The CMO of 2027
More Capability, More Responsibility
Marketing has never had access to this much capability. But according to Khensani Nobanda, Group Chief Marketing Officer at Nedbank, that capability comes with an equally significant responsibility. Speaking at the recent CMO Summit, Nobanda explored the strategic priorities that she believes will shape the role of the CMO as we move towards 2027.
Her starting point was a tension that many marketing leaders will recognise. Marketers have more data, more technology, more channels and more ways to understand customers than at any other point in their careers. Artificial intelligence has accelerated this further, providing tools that can generate ideas, personalise experiences, optimise media, predict behaviour and automate work at extraordinary speed.
Yet the commercial expectations placed on marketing have become tougher rather than easier.
“We’ve never had more capability. We’ve not been under greater obligation not to squander this very moment that we have in front of us.”
Marketing budgets remain under pressure. Boards want clearer evidence of growth. Customers expect relevance and personalisation without sacrificing their privacy. Organisations want greater speed without greater risk. At the same time, compliance and governance requirements are becoming increasingly complex.
For Nobanda, this makes 2027 an inflection point for the industry. The question is no longer whether AI will change marketing. It already has. “The question really is going to be: how will marketing employ this moment to become more invaluable to the enterprise?” she said.
She identified five priorities that she believes will help CMOs do exactly that.
Marketing has to speak the language of growth
Nobanda’s first priority is a shift away from marketing activity towards profitable growth.
Marketing has spent years talking about reach, impressions, engagement, share of voice, leads and click-through rates. These measures have a role, she argued, but they cannot become the destination.
“None of your CEOs wakes up hoping for a stronger click improvement. The business wants sustainable revenue, stronger client relationships, preference, retention, margin, lower cost to serve, and future demand.”
The strategic shift, therefore, is not simply about becoming better at proving return on marketing investment. It is about becoming clearer about the economic job marketing performs within the business.
Nobanda explained that this has already changed the nature of conversations within Nedbank. “Increasingly, we don’t discuss marketing activity in isolation,” she said. Instead, conversations focus on acquisition, retention, share of wallet, customer value and business growth.
The distinction is important because it changes how marketing is prioritised, measured and ultimately valued within an organisation.
Where is marketing creating demand? Where is it increasing the likelihood that a customer chooses the organisation? Where is it improving retention or lifetime value? Where is it reducing friction or cost? And where is it building brand assets that will make tomorrow’s growth easier?
For Nobanda, the CMO of 2027 cannot be the person brought into the room at the end of strategic-planning simply to communicate decisions that have already been made.
“The CMO of 2027 won’t be the person who arrives at the end of strategic planning just to communicate. It will be the CMO who will be in the room early enough to help shape where future growth will come from.”
That requires a different relationship with finance too. Rather than a defensive relationship in which marketing continually explains or protects its budget, Nobanda advocates a partnership based on a shared understanding of the value the organisation is trying to create. She also cautioned against treating brand and performance marketing as competing philosophies. Brand creates memory, meaning and future demand, while performance marketing converts the demand available now.
A mature growth strategy needs both.
AI tools do not make an AI operating model
Nobanda’s second priority is moving beyond AI experimentation towards an AI operating model. There is certainly no shortage of impressive AI demonstrations. A prompt can produce a strategy in seconds. Images can be generated almost instantly. Content variations can be created at scale, audiences simulated and campaigns optimised automatically.
But impressive demonstrations are not the same thing as transformation. The real challenge begins when AI moves from the edges of the marketing function into the way the function actually operates.
Who owns the data? Which decisions can an AI agent make? Which decisions should remain human? How is brand quality protected? How is customer information safeguarded? How are automated decisions audited? And how do organisations redesign roles rather than simply adding another tool to already overloaded teams?
For Nobanda, the next phase of AI in marketing is therefore an operating model challenge involving data, governance, workflow, talent, brand intelligence, measurement, decision rights and choice.
“We should not automate something simply because we can. We should automate where it creates a better outcome for the customer and a better outcome for the business.”
This is particularly pertinent in financial services, where technology and trust constantly intersect. Customers want banking to become more convenient, personalised and responsive, but financial institutions are also custodians of some of their most sensitive information. As Nobanda put it, customers do not simply judge whether an interaction was efficient. They also consider whether it was responsible, transparent and worthy of their trust.
“In our industry, convenience matters, but trust continues to remain the currency of action,” she said.
Her advice to CMOs is therefore to move beyond asking where AI can be used.
“Rather ask: which customer or business outcome becomes possible, or materially better, because AI is here?”
The customer is no longer necessarily acting alone
Nobanda’s third priority concerns a fundamental change to the customer journey.
Marketing funnels have traditionally been designed around human behaviour. A person searches, sees an advertisement, compares products, clicks and eventually makes a decision.
AI is beginning to insert itself into that journey. Consumers are using AI systems to compare prices, interpret reviews, shortlist products and help them make purchasing decisions. As those systems become more capable, AI may increasingly act as an intermediary between customers and brands.
Nobanda referred to South African research showing that consumers are already using AI to assist with shopping. However, she highlighted an important distinction between assistance and trust: only 23% of the South African consumers in the research said they trusted an AI agent to complete the checkout process for them.
