Blog | AI in Marketing: Where to Begin

​​1. Start with the Data You Already Own​​​

AI is only as good as the data it learns from. Before investing in new tools or platforms, you must be confident that your marketing data is clean, connected and trustworthy. 

 

In our previous blog, we shared a 6-step checklist to improve marketing data quality starting with auditing your sources and aligning key fields across systems. This is essential groundwork. Without reliable first-party data, AI-powered tools will underperform or even mislead.

 

Ask yourself the following: ​

• Are your CRM and marketing platforms capturing complete and consistent data?

• Is data accessible across functions, or trapped in silos?

• Can your team act on insights, or are they spending time cleaning and exporting?

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2. Revisit the Funnel. It May No Longer Be Fit for Purpose​​​

Traditional B2B funnels are built on the assumption that leads move through a predictable, linear path. AI offers the potential to personalise journeys, predict intent and score opportunities in real-time.

 

But this requires rethinking how your funnel is structured and measured. Now is the time to:

• Re-evaluate your lead stages and conversion metrics

• Map your customer journeys with real data

• Identify where manual hand-offs or friction reduce impact

 

Before jumping into AI tools for lead scoring or journey orchestration, make sure your funnel structure reflects how customers actually behave.

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3. Conduct a Practical Gap Analysis: Tools and Skills​​​

AI adoption is not about chasing trends. It is about identifying specific use cases where automation, prediction or content generation could reduce time-to-value or enhance personalisation.

 

Conduct a simple audit:​

• Where are you manually analysing data that could be automated?

• Which tasks are repetitive and could benefit from AI-generated support (e.g. A/B testing, copy variation, predictive scoring)?

• Which tools do you already use that offer AI functionality you’re not yet taking advantage of?

 

In parallel, assess your team’s current skill set:​

• Do they understand how AI fits into marketing workflows?

• Are they confident in interpreting AI outputs or using AI-enhanced tools?

• Where could short-form training or pilot projects help build confidence?

• Do they have sufficient bandwidth to continue their daily projects?​​​​

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4. Train, Don’t Replace​​

The greatest misconception around AI in marketing is that it requires a new team of data scientists and technologists. In reality, most successful AI adoption happens when existing marketing teams are trained and empowered, not replaced.

 

Your current team knows your customers, your market and your business. These are assets you cannot teach overnight.

 

Up-skill through:

• Internal learning sessions and guided tool use

• Short-term pilots focused on a single use case

• Pairing marketers with AI champions or external experts for coaching

 

The goal is to augment their capabilities, not replace their judgment.

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5. Plan for Ongoing Data Maintenance​​​

But a one-off clean-up is not enough. Build a plan for regular data maintenance including periodic audits, automated deduplication and workflows for updating records. If you have not done so already, consider appointing a data controller or using external partners if internal resources are limited.

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This will help you maintain high data quality as your database grows and customer behaviours evolve.

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Final Thought: A Positive, Sustainable Approach​

AI in marketing does not need to be overwhelming. It also does not require a complete reset. For B2B marketing leaders, the first step is not about buying new tools or hiring external experts. It is about assessing what is already in place. Your data. Your funnel. Your people. And building from there.

 

The most successful teams are not always the ones with the largest budgets or the most advanced platforms. They are the ones who stay curious, invest in learning and bring their teams along on the journey. AI should not replace the knowledge and experience already within your organisation. It should help unlock it.

 

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To learn how we could help your organisation and team, contact us.

 

Published: 15 September 2025​​​​​​​