where buyers compare options, check price tiers, and review integration paths. Those are the tasks that still require a visit. The ad should promise the trial or demo directly. The page should deliver it without detours or fluff. Report the shift in pipeline per 1,000 impressions and cost per qualified opportunity after moving budget from early curiosity to late-stage validation. This lines up with how summaries change behavior and where they tend to appear. [1] [3]

What changed on the Search Engine Page Results

The results page now answers more questions and highlights a short list of likely solutions. That pushes traditional links and ads lower on the screen. CTR falls even when you hold in position. In some cases, ads can show next to or within the summary if they win placement and match the user’s task. Google has expanded this inventory beyond the initial U.S. rollout, so treat it as part of your working surface area, not a novelty. Your copy and page should mirror how the summary frames the problem and the options, so your ad is the obvious next step. [6] [7]

The path forward

The path forward isn’t hard, it’s just different. Paid search isn’t about buying a seat at the top anymore; it’s about earning the next step after a machine-generated summary. SEO isn’t just about climbing ranks; it’s about building enough authority to be cited in the summary that shapes perception before your ad even loads.

This environment rewards teams that retire vanity volume and optimize for decisiveness. It punishes generic pages, shallow content, and ad copy that doesn’t align with the decision a buyer is trying to make. It rewards aligned channels, specific promises, and pages that deliver those promises fast.

So, there will be fewer clicks. But the clicks that remain are worth more. Recalibrate for that reality, and your reports will shift from explaining lost volume to proving stronger efficiency per impression. The drought isn’t a decline; it is a correction back to relevance, clarity, and intent.

Marketing teams have always been data hungry. But now they’re feeding that data directly into AI systems that remember everything, learn from everything, and sometimes share everything with the wrong people. That’s not a marketing problem or an IT problem. That’s a business risk that lands squarely on executive desks.

The math is brutal. Your marketing team uploads customer data to train a lead scoring model. That same data gets absorbed into the vendor’s foundational training set. Six months later, a competitor’s chatbot starts referencing insights that sound suspiciously like your customer research. You can’t prove it, but you can’t un-ring that bell, either.

This isn’t hypothetical doom-and-gloom thinking. It’s the new reality of marketing in an AI-first world. The tools that promise to revolutionize your customer acquisition are the same tools that can accidentally revolutionize your competitors’ understanding of your market.

What is marketing data privacy in the age of AI?

Marketing data privacy in AI refers to protecting customer and business intelligence from unintended exposure when using AI-powered marketing tools. Unlike traditional data privacy, AI privacy accounts for how machine learning models learn from, store, and potentially reproduce patterns from your data across different customer environments.

Key difference: Traditional tools process your data and forget it. AI tools process your data and learn from it permanently.

The risk compounds because AI marketing tools often share learned insights across their customer base, meaning your competitive intelligence can inadvertently inform recommendations for your rivals.

Why doesn’t traditional data governance work for AI marketing tools?

Traditional data governance fails with AI marketing tools because it assumes you can control what happens to your data after sharing it. AI systems are designed to find hidden connections, learn unexpected patterns, and make predictions based on information you didn’t realize was sensitive.

The fundamental problem: Traditional governance treats data as files you can lock, copy, or delete. AI governance must treat data as knowledge that becomes part of a learning system.

Most companies apply file-based security thinking to AI tools. They encrypt data in transit, restrict access permissions, and audit data flows. But once AI models learn from your data, those protections become largely irrelevant. The model has already extracted and internalized the valuable patterns.

Summary: AI tools don’t just use your data—they learn from it permanently, making traditional data controls inadequate.

What competitive intelligence do marketing AI tools actually capture?

Marketing AI tools capture four types of competitively valuable intelligence that most executives don’t realize they’re sharing:

Customer acquisition intelligence reveals exactly which segments convert, at what price points, and through which channels. This data shows competitors your successful acquisition playbook and vulnerable customer segments.

Messaging effectiveness data exposes which value propositions resonate with different buyer personas, essentially handing over your positioning strategy and communication framework.

Pipeline intelligence includes sales cycle length, deal sizes, and conversion bottlenecks, allowing competitors to time campaigns that intercept your prospects at decision points.

Behavioral analytics show how customers use your product, where they struggle, and why they churn—product strategy intelligence disguised as marketing data.

Bottom line: Your marketing data contains your entire go-to-market strategy in quantified form.

How do AI marketing tools actually use your data for training?

Most AI marketing tools use customer data in three ways that create privacy risks:

Direct model training: Your data becomes part of the vendor’s training corpus, teaching their AI system patterns that can be applied to other customers’ scenarios.

Insight derivation: Even if raw data stays private, AI models learn general patterns from your specific data that inform recommendations for other customers.

Cross-customer optimization: Vendors use learnings from your data to improve their overall platform performance, inadvertently sharing your competitive insights.

Geographic considerations: Data processed in different jurisdictions creates compliance cascades. European customer data processed through US-based AI infrastructure triggers privacy regulations that traditional marketing tools never encountered.

Summary: AI vendors aren’t necessarily stealing your data, but they are learning from it in ways that can benefit your competitors.

Where does your marketing data actually get processed and stored?

Marketing data in AI systems gets processed across multiple geographic locations and technical environments:

Processing locations: Data may be processed in regions with different privacy laws than your customer locations, creating compliance gaps.

Model hosting: AI models trained on your data often run on shared infrastructure where derived insights can cross-pollinate between customers.

Backup and archival systems: Learned patterns from your data persist in model weights and backup systems long after raw data deletion.

Edge computing: Some AI marketing tools process data on distributed edge networks, where geographic boundaries become unclear.

The hidden risk: Your data residency commitments with customers may not account for where AI learning happens versus where data storage occurs.

What should marketing executives audit in their AI tool stack?