Her conclusion was wonderfully concise:
“Convenience can be faster than trust.”
This creates an entirely new brand challenge.
Marketers will still need to ensure that their brands are distinctive, memorable and meaningful to people. But they will increasingly need to consider whether those brands are understandable to the AI systems assisting those people. Can an AI system understand what the brand stands for? Can it determine what the organisation offers and who that offering is intended for? Can it recognise whether the information is credible? Can it understand why the brand deserves to be considered?
For Nobanda, this does not make branding less important.
“In fact, it makes brand more important,” she said, because when functional comparison becomes easier, qualities such as trust, reputation, distinctiveness, meaning, experience and culture become more valuable.
Personalisation cannot come at the expense of trust
Nobanda’s fourth priority is a move from personalisation at any cost towards trust-based relevance.
Marketing technology has long operated on the premise that knowing more about customers allows organisations to personalise more effectively. AI makes that possible on an extraordinary scale.
But, according to Nobanda, marketers may be asking the wrong question.
“It’s not: how much do you know about me? It’s: do I trust you with what you know about me, and are you using it to make my life better?”
The difference matters.
There is a risk that marketers confuse technical relevance with human relevance.
“A message can be perfectly targeted and still feel wrong,” Nobanda said.
Content can be generated specifically for an individual and somehow remain generic. A recommendation can be accurate while still making the recipient uncomfortable.
And as synthetic content becomes increasingly abundant, something else happens.
“Authenticity becomes scarce.”
For Nobanda, trust therefore cannot be left until the end of the marketing process as a compliance exercise.
“Trust has to become a design piece,” she said.
What data should be used? What should be explained to customers? Where should a human remain involved? How much personalisation is genuinely useful? What choices should customers retain? And what is the reputational cost when an organisation gets these decisions wrong?
These are no longer questions for the technology or compliance teams alone. They are marketing questions.
When competence becomes cheap, distinctiveness becomes valuable
One of Nobanda’s most compelling observations concerned the effect AI may have on creative quality.
The greatest danger is not necessarily that AI will produce terrible content.
The bigger challenge is that it can produce competent content very cheaply.
“When everyone can create faster, average becomes abundant.”
That shifts where value lies.
Judgement matters. Taste matters. Cultural understanding matters. A recognisable point of view matters. Creativity that unmistakably belongs to a particular brand matters.
The answer, therefore, is not to choose between technology and human creativity.
“The CMO’s job is not to choose between AI and human creativity. It is to design a system in which AI expands the possibility of the team, while human judgement keeps the work valuable, responsible and distinct.”
Technology can provide speed and scale. It can expand what marketing teams are capable of producing.
But it cannot decide what a brand should stand for.
The CMO needs a new kind of literacy
Nobanda’s final priority focuses on the marketing organisation itself.
She believes AI literacy will become increasingly important for senior marketing leaders, but she does not interpret that as meaning every CMO needs to become a machine-learning expert.
Instead, it is about leadership literacy.
“I don’t need to be the smartest person in the room on every emerging technology that comes out, but I do need to know enough to ask better questions, to challenge assumptions, to recognise risk, to help teams make better decisions.”
The distinction is important.
CMOs need to understand what systems can and cannot do and make informed trade-offs between efficiency, customer value, brand quality and trust.
The teams surrounding them will need to change too.
“We need people who understand data, analysts who understand customers, technologists who understand brands, and marketers who understand economics,” Nobanda said.
Marketing leaders will increasingly need to move comfortably between the CEO, CFO, CIO, data teams, product teams, agencies and frontline employees without losing sight of the customer somewhere along the way.
For Nobanda, marketing cannot remain a department that simply receives a brief from elsewhere in the business. It has to become part of the business’s growth system.
She illustrated the different perspective marketing brings to the executive table with a comment she makes to her CFO:
“You look backwards. I look forward. I look forward with this organisation.”
Marketing brings curiosity, customer understanding, imagination, cultural fluency and the ability to create meaning. It also brings the courage to make choices about what a brand will and will not stand for.
“AI can make us faster,” Nobanda said. “It cannot make those choices for us.”
Five questions for the CMO of 2027
Nobanda closed her address by leaving marketing leaders with five questions to take back into their own organisations:
Can marketers explain, in business language, where marketing creates profit?
Has the organisation created an AI operating model, or has it simply accumulated AI tools?
Is the organisation designing for a customer journey in which people will increasingly be assisted by AI agents?
Have trust and distinctiveness become design principles rather than afterthoughts?
Are the capabilities and partnerships within the marketing function changing quickly enough to support the role marketing says it wants to play?
Together, these questions point towards a much broader interpretation of what the future of marketing looks like.
For Nobanda, it is not simply a future of better technology, content produced at industrial scale or “a race to automate everything that moves”.
The opportunity is much bigger.
It is about turning customer intelligence into enterprise growth. It is about using technology to remove friction and create value. It is about building brands that people, and increasingly the systems acting on their behalf, can find, understand and trust.
It is also about proving marketing’s commercial impact without sacrificing the long-term brand assets that make future growth possible.
Nobanda returned at the end of her address to the idea with which she began: marketers have never had more capability at their disposal.
The challenge for the CMO of 2027 is turning that capability into something that matters.