Getting Started with AI in Marketing: Stepping Stones for Leaders

Mladen Tošić
Jul 5, 2025
5 min read

As brands like Reckitt and Unilever push ahead to embed AI into their marketing, many others are still finding their feet—experimenting with tools, running pilots, but not yet fully aligned on where this journey leads.

“We’re tinkering with AI, but we’re not yet aligned on what ‘doing something’ really means” — CMO, global brand

This sentiment comes up again and again when I speak with marketing leaders.

AI is already changing how marketing teams work day-to-day—and in some cases, what they do altogether. The challenge for leaders is to help their teams navigate this change strategically and cohesively. Done well, it won’t be disruptive. It can be positive and empowering—unlocking new potential and value.

What follows isn’t a blueprint—it’s a set of stepping stones I’ve seen work in different contexts. They reflect how teams tend to move through this change. But as with all transformation, reading the list can only take you so far. At some point you have to go do it. (It’s a bit like watching someone else work out versus actually picking up the weights yourself.)

And let’s be honest—some leaders are better at asking for help than others (you know who you are). Of all topics, this one should feel easier to engage on—nobody has fully nailed it yet. Consider whether you’re set up for success or if you’re risking overpromising to yourself and your team. Whether you empower someone internally or bring in external expertise, being active and leading through this change will pay off in many ways.

A row of natural stone steps crossing a calm river, symbolising progress and steady movement forward — *Progress in AI isn’t about giant leaps—it’s about taking the next step. One stone at a time.*

🌱 The Stepping Stones: What to Do to Get Started with AI in Marketing

1. Align on Purpose, Priority, and Pace

Start by understanding what this change means for your business. This isn’t a one-off “LT discussion”—it’s often iterative, informed by early team engagement too.

Key questions:

What do we mean by “AI in marketing”? Are we talking GenAI for content, predictive analytics for targeting, or a broader transformation of how we work?
Why does this matter to us? Growth? Staying competitive? Managing tighter budgets?
How big is this change? Tactical—improving how we work? Or strategic—reshaping how we engage customers, clients, and partners?
What’s our timeline—6 months? 2 years?
Who owns this? Who sponsors it? Do we need external expertise?
What does success look like—not in abstract, but in day-to-day impact?

🟢 Tip: Write it down. Alignment isn’t about vague agreement; it’s about clarity everyone can act on.

2. Build Confidence by Engaging Your Team Early

As leadership shapes direction, involve your team to build confidence and shared ownership.

Run listening sessions—many are already experimenting quietly
Share your emerging perspective and invite feedback
Encourage exploration with shared norms around usage and quality
Engage external partners or vendors for know-how—but don’t rely on them alone

One CMO described how their organisation flipped the narrative: “We moved from giving permission to use AI, to setting the expectation that first drafts should be AI-assisted. It’s not about replacing people—it’s about unlocking their creativity.”

🟢 Tip: Don’t wait for everything to be finalised. Early engagement can shape smarter strategy.

3. Create Shared Practices and Guardrails

As usage grows, establish consistency—not heavy-handed control, but clear expectations.

Consider:

Guidelines for acceptable use (e.g. no confidential data in public tools)
Legal, ethical, and brand boundaries
Sharing best practices and prompt examples
Recognising smart AI use in team meetings

Depending on your business, you’ll also need to consider:

Client or customer requirements around data use, copyright, and IP
Industry-specific regulatory and compliance standards
Governance for AI outputs to ensure quality and accountability

🟢 Tip: As you progress, engage others beyond marketing—finance, legal, operations—and even clients and customers. AI’s impact rarely stays siloed.

4. Identify, Prioritise, and Manage Use Cases

Now your team is engaged and experimenting, it’s time to focus. Start identifying where AI can have the biggest impact and structure these opportunities into a prioritised backlog.

Look for:

Manual-heavy tasks (e.g. producing asset variants, translating campaigns)
Bottlenecks or pain points
High-impact decisions (e.g. segmentation, planning)
Opportunities for differentiation (where AI elevates creativity or insight)

💡 Common early use cases:

AI-generated content briefs and copy
Weekly insights summaries using Perplexity or ChatGPT
Dynamic email subject lines or landing page variants
Multilingual campaign adaptations

💡 Emerging opportunities for advanced teams:

Agentic AI systems that can run multi-step workflows—like autonomously generating, testing, and optimising campaign variants across channels
AI agents for campaign orchestration, automating repetitive processes while humans focus on creative and strategic direction

🎯 Example backlog items:

Test AI-assisted social publishing workflows
Create an internal “AI prompt library”
Pilot GenAI for campaign reporting automation
Reduce production timelines for social content by 30%

🟢 Tip: Bring your team together regularly to share what they’re trying. A workshop can help surface ideas and prioritise a few to back strategically.

🟢 Tip: Involve other parts of the business—especially finance. Overcommunicate progress, share success stories, and track key metrics. This isn’t just about tools; it’s a new way of working for marketing.

🛠️ Making it Happen: How to Lead the Change

Rethink Your Operating Model

For brands with sizeable marketing teams, AI will reshape how work gets done.

Consider:

What stays in-house vs outsourced?
How team structures shift as automation takes on production
New roles/capabilities (AI product managers, prompt engineers)
Governance and decision-making in faster cycles

This isn’t about tearing down your current setup—but acknowledging that as AI integrates, your marketing operating model will evolve alongside it.

Rethink Your Commercial Model (For Agencies)

For agencies, AI doesn’t just change execution—it challenges how value is created and delivered.

Questions surfacing:

If clients pay by the hour, what happens when output doubles in half the time?
How do you price creativity when AI accelerates production but not necessarily strategy?
What happens to team structures when fewer people are needed?

Agencies that embrace these discussions can create new, AI-enabled service models that strengthen client relationships.

Keep It Moving: Evolve, Don’t Overhaul

AI in marketing isn’t “one and done”—it’s an ongoing evolution that will unfold over years. Leaders who treat it as “done” after a few pilots will fall behind.

🟢 Tip: Set up a regular forum—“Marketing Forum” or something more distinctive—to bring marketing and adjacent teams together. In my work with organisations, I’ve seen such forums galvanise teams and embolden them to lead change rather than react to it.

Why This is Hard—and Why It’s Worth It

This is both a strategic and capability shift, happening at a pace we haven’t seen before. Leaders need to:

Stay open to new technologies and new ways of working
Set a clear vision and direction amid uncertainty
Apply change management practices to support and empower their teams

There are no perfect answers—it’s still a moving target. But the opportunity is enormous for those who lead proactively and help their teams do the same.