The easiest return to demonstrate on a marketing investment in AI is a saving. A task takes fewer hours, production costs fall and a campaign generates more versions within the same budget. These are useful gains, particularly for marketing teams under pressure to prove their contribution to the business.
But what happens to the quality of the decisions behind the work? A brand can become faster and cheaper to run while becoming easier to overlook.
If AI adoption concentrates entirely on reducing the resources needed to produce marketing, businesses risk weakening the very capabilities that give that marketing value: understanding people, recognising an original idea and deciding when to take a creative risk.
As production becomes more accessible, those capabilities deserve greater investment.
What Google leaders say
Conversations with four leaders at Google brought this tension into focus. Across their different perspectives on AI and marketing, a common concern emerged…efficiency alone is too narrow an ambition for a technology with the potential to expand what creative teams can do.
Neil Hoyne, Google’s chief strategist, described the consequences of an excessive reliance on certainty: “They go for the sure thing…and then they wonder why they’re not differentiating themselves.”
It is a familiar problem in marketing. Evidence helps teams make informed decisions, but it can also become a shield against making difficult ones. A concept that resembles something successful is easier to defend in a meeting. An unfamiliar idea demands more conviction from the people proposing it and more trust from those approving it.
A borrowed line
AI can accelerate that preference for the familiar if teams use it chiefly to reproduce established patterns. The result may be polished, relevant and technically competent, yet offer little reason to remember which brand produced it.
The responsibility for avoiding that outcome sits with the people commissioning and evaluating the work. They must decide what the brand wants to stand for, which conventions it should challenge and how much uncertainty they are prepared to accept.
This matters locally, where cultural understanding requires more than inserting a Southafricanism into a global campaign. Humour, aspiration, status and belonging carry different meanings across communities and contexts.
A line can be linguistically accurate and still feel borrowed. Recognising that difference requires proximity to the people a brand hopes to reach.
That understanding takes time; listening, observing, questioning assumptions and allowing an insight to develop before turning it into an execution. If every hour saved through AI is removed from the budget, where will that work happen?
Investment discussion
Amy Bloemendaal, global lead on Google’s Accenture account, raised a related concern in our conversation: businesses that focus only on deductions and efficiency can miss opportunities to use AI to accelerate growth.
For marketing leaders, this should change the investment discussion. Alongside asking how much time a tool saves, they should ask what the team can now attempt. Could it explore more creative directions, investigate an overlooked audience or test an idea that previously seemed too expensive to pursue?
Aprajita Jain, Google’s chief brand and creative marketing evangelist, described a useful division of labour: “AI builds the engine; humans provide the empathy.”
The practical challenge is making room for that empathy in the workflow. Giving a team better tools achieves little if its brief remains shallow, its deadlines leave no room for reflection and its approval process rewards predictable work.
Interesting approach
The research partnership between Google DeepMind and film studio A24 offers an interesting approach. Its stated ambition includes involving filmmakers directly in shaping technology around their creative processes. That is a useful principle for brands too; the people responsible for creative quality should help determine how the tools are used.
The brief itself also deserves more scrutiny. Mélissa Chan-Cheape, a product marketing manager at Google, pointed to the information people leave unsaid when asking AI to help tell a story.
Marketers should recognise that problem. Briefs often contain confident statements about audiences without explaining the observation behind them. Terms such as ‘authentic’, ‘relatable’ and ‘engaging’ can conceal an absence of clear thinking. A fluent response to such a brief may make that weakness harder to spot.
Judgement before generation
Creative judgement therefore begins before generation. It involves asking what the audience actually cares about, what evidence supports the proposed insight and what the brand has earned the right to say.
It also continues after generation. Someone must reject the plausible but generic option, recognise the promising idea and take responsibility for the final choice.
Marketing leaders should assess AI adoption against those standards as well as cost and speed. Savings have strategic value when they create capacity for better decisions and more ambitious work. Producing more is increasingly easy. Giving people a reason to care remains the harder job.
* Summary created by AI
Kwena Semenya is senior creative strategist at Machine.