Marketing executives should conduct a comprehensive AI privacy audit covering these areas:

Tool inventory questions:

• Which marketing tools use AI to analyze customer data?
• Where is data processed geographically?
• What happens to data during model training?
• Who has access to insights derived from your data?
• How long is data retained and in what form?

Data classification framework:

• Tier 1 (AI-Prohibited): Customer lists, pricing data, strategic plans, competitive intelligence
• Tier 2 (AI-Restricted): Behavioral data, messaging performance, campaign effectiveness
• Tier 3 (AI-Permissible): Anonymized usage patterns, market research, publicly available data

Contract evaluation: Review vendor agreements for AI-specific privacy protections, not just traditional data sharing terms.

Summary: Audit should focus on data learning and insight sharing, not just data access and storage.

How should companies renegotiate AI marketing vendor contracts?

Companies should demand four key contractual protections for AI marketing tools:

Data learning restrictions: Explicit prohibition on using customer data for vendor foundational model training or cross-customer insight sharing.

Geographic processing limits: Mandatory data processing within specified jurisdictions that align with customer privacy commitments.

Audit rights: Regular reviews of how customer data influences recommendations and insights for other vendor clients.

AI-specific deletion procedures: Data deletion that includes learned patterns and model weights, not just stored files and databases.

Additional considerations: Traditional vendor agreements focus on data sharing, not machine learning implications. AI contracts must address how models learn, retain, and apply insights derived from customer data.

Summary: Renegotiate for AI learning control, not just data access control.

What immediate actions should executives take for marketing AI privacy?

Executives should implement a 30–90 day action plan addressing AI privacy risks:

Immediate actions (30 days):

1. Inventory all AI-enabled marketing tools currently in use
2. Identify tools with access to competitively sensitive customer data
3. Review vendor agreements for AI-specific privacy protections
4. Establish data classification guidelines for AI tool usage

Strategic actions (90 days):

1. Develop AI vendor evaluation criteria prioritizing data privacy
2. Create cross-functional AI governance team (marketing, IT, legal, executive)
3. Implement regular AI tool audits and data sharing assessments
4. Establish incident response for suspected AI-related data leakage

Ongoing requirements: Monitor industry AI breach reports, stay current on AI privacy regulations, reassess marketing data sensitivity, maintain updated vendor agreements.

Summary: Treat AI marketing privacy as ongoing business risk management, not one-time compliance project.

Frequently Asked Questions

Q: Can AI marketing tools really expose our competitive data to rivals? 

A: Yes. AI models learn patterns from your data that can inform insights and recommendations for other customers, including competitors. This happens through model training, cross-customer optimization, and derived insight sharing.

Q: How is AI data privacy different from traditional marketing data privacy? 

A: Traditional privacy controls what happens to your data files. AI privacy must control what AI models learn from your data, which becomes permanent knowledge that can’t be “deleted” in the traditional sense.

Q: What’s the biggest risk executives overlook with marketing AI tools? 

A: Most executives assume marketing data is less sensitive than financial or operational data. In reality, marketing data reveals your entire go-to-market strategy, customer acquisition playbook, and competitive positioning.

Q: Do we need to avoid AI marketing tools entirely? 

A: No. The goal is to use AI marketing tools strategically while protecting competitively sensitive data through proper classification, vendor selection, and contractual protections.

Q: How can we tell if our marketing data has already been exposed through AI tools? 

A: Direct detection is difficult. Look for competitors suddenly improving in areas where you previously had advantages, or vendors whose AI recommendations seem unusually informed about your market segment.

The marketing data trust equation isn’t complicated. The data you share with AI tools today influences the competitive landscape tomorrow. Companies that solve for trust alongside performance will have sustainable advantages. Companies that don’t will find their advantages mysteriously eroding, one AI model at a time.

Key Takeaway: Marketing AI privacy requires treating data as knowledge that becomes permanently embedded in learning systems, not files that can be secured through traditional access controls.

Last month, at the Colorado Technology Association’s Women in Tech conference, tech leaders from across Colorado gathered to talk about the future of innovation, AI, and leadership. As a women-owned growth marketing agency, we showed up because these conversations matter—and because the speakers weren’t just talking about change, they were actively building it.

Here’s what landed, what it means, and what we’re doing about it.

Think in Generations, Not Quarters

CSU President, Amy Parsons, opened with a gut-check: are you making decisions for the next 150 years, or just the next board meeting?

Her approach to integrating AI across campus operations while maintaining human connection hit home. Here’s the thing: we constantly see this tension in growth marketing. Everyone wants to scale fast, automate everything, and optimize their way to hockey-stick growth. But if your AI strategy is helping you avoid talking to customers instead of understanding them better, you’re building on quicksand.

The takeaway: Technology should enhance relationships, not replace them. At Catalyst, we treat AI like a team member that makes us faster and wiser—not one that thinks for us. Vision and execution aren’t mutually exclusive. They’re non-negotiable.

Your Assumptions About Your Audience Are Probably Wrong

Rob Cohen’s work launching Denver’s new NWSL team was a masterclass in letting data and humanity drive strategy. Family-friendly stadiums designed from actual feedback. Training programs that account for women’s physiological cycles, because (wild concept) female athletes have different needs than male athletes.

This mirrors exactly what we preach about AI-enhanced marketing: powerful analytics mean nothing without a genuine understanding of what your audience actually needs.

The takeaway: Stop building for imaginary personas. Start listening to real humans. Your CRM has the data. Your sales team has the stories. Put them together and you’ll stop wasting budget on campaigns that miss the mark.

Technology Is Breaking Free From Screens

Cathy Hackl, tech futurist and co-author of the newly released Spatial Computing: An AI-Driven Business Revolution, reminded us that we’re standing at the intersection of AI and spatial computing—a shift that’s poised to be bigger than mobile or personal computing.

Her insights on how spatial computing will transform human-computer interaction hit differently when you consider what it means for customer experience. We’re not just talking about AR filters or VR headsets. We’re talking about blending virtual experiences into the physical world in ways that fundamentally change how people discover, evaluate, and buy.

