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Dec 24, 2024 | 5 min read

5Ps of Marketing AI : Scaling Your 2025 Strategy & Roadmap

Picture of Catherine Toms

Catherine Toms

AI Expert | Educator | Consultant

If 2024 was the year of dabbling with AI tools and pilots, then 2025 has marketing teams scratching their heads, asking: how do we scale AI and see real ROI from our efforts. 

If you’re struggling with this, you’re not alone! Over 50% of teams say AI strategic planning is one of the biggest skills gaps we see. 

We all know the good old 4P’s of Marketing, so here’s the 5P’s you need to know to plan and scale a Marketing AI roadmap for 2025:

Step 1: Priorities – The Why

The biggest issue we see? 

Businesses diving into AI tools without a clear plan, goals, or strategy. They test a bunch of tools without knowing if they’ll add value.

Start with your highest priorities. Define the problem or opportunity first. Use your data to find your biggest productivity blockers and customer friction points. Discover where you could improve profits or performance.

The benefits?

A clear path forward where everyone knows why you’re doing it and what good AI looks like.

You can speak the boardroom language: “If we invest in X, we expect Y to happen.” This helps secure buy-in and budgets.

Step 2: People – The Who

You can’t do this alone. Start by gathering your AI marketing squad—this isn’t about anything official or fancy. Just identify the key people you need to help develop practices and processes that understand the biggest impacts AI can have in their area or teams. 

Here’s how to get started:

  • Gather your squad: Who else might you need to bring in? Identify the relationships you need to build. Taking action can be as simple as setting up a coffee and a chat.
  • Think cross-functional: You’ll need to see how AI will impact each unique team and tap into their expertise on where it can add the most value.
  • Start small: Keep it to 1-2 perspectives from each area to avoid getting bogged down.


Pro tip: Include the sceptics—people who aren’t totally sold on AI. They’re more likely to challenge your ideas, think about risks, and help make your AI strategy stronger and more balanced.

Step 3: Process – The What

Reimagine how things could work better with AI in the mix. 

Map out where AI can add the most value without disrupting workflows. Think of it as building your team of AI assistants. Decide which tasks to outsource to AI, while humans focus on overseeing, vetting, and training AI outputs for compliance and safety.

Before you start you need 3 things:

  • Simple Process Maps – How does work get done and flow today – where are your biggest headaches, time sucks and friction points?
  • Data – AI is the accelerator, but data is the fuel. Gather and clean your data because, remember: rubbish in = rubbish out.
  • Guardrails and ethics – Set clear guidelines for AI use – what you can and can’t do – to keep things safe and compliant.

Step 4: Platforms – The How

Before rushing out to buy new AI tools, start with what you already have. Many platforms (your CRM, CDP, Marketing Automation, Canva, META, Google, and HubSpot etc etc) already have AI functionality built into their systems.

Here’s what to do:

  • Map your martech stack to identify existing AI capabilities.
  • Talk to your vendors—what’s already available, on their development roadmap or around the corner?
  • Fill the gaps only if the tools solve a specific problem. Avoid tool overload by ensuring any new tech integrates smoothly with your current systems.
  • Remember: Tech is easy to buy but hard to implement, and even harder to replace. Make sure whatever you bring in aligns with your goals and scales with your business.

Step 5: Performance – The ROI

Once you’ve tested your use cases, it’s time to focus on measuring ROI and proving the case for investing. 

Define clear KPIs to track the impact of your AI initiatives. It’s not just about operational efficiency—AI should be driving measurable quality, effectiveness, and growth. 

Ask yourself:

  • Is it improving customer experiences?
  • Are outcomes better and faster?
  • Is it contributing to better leads, optimised performance or more growth? 

This is your proof that AI is delivering value beyond just doing things faster.