There’s a new expectation in the C-suite. The moment AI enters the conversation, the assumption is that marketing will suddenly deliver “quicker, better, and faster” – with fewer people and at a fraction of the budget.

The reality is far more complex.

Every CMO must start with a clear vision: why are we using AI, and how does it enable the business strategy? This clarity ensures we invest in the right capabilities – not the loudest technology. If an AI tool drives measurable growth, it becomes a business asset – not a technical experiment. If not, it’s just a shiny distraction.

Our role is to bridge the gap between this new expectation and a practical reality. We are being reforged from brand storytellers into growth orchestrators, and this transformation is built on data, technology, and governance.

Moving from “gut feel” to growth engine

For decades, many strategic marketing decisions were based on an age-old “gut feel”. We no longer have that luxury. The business now expects marketing to be a scientific, technology-enabled growth engine, and they expect us to prove it.

This is the biggest shift: we are moving from being accountable for brand awareness and campaign execution to being accountable for business growth.

This means using AI tools, like predictive analytics, to tie every rand we invest directly to a revenue outcome. But to do that, we must first solve the data problem.

The CMO as the new data champion

AI enables us to become far more data-driven, but it comes with a major challenge. We still face huge hurdles with data collection, data management, and having a single source of truth.

This is where marketing must step up. We need a strong data foundation, and if the business isn’t owning it, we must become the initiators or, at the very least, the key influencers. We must work with the operations teams who own the data to ensure it’s captured correctly and structured in a way that’s helpful for everyone. Investing in data quality, governance, and integration – and finding the right team to support it – is critical.

If your data is incorrect, your AI will fail. It’s that simple.

From once-off campaigns to continuous experiences

With a foundation of clean data, AI allows us to move from running disconnected, once-off campaigns to creating continuous, personalised customer experiences.

We can use AI to interpret insights from all our data sources—be it a person-to-person interaction, an after-sales survey, or website behaviour. This allows us to design specific customer journeys and personalise the experience at every touchpoint.

This can be as simple as an AI-powered chatbot providing 24/7 support, or as complex as an automated lifecycle marketing programme that nurtures a customer from acquisition to retention, all without manual intervention.

The human is not redundant, but rather the refiner

We cannot be afraid of these tools. AI is here to enable us to be better at our jobs, but it does not replace humans. An AI tool will give you an output, but it still requires human intervention for refinement.

It lacks the intrinsic, nuanced understanding of our business. It doesn’t know the language of the brand, and it cannot appeal to humans without a human guiding it.

This is a critical conversation every CMO must have with their CIO or CTO. We must brief them on the risks of using a tool like ChatGPT to replace paid specialists. An AI tool does not have the strategic understanding of your brand that a specialist does. It is a powerful partner to make that specialist better, faster and more data-driven. It is not a replacement for them.

The new team and the new policy

This shift puts immense pressure on me as a CMO, but it also puts pressure on my team. We have to rethink our traditional marketing roles and create an environment for experimentation, with clear guardrails. We cannot risk exposing confidential company or client data to open AI platforms.

It is critical to make sure everyone in the marketing function is upskilled and empowered. We need to train them on:

• • How to write effective prompts.

  • How to use AI to interpret data and find insights.

  • How to use AI ethically and what the governance rules are.

This requires a culture shift. We must build a “test and learn” culture that values curiosity over perfection.

Perhaps, most urgently, the CMO must now be a policy driver. Most organisations are creating general AI governance policies, but they often haven’t considered the special, advanced requirements of a marketing function.

We have to initiate that conversation with the CIO or CTO. We must ensure that our requirements are not ignored and that our policies are adapted to allow us to innovate, while still managing risk. This is the new, strategic reality of marketing leadership.