The takeaway: The brands that win in the next decade won’t just have great websites—they’ll create experiences that break free from screens entirely. For growth marketers, this means rethinking not just what we say, but where and how customers experience our messages.

Success Requires Ecosystem Thinking

Bijal Shah from Guild reminded us that solving significant challenges (economic inequality, workforce transformation, innovation at scale) requires ecosystem thinking, not hero-ball.

Her “kind but high-performance” leadership philosophy and emphasis on understanding AI’s limitations alongside its capabilities gave us a roadmap for responsible innovation that actually serves people (instead of just looking good in a case study).

The takeaway: The barriers you tear down and the people you bring along matter just as much as the metrics you hit. Colorado’s tech community gets this right when we’re not too busy trying to outdo Silicon Valley. Collaboration beats competition every time.

Every Campaign Is a Choice About What Stories Get Told

Melissa Akie Wiley‘s closing keynote landed hard: technology’s real power isn’t in its invention, but in how we choose to use it. Her challenge to “make goodness attractive” and replace harmful stereotypes with authentic stories applies to every marketer in the room.

As Mr. Rogers proved with television decades ago, the question isn’t what technology can do—it’s what we will do with it.

The takeaway: Every piece of content you create, every campaign you launch, every platform you choose is a decision about which voices get amplified. In a world drowning in content, thoughtful beats loud every time.

Why This Matters to Us

These conversations reinforced why Catalyst is passionate about serving Colorado’s tech community. We’re not just here to drive MQLs and optimize CAC (though we’re pretty damn good at that). We’re here to help build a future where diverse voices lead, where technology serves people, and where “growth marketing” means something more than just bigger numbers.

Thanks to CTA for creating space where leaders can learn, connect, and commit to doing better. Not hypothetically. Actually.

Want to talk about what human-centered growth marketing looks like for your team? Let’s connect.

Why Mindset Matters More Than Ever

Too often in marketing, it’s easy to think: “If only I had better tools, a bigger budget, or more talent, then I could really deliver.” But the truth is, constraints—especially time constraints—can be a gift. They force sharper thinking, quicker iteration, and more creative problem-solving.

That’s where the Growth Marketing Mindset comes in. It’s not about chasing perfection or waiting until you have every resource in place. It’s about adapting to the “do more with less” culture we live in, and learning how to use speed, iteration, and data as leverage.

Importantly, this doesn’t mean the death of grand, well-executed, pixel-perfect campaigns. Far from it. Growth marketing is about choosing your battles. There are moments when you need to hit the ground running—shipping quickly, learning from the market, and building momentum. And there are moments when you swing big with high-concept creative that requires more investment and polish.

The difference is that with a growth mindset, you don’t hit pause on everything while the marketing team disappears to “perfect” something. Those pauses need to be shorter. Quick wins and iterative experiments buy you both the time and the data to make the big swings land with greater impact.

That’s why the Growth Marketing Mindset matters. It’s not just another framework or buzzword. It’s a way of thinking that helps organizations reduce stagnation, break down silos, and create new pathways for growth. At Catalyst, it’s the operating system we use every day—but more importantly, it’s an approach any marketing leader, team, or business can adopt to transform their outcomes.

What the Growth Marketing Mindset Really Means

At its core, the Growth Marketing Mindset is about approaching every challenge with curiosity, adaptability, and a relentless focus on outcomes. It’s built on six attributes that shape how we think, plan, and act:

• Customer-Centric: Growth begins with solving real customer problems, not pushing features. Every tactic starts with the question: what’s in it for them?
• Full-Funnel Thinking: Marketing doesn’t stop at the click. Growth means looking at the entire journey—from awareness to retention—and optimizing every touchpoint along the way.
• Collaborative: Growth doesn’t belong to a single department. It happens when marketing, sales, product, and even HR work together toward shared goals.
• Strategically Creative: Bold creative ideas matter, but only when they’re anchored in data and designed to drive measurable business outcomes.
• Adaptable: “Launch fast, learn faster.” It’s about putting out the Minimally Lovable Product (MLP), gathering real feedback, and iterating quickly. Wins and losses both feed the growth engine.
• Tech-Forward: Modern growth marketing doesn’t shy away from technology. We lean into AI, automation, and emerging tools to analyze, optimize, and scale smarter.

These six attributes form the foundation of how growth marketers think. They’re not boxes to check once—they’re muscles to build and flex every day.

How You Can Apply the Growth Marketing Mindset in Your Organization

This isn’t just about how Catalyst works. It’s about how you can unlock growth inside your own organization. Here are practical ways to bring each attribute to life:

1. Get Customer-Centric

• Shift from features to outcomes. Instead of asking, “What can we sell them?” ask, “What pain point are we solving?”
• Adopt a simple habit: After every initiative, ask your team: “What new customer insight did we gain, and how will it shape our next step?”
• Try this tomorrow: Replace one product-focused message with a customer-focused one—language that mirrors their needs, not your features.

2. Think Full-Funnel

• Go beyond lead gen. Growth doesn’t end at the MQL. Look at how your marketing affects sales conversations, onboarding, retention, and even referrals.
• Adopt a simple habit: Even if you only own one part of the funnel, always ask what comes before and after. Those questions expand your influence.
• Try this tomorrow: Map one customer journey from awareness to referral. Circle one stage you’re currently ignoring—and brainstorm a way to impact it.

3. Be Collaborative

• Break silos intentionally. Invite colleagues outside marketing into the conversation. Sales, product, HR—all have data and perspectives that influence growth.
• Adopt a simple habit: In your next cross-functional meeting, ask: “What’s our shared goal, and how do our departments connect to achieve it?”
• Try this tomorrow: Schedule a 30-minute sync with a peer in another department. Ask them what obstacles they see that could be solved through better messaging or engagement.

4. Stay Strategically Creative

• Balance boldness with measurability. Creative that looks great but doesn’t move the needle isn’t growth marketing. Likewise, strategy without strong execution won’t inspire.
• Adopt a simple habit: For every new campaign, define both the bold creative hook and the KPI it’s tied to. Don’t launch without both.
• Try this tomorrow: Run a mini “creative experiment.” Launch two variations of the same message—one conservative, one bold—and see which drives more engagement.

5. Be Adaptable

• Embrace iteration. The Growth Marketing Mindset thrives on feedback loops. Wins and losses are both valuable.
• Adopt a simple habit: Replace “Did it work?” with “What did we learn?” That one language shift reduces fear of failure and increases speed.
• Try this tomorrow: Take one project you’re sitting on and launch a “good enough” version. Collect feedback. Iterate. Repeat.

6. Go Tech-Forward

• Leverage AI and automation. Tools are accelerators—but only when guided by strategy. Use them to multiply human insight, not replace it.
• Adopt a simple habit: Dedicate one hour a month to trying a new tool. Share your findings with your team.
• Try this tomorrow: Pick one repetitive task you do weekly and explore whether automation could handle it. Free your brain for strategy.

How Catalyst Lives This Mindset

At Catalyst, we’ve built our culture around these practices. Not because it’s trendy, but because it works. Here’s how we reinforce the mindset:

• Everyday Habits
  • After-action reviews: “What did we learn, and how will it make the next one stronger?”
  • Asking beyond our assignment: “Where does this fit in the client’s full funnel?”
  • Sharing AI discoveries in Slack so the whole team benefits.

• Ways of Working
  • Launching Minimally Lovable Products (MLPs) to learn fast.
  • Collaborating across strategy and creative as true partners.
  • Treating both wins and losses as data, not verdicts.

• Cultural Anchors
  • Phrases like “launch fast, learn faster” aren’t slogans—they’re marching orders.
  • Curiosity is celebrated as much as performance. Every experiment has value.

For us, the Growth Marketing Mindset is more than a philosophy—it’s our operating system. And it’s one that any organization can adopt.

Why It Matters for Clients—and for You

For clients, this mindset shows up in the outcomes they experience:

• Faster Learning Loops: Weeks instead of months.
• Sharper Insights: Every experiment builds knowledge.
• Better ROI: Less wasted spend, more proven levers.
• Stronger Alignment: Marketing + sales + product rowing together.
• Future-Proofing: Tech-forward adaptability ensures relevance.

For your own organization, the benefits are similar. Here’s why adopting the Growth Marketing Mindset matters:

• It helps you reduce stagnation by replacing endless planning cycles with real-world experiments.
• It helps you create organizational connections by making growth a shared responsibility across departments.
• It gives you a framework for innovation—a way to test new ideas without betting the farm.
• And critically, it gives you runway to do the big swings—because quick, iterative work buys time and data to make those large, polished efforts more successful.

Looking Ahead: Winners vs. Laggards

The future of marketing will be defined by mindset. Agencies and companies that cling to traditional, campaign-driven thinking will struggle. The ones who thrive will be those who embrace curiosity, collaboration, adaptability, and technology as everyday operating principles.

AI is already accelerating this shift. Where once you could get by with slow planning cycles, today’s tools demand a faster, more experimental approach. The teams that learn to pair human insight with machine intelligence—that see AI as a multiplier, not a shortcut—will pull ahead.

The Growth Marketing Mindset isn’t just Catalyst’s way of working. It’s an approach any organization can use to outpace competitors, foster innovation, and create lasting growth.

Closing Reflection

Growth isn’t just about what you do. It’s about how you think.

That’s the essence of the Growth Marketing Mindset. It’s not about chasing every new tool or gimmick. It’s about building a way of working—curious, adaptable, collaborative, and tech-forward—that consistently delivers smarter results.

Whether you’re leading a marketing team, sitting in a product role, or running a business, this mindset is available to you. Start small. Build the habits. Ask better questions. And you’ll find that the compounding effect of these shifts can transform your outcomes.

For Catalyst, this is the philosophy that drives how we show up every day. But for you, it can be the spark that moves your organization from stagnation to momentum, from silos to collaboration, from incremental wins to exponential growth.

When Campaigns Shrunk to Single Assets

For decades, growth marketers have known the truth: the best campaigns don’t live in one channel. They stretch across platforms, adapt to context, and meet customers wherever they are.

But over the years, shrinking budgets and leaner teams forced tradeoffs. Entire campaigns were whittled down to a handful of assets—a single hero video instead of a series, one key visual instead of a library, and a few resized cutdowns repurposed across channels. Personalization was more talking point than practice. Multi-channel ambitions shrank into a question of survival: What’s the minimum we can deliver and still launch?

Generative AI is changing that equation. Suddenly, the budgetary and time constraints that throttled multi-channel marketing are disappearing. The need for channel-specific creative, personalization, and rapid iteration is back—and this time, it’s achievable at scale.

Speed + Scale: The Multi-Channel Mandate

Here’s the reality: Your customers aren’t sitting in one place. They’re scrolling Instagram while waiting for coffee. They’re watching YouTube on their commute. They’re skimming LinkedIn between meetings, swiping TikTok at night, and deleting emails in the morning. To stay relevant, your creative has to move with them.

The problem? Making multi-channel assets used to be slow and resource-heavy. That’s where AI shifts the game.

Instead of one hero video cut down, one static image resized, or one social copy line tweaked, AI can generate multi-channel variations in minutes. The hero video becomes dozens of platform-optimized edits. The key image spawns a carousel, a story sequence, and a batch of ad creative. The campaign headline transforms into dozens of copy variants for social, email, and display.

For growth marketers, that means more shots on goal. More creative in more places—without ballooning costs or timelines.

Personalization + Iteration: AI’s Secret Weapon

Speed and scale are table stakes. What really moves the needle is personalization.

Personalization used to mean swapping out a first name in an email. Today, audiences expect more: content that feels specific to their industry, role, or even stage in the buying journey. But producing that many versions was impractical—until now.

AI enables true creative branching:

• One campaign becomes dozens of micro-campaigns, tailored by persona, vertical, or geography.
  
• Email subject lines are generated and tested for each audience segment.
  
• Social ads get rewritten for awareness, consideration, or conversion stages.
  

And because AI accelerates iteration, you don’t just ship one version—you test five, ten, or fifty, and let the data surface what works.

That shift changes how growth marketing operates. It’s not about one big bet. It’s about continuous learning loops: create, test, refine, repeat. AI makes the cycle fast enough (and cheap enough) to actually do it.

What’s Working Today: AI Across Channels

We’ve seen AI’s impact in video already, but the real power is in how it enables cohesive, multi-channel execution. Here’s where it’s showing up now:

• Email + CRM: Generating personalized subject lines, content blocks, and CTAs that adapt to customer behavior, enabling high-volume, tailored campaigns at scale.
  
• Social Media: Generating platform-native content (short-form clips, image carousels, trending-style captions) that would have been impossible to produce before.
  
• Web + Landing Pages: AI-driven copy testing, layouts, and imagery allow for real-time personalization per visitor segment.
  
• Advertising: Campaigns can spin up hundreds of creative variations—headlines, visuals, calls to action—optimized in real time for performance.
  
• Content Marketing: Blog outlines, visuals, and social snippets can be spun out in parallel, ensuring your thought leadership extends across multiple touchpoints.
  
• Localization: Generative AI tools like ElevenLabs make it possible to quickly create regionally relevant versions of assets—voiceovers, captions, even entire campaign variants—in multiple languages, so global campaigns resonate locally.
  
• Custom Music: Tools like Suno can generate original, fully customized music tracks for videos, giving campaigns a unique sonic identity that stands out across channels.
  

The magic here isn’t just “AI can make things faster.” It’s that AI makes the multi-channel vision affordable again—something teams don’t have to compromise away when budgets tighten.

Beyond Efficiency: New Creative Possibilities

Efficiency is great. But the real story is possibility.

With AI, creative teams can explore campaign directions they would’ve killed in the first round because of cost, deadlines, and bandwidth. Imagine testing three entirely different campaign directions in parallel—one bold, one conservative, one experimental. AI lets you prototype each, bring them into market, and double down on the one audiences respond to.

This is what democratization looks like:

• Small brands can compete like global players, showing up across multiple platforms with content that feels polished and personalized.
  
• Big brands can act like startups, experimenting quickly without waiting months for production.

The creative constraint has shifted. It’s no longer “what can we afford to make?” It’s “what do we want to learn, and how fast can we test it?”

Where Humans Still Rule

Of course, multi-channel marketing isn’t just about flooding feeds with variations. Without strategy, taste, and cultural awareness, AI can churn out content that feels repetitive or off-base.

Humans still set the course by:

• Deciding which audiences to prioritize.
  
• Shaping the core narrative and brand voice.
  
• Curating AI creative outputs into a campaign that feels coherent, not chaotic.
  
• Guarding against “AI Sameness.” One danger in multi-channel AI output is blandness: the too-slick stock photo vibe, the copy that says a lot without saying anything, the generic social ad. If brands blindly pump AI outputs into market, everything starts to look and sound the same. That’s why iteration and curation matter so much. AI is the accelerator, but humans provide the steering—choosing the creative that disrupts the feed instead of blending into it.

AI can give you multiple options. A human knows which ones actually resonate.

The Catalyst POV

At Catalyst, we see AI not only as a tool, but as part of a system:

• AI accelerates: asset generation, multi-channel versions, and personalization at scale.
  
• Humans elevate: strategy, storytelling, visual direction, and channel cohesion.
  
• Data validates: we test, refine, and invest in what performs.

That loop—accelerate, elevate, validate—is how we help clients thrive in a multi-channel world without sacrificing brand integrity.

And because we’ve built infrastructure like our AI Innovation Lab, we don’t just “experiment with tools.” We turn AI into a repeatable, scalable advantage for growth marketing.

The Bottom Line

Multi-channel marketing isn’t optional anymore—it’s survival.

Generative AI makes it possible to:

• Create channel-specific variations in minutes, not weeks.
  
• Personalize campaigns deeply across segments and buyer journeys.
  
• Iterate rapidly, letting data guide creative refinement.
  
• Unlock campaign possibilities that would’ve been killed by budget constraints in the past.
  

The brands that thrive won’t be the ones resisting AI, or the ones using it without direction. They’ll be the ones who use it as a multiplier—amplifying human creativity, speeding up execution, and scaling across every channel.

Ready to scale your message across every channel without losing the creative spark? Let’s start a conversation about how AI-driven multi-channel marketing can help you test faster, personalize deeper, and win bigger.

For years, the creative toolkit has expanded in increments. Creative teams have always adapted to new tools. The printing press made design reproducible. Television opened a new stage for storytelling. Digital tools turned Photoshop into the 11th commandment. And the iPhone put a camera in everyone’s pocket. Each shift changed the way creative work was made. 

But nothing—and we mean nothing—has shifted the creative process as radically, as quickly, and as irreversibly as AI. 

This isn’t about replacing human creativity (spoiler: it can’t). It’s about how creativity itself is evolving when human intelligence and machine intelligence collide. And for growth marketers? That collision is where the magic (and ROI) happens.

Speed + Possibility: AI’s Double Benefit

Let’s start with the obvious: speed.

AI eats bottlenecks for breakfast. Drafts that used to take weeks now take minutes. Concepts that required three brainstorms and a rewrite can be iterated in an afternoon. Need 20 headline options before your 9 a.m. client call? Done.

And in growth marketing, where speed-to-market often means the difference between a campaign that crushes and a campaign that never even launches, speed is a game-changer.

But speed is only half the story.

The bigger benefit? Possibility.

AI is giving brands access to creative executions they never could have touched before—because of time, talent, or most often, budget.

• The indie brand with a shoestring ad spend can now visualize cinematic scenes that once required a Hollywood crew.
  
• The scrappy startup can test five campaign directions instead of one, because ideation cycles are measured in hours, not weeks.
  
• Even global brands with big budgets are reallocating spend—not on “making the thing,” but on “testing more things” until the winning creative emerges.
  

AI isn’t just a time-saver—it’s a door-opener.

What’s Working Today: AI + Video

Nowhere is the AI impact more visible (literally) than in video.

Video has always been king for engagement. But video has also been expensive—time, talent, production, editing, licensing, the whole circus. AI just handed marketers a golden ticket.

Here’s how teams are using it right now:

• Custom footage from prompts or stills
  Tools like Runway, Pika Labs, and Synthesia can generate realistic video sequences from nothing more than text input or a single static image. Suddenly, your product demo doesn’t need a studio shoot.
  
• Impossible locations made possible
  Want to set your campaign in a neon-lit Tokyo street, a 1920s jazz club, or a Martian landscape? Previously, that was a million-dollar ask. Now it’s a prompt away.
  
• Budget-friendly production
  Even “simple” video concepts—explainer animations, motion graphics, testimonial-style clips—are becoming accessible to brands that never had the dollars (or the editors) to make them.
  
• Faster concepting and iteration
  Need campaign storyboards or test imagery to pitch a big idea? AI generates visuals on the fly, accelerating approval cycles and freeing humans to focus on strategy instead of scrambling for stock shots.

And here’s the kicker: it’s not just the “big” campaigns. AI is helping with the unglamorous but necessary stuff too—snackable social clips, sales enablement videos, even internal comms. Things that used to be “nice to have if we had budget” are suddenly doable.

AI is democratizing video.

Beyond Video: How Catalyst Is Putting AI to Work

At Catalyst, we see AI as more than a one-off tool—it’s part of the creative bloodstream. Here’s how it shows up in our process today:

• Concepting: AI helps us generate early campaign ideas, audience insights, and fresh angles we might not have considered in a human-only brainstorm.
  
• Copywriting: We use AI to accelerate ideation—drafting headline options, tightening messaging, or testing different tones—before a strategist polishes it for brand nuance.
  
• Image generation: AI allows us to quickly create mockups, pitch visuals, and campaign imagery that would otherwise stall in production bottlenecks.
  
• Video: From storyboarding to fully generated clips, AI tools are shortening production timelines and letting us experiment with creative variations at scale.
  

But here’s the key: we don’t stop at “trying out cool tools.” We’ve built infrastructure to make AI a repeatable, scalable advantage.

Where Humans Still Rule

Now let’s address the panic button: “Is AI replacing creative teams?”

Short answer: no. Long answer: absolutely not.

Here’s what AI can’t do:

• Choose the right story for your audience
  
• Understand cultural nuance (at least, not well)
  
• Infuse humor, irony, or emotion that actually lands
  
• Know when “too much” is really… too much
  

AI is brilliant at pattern recognition. But culture-shaping, brand-defining, emotionally-resonant creative? That still requires taste, judgment, and an understanding of the messy, irrational thing we call being human.

In other words: AI may be the rocket fuel. But humans still set the course.

The Risk of “AI Sameness”

There’s also a danger in leaning too hard on machine outputs: everything starts to look the same.

We’ve all seen it—those too-smooth hands, that uncanny animation style, the copy that sounds fine but says nothing. If you let AI run the show unchecked, you risk producing content that blends into the noise instead of breaking through it.

This is where human oversight is critical. Creative teams don’t just generate—they curate. The real advantage is not “let AI make something” but “let AI make ten somethings, and then let a human choose the one that surprises, delights, or disrupts.”

The Catalyst POV

At Catalyst, we orchestrate this balance intentionally:

• AI accelerates: ideation, mockups, early drafts.
  
• Humans elevate: strategy, vision, storytelling, taste.
  
• Data validates: we test, refine, and double down on what works.

The growth marketing teams that thrive won’t be the ones who resist AI, or blindly outsource everything to it. They’ll be the ones who use it as a creative multiplier—expanding what’s possible while letting human intelligence steer toward impact.

Because the real creative revolution isn’t about AI doing our jobs. It’s about AI giving us back the time, space, and possibility to do our best work.

The Bottom Line

AI is transforming creative work. Not hypothetically. Not in the future. Right now.

• Speed is the obvious benefit—but possibility is the bigger prize.
  
• Video is the frontline where AI is making creativity more accessible, more scalable, and more experimental.
  
• Human creativity is not just relevant, but essential, to guide AI outputs toward resonance, not sameness.
  
• Catalyst is investing not just in tools, but in systems like our AI Innovation Lab to turn experimentation into repeatable client value.

Growth marketing just got an upgrade. And if you’re ready for what’s possible, the future’s wide open.

Ready to see what AI-powered creativity can unlock for your brand? Let’s start a conversation about how human imagination and artificial intelligence can create work that’s faster, smarter, and more impactful.

The Rules Changed While No One Was Watching

While you were optimizing for “digital marketing services,” your competitors were building authority around digital transformation strategy. While you tweaked exact match bids, they let AI uncover high-intent audiences you didn’t know existed.

The game has shifted. Phrase match is dead. Exact match is weaker. Broad match has become Google’s growth engine. And here’s the kicker: Search and advertising are no longer separate channels. They have collapsed into one AI-powered experience.

This isn’t theory. It’s already happening. Google’s AI Overviews now appear in nearly one out of five desktop searches in the U.S. (Semrush, 2025). Semrush estimates 65% of all searches now end without a click. And Google reports advertisers using Performance Max see 20–30% more conversions than those clinging to legacy campaigns.

So, what does that mean for you? Success isn’t about chasing keywords or hand-tuning bids anymore. It’s about building topical authority, showing up in AI-generated answers, and feeding automation with the right creative and strategy.

From Keywords to Context

Search used to be about keyword density. Jam the right phrase in a headline a few times and you could climb the rankings. Not anymore.

AI doesn’t care how many times you say the word. It cares whether your content demonstrates real expertise, answers questions completely, and shows depth on a topic.

A common pattern we’re seeing: Businesses with dozens of thin, keyword-stuffed pages tend to lose ground as AI Overviews roll out. In contrast, consolidated content that covers an entire topic comprehensively is far more likely to surface in summaries.

Takeaway: If you’re still keyword chasing, you’re invisible.

AI Overviews Are the New Prime Real Estate

Yes, AI Overviews eat clicks. Publishers are reporting 25%+ traffic declines since their rollout. But showing up inside an Overview carries more weight than a standard blue link ever did.

Think of it as becoming part of the answer, not just a possible click. When buyers see your brand embedded in the summary itself, that visibility shapes perception even if they don’t click through.

Takeaway: This is where trust gets built now. If you’re not visible in Overviews, your competitors will own the conversation.

Automation Is the Default, Whether You Like It or Not

Performance Max and Demand Gen aren’t experimental anymore. They are how Google runs ads. Manual bidding is a relic.

Advertisers leaning into broad + Smart Bidding are already 20% ahead on conversions compared to those sticking to exact match only (Google Ads Data, 2025).

Takeaway: If you’re not letting AI optimize, you’re leaving efficiency and market share on the table.

The Match-Type Reality Check

Let’s cut through the noise:

• Exact Match = Guardrail
  Still worth protecting your highest-value queries, especially in B2B. Think “pharma validation consultant,” not “pharma internships.”
  
• Phrase Match = Dead
  Redundant. Industry tests show it adds no incremental value over broad.
  
• Broad Match = Growth Engine
  With Smart Bidding, broad unlocks queries you’d never imagine bidding on. It interprets intent across context, audiences, and behaviors to deliver incremental scale.

Takeaway: Exact protects, broad grows, phrase is done. Build your mix accordingly.

The Challenges Marketers Can’t Ignore

Here’s the hard truth:

• Zero-click searches are now the majority. 65% of searches don’t leave Google (Digiday, 2025).
  
• Referrals are declining. Global traffic referrals fell 6-7% year over year (SimilarWeb, 2025).
  
• Transparency is shrinking. AI automation hides which levers drive results.
  
• AI can flatten brand nuance if you don’t set creative guardrails.
  

Takeaway: AI drives efficiency, but it can’t be your strategist. That’s still your job.

Quick Wins You Can Try This Week

Not ready for a full overhaul? Start small.

• Switch one campaign to broad match testing. Run it side by side with exact for two weeks.
  
• Add FAQ sections to your top 5 landing pages. AI eats up concise answers, so make them easy to pull.
  
• Track your AI Overview presence. Google your brand + top 10 keywords and log where you show up.
  

These quick wins give you data fast and momentum to push bigger changes.

Your 2025 Roadmap

Once you’ve tested the waters, here’s where to go next:

1. Audit for Authority: Spot the content gaps your competitors already own.
   
2. Restructure for AI Readability: Think FAQ snippets, expert quotes, multimedia.
   
3. Run AI Pilots: Compare Performance Max against your legacy campaigns.
   
4. Double Down on UX: Sites that load faster see 24% higher engagement (Google, 2024).
   
5. Rethink Measurement: Don’t just count clicks; track Overview visibility and brand lift.
   
6. Balance AI + Human Oversight: Let machines optimize, but protect your brand voice.
   

Final Word

AI isn’t a shiny add-on. It’s the foundation of how search and advertising work today. The winners will be the ones who let machines optimize while humans set the rules, strategy, and story.

If you don’t have an AI-first search and ad strategy in place by Q4 2025, you’re already behind. At Catalyst, we’re helping brands get there now. Let’s build it together.

Why We’re Building Tomorrow’s Marketing Solutions Today

There’s this moment when you realize the ground beneath your entire industry is shifting—and you have two choices. You can either ride the wave of what’s next or be overwhelmed by it.

That inflection point came when we watched multiple team members independently discover breakthrough AI applications, each getting remarkable results—but with no systematic way to capture those findings or scale them for our clients. We had pockets of brilliance happening everywhere, but no coordinated effort to turn those experiments into sustainable competitive advantages.

More importantly, we realized something that changed everything: to move ahead, we couldn’t just use AI tools to do marketing in the same way—only faster or at scale. We had the opportunity to fundamentally change how we approach our clients’ challenges. Instead of simply automating existing processes, we could reimagine the entire problem-solving framework.

That’s when we knew it was time to get serious. Not just about using AI tools—everyone’s doing that now—but about pioneering how AI and human intelligence work together to solve complex challenges in completely new ways.

So at the beginning of Q3, we officially launched the Catalyst AI Innovation Lab. The stakes? Agencies can either lead this transformation or watch their relevance fade.

What the AI Innovation Lab Really Means

Let me be clear upfront: this isn’t just a fancy name for “we use ChatGPT sometimes.” The AI Innovation Lab is our systematic commitment to transforming how businesses scale in the AI era through deliberate, methodical innovation.

Here’s what makes this systematic—we’ve built a structured engine that:

• Tests up to five emerging AI tools monthly to find the best options for in-house and customer use
• Runs controlled client pilots using real challenges and rigorous A/B testing
• Develops proprietary methodologies from successful experiments
• Shares thought leadership and insights that establish thought leadership in AI-enhanced growth marketing

Our dedicated team is passionate about AI innovation and solving real customer problems. We’re not just playing with shiny new tools—we’re asking hard questions like, “How can we use this to fundamentally change how we solve our clients’ marketing challenges?” and “What becomes possible when we stop thinking about AI as a way to do existing things faster?”

The difference between having an “innovation lab” and just using AI tools is treating innovation as a discipline, not a one-off. Every experiment flows into a repeatable playbook, every insight gets documented, and every lesson improves the next round.

Beyond Tools—Building AI-Enhanced Capabilities for Client Growth

One of the biggest misconceptions about AI in marketing is the “shortcut myth”—that it’s some kind of magical vending machine where you type in a simple prompt and boom, all your marketing problems are solved.

That approach is exactly why so many companies are getting mediocre results from their AI investments.

The real power emerges when you treat AI as a creative multiplier, not a shortcut. When you engage AI in genuine dialogue—when you iterate, refine, and collaborate with it—you start seeing exponential improvements. It’s when you take what is inherently human and multiply it that AI becomes transformative.

This is why our approach to AI tool evaluation is so strategic. We don’t jump on every new tool that launches. Instead, we invest significant time reviewing, testing, and understanding how different AI capabilities solve real client challenges before they ever see an experimental approach.

Here’s how we do the heavy lifting first: We work through pain points, test edge cases, and refine processes within our own operations. We fail safely, learn quickly, and only scale what actually works.

Currently, we’re running experiments across multiple areas: developing AI-enhanced personas that test our work before it goes live, creating automated workflows for common marketing challenges, and building proprietary prompt libraries that consistently deliver high-quality outputs.

Let me give you a concrete example. Recently, I was working on a webinar outline that was solid. But when I ran it through one of our AI personas—a virtual representation of our target audience that we’ve fine-tuned based on extensive research—it gave me feedback that completely changed my approach. “I like the content,” it told me, “but it feels too technical. You need more story elements to keep people engaged.”

That was a great call-out I may have missed, leading to a much more effective presentation. But notice what happened: I still did the strategic work of understanding the audience, defining objectives, and structuring content. AI just helped me see blind spots and refine execution.

This is what I mean by AI + HI (Human Intelligence). The human provides strategic foundation, creative vision, and business context. AI provides analytical power, scalability, and the ability to process information at speeds humans simply can’t match. Together, they create something more powerful than either could achieve alone.

Preparing Our Team for the AI-Centric Future

None of this would be possible without serious investment in our team’s capabilities. You can’t just hand people AI tools and expect transformative results—you need to build genuine AI fluency across your organization while maintaining the human strategic excellence that makes the work valuable.

That’s why we developed a comprehensive 16-week curriculum on AI and growth marketing. This wasn’t just lunch-and-learns about the latest tools. This was a systematic program designed to help every team member understand not just how to use AI, but how to think strategically about AI applications in their specific role.

The most important element was demystifying AI for people who might have been intimidated by the technology. For a lot of people, AI feels like magic—some mysterious process happening inside a black box. Our educational program stripped away that technological barrier and helped people understand AI as a fundamental tool that enhances their existing capabilities. It also explores the ethical concerns and bias inherent in AI and how to balance its use while taking into account today’s very human concerns.

The results have been remarkable. Ideas that used to be shelved because of time constraints, budget limitations, or practical impossibilities can now be evaluated purely on their creative and strategic merits. We can run personalization at scale, test campaign concepts with virtual audiences before spending media dollars, and generate multiple creative variations without exponentially increasing production costs.

This democratization of capabilities means we can deliver higher-quality solutions to a broader range of clients. Small and mid-size businesses now have access to sophisticated marketing strategies that were once only available to enterprise clients with massive budgets.

What This Means for Growth Marketing’s Future

We’re not just witnessing incremental change—we’re at the beginning of a complete reimagining of what growth marketing can accomplish. The democratization we’re seeing now is just the start.

The creative multiplier effect will compound exponentially. Today, our AI personas help us refine content and catch blind spots. Within 24 months, we’ll be running virtual focus groups with AI-generated personas that test campaign concepts in simulated market conditions before spending a dollar on media.

The speed of innovation will separate winners from casualties. While competitors struggle with basic automation, AI-native agencies will deploy predictive models that identify high-value prospects before they even realize they need your product. We’ll craft messaging that evolves based on real-time sentiment analysis and optimize campaigns that learn faster than any human team could manage.

But here’s what excites me most: AI will finally solve the attribution problem that’s plagued marketers for decades. We’re developing models that trace influence across every touchpoint and prove definitively which activities drive actual business growth. For CMOs, this means the end of “marketing as a cost center” and the beginning of marketing as a measurable, scalable revenue engine.

The organizations that build systematic AI + HI capabilities will outperform competitors and make their approaches look fundamentally obsolete.

Leading the Evolution, Not Following the Trends

The goal of the AI Innovation Lab is not only staying current with technology trends but also taking responsibility for defining what excellent AI-enhanced marketing looks like and sharing those insights with our industry. We’re committed to documenting experiments, sharing learnings, and contributing to the broader conversation about how AI can be used ethically and effectively in marketing.

The Q3 launch is really just the beginning. We have ambitious plans for expanding research, developing new methodologies, and creating even more sophisticated tools for our clients. But the foundation we’ve built—systematic experimentation, rigorous testing, and genuine collaboration between AI and human intelligence—that’s what will enable everything else.

If you’re a marketing leader thinking about how AI fits into your organization’s future, I’d encourage you to think beyond individual tools and tactics. The real opportunity is in building systematic capabilities that allow your team to consistently leverage AI as a creative and strategic multiplier.

The future belongs to organizations that embrace AI not as a replacement for human insight, but as a powerful amplifier of human creativity, strategy, and execution. That’s what we’re building at Catalyst, and I couldn’t be more excited about where this journey leads us next.

Ready to explore how AI-enhanced growth marketing could transform your business? Let’s start a conversation about what’s possible when human ingenuity and artificial intelligence work together to solve your biggest marketing challenges